System and methods for processing analyte sensor data for sensor calibration

Information

  • Patent Grant
  • 11883164
  • Patent Number
    11,883,164
  • Date Filed
    Wednesday, January 12, 2022
    2 years ago
  • Date Issued
    Tuesday, January 30, 2024
    2 months ago
Abstract
Systems and methods for processing sensor analyte data are disclosed, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. The sensor can be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. Reference data resulting from benchtop testing an analyte sensor prior to its insertion can be used to provide initial calibration of the sensor data. Reference data from a short term continuous analyte sensor implanted in a user can be used to initially calibrate or update sensor data from a long term continuous analyte sensor.
Description
FIELD OF THE INVENTION

The present invention relates generally to systems and methods for analyte sensor data processing. Particularly, the present invention relates calibration of sensors.


BACKGROUND OF THE INVENTION

Diabetes mellitus is a disorder in which the pancreas cannot create sufficient insulin (Type I or insulin dependent) and/or in which insulin is not effective (Type 2 or non-insulin dependent). In the diabetic state, the victim suffers from high blood sugar, which can cause an array of physiological derangements (e.g., kidney failure, skin ulcers, or bleeding into the vitreous of the eye) associated with the deterioration of small blood vessels. A hypoglycemic reaction (low blood sugar) can be induced by an inadvertent overdose of insulin, or after a normal dose of insulin or glucose-lowering agent accompanied by extraordinary exercise or insufficient food intake.


Conventionally, a diabetic person carries a self-monitoring blood glucose (SMBG) monitor, which typically comprises uncomfortable finger pricking methods. Due to the lack of comfort and convenience, a diabetic will normally only measure his or her glucose level two to four times per day. Unfortunately, these time intervals are so far spread apart that the diabetic will likely find out too late, sometimes incurring dangerous side effects, of a hyper- or hypo-glycemic condition. Alternatively, a long term sensor implanted in a diabetic person can provide substantially continuous blood glucose measurements to a receiver carried by the diabetic and obviate the finger pricking method. Due to its biological interface, after it is implanted a long term sensor typically requires a waiting period after which its sensor data must be calibrated using the finger prick method or the like.


SUMMARY OF THE INVENTION

Systems and methods for providing blood glucose measurements are needed that can shorten the calibration process of a long term sensor, avoid or reduce dependence on using the finger prick method during calibration, or overcome other problems known in the art. Systems and methods are disclosed that provide calibration of a long term sensor data using sensor data from another sensor. In one embodiment, the invention includes a method for calibrating an analyte sensor, the method including receiving sensor data from a first analyte sensor, receiving sensor data from a second analyte sensor, and calibrating the sensor data from the first analyte sensor using the sensor data from the second analyte sensor.


In one aspect of the first embodiment, the first analyte sensor is a long term substantially continuous analyte sensor and the second analyte sensor is a short term substantially continuous sensor. One embodiment of this aspect further includes receiving sensor data from a set of substantially continuous analyte sensors, the set of sensors comprising one or more short term sensors, and the set of sensors being employed in a host in series such that the overall time period during which sensor data from the set of sensors is received is greater than the useful lifespan of one of the short term sensors and calibrating the sensor data from the first analyte sensor using the sensor data from the second analyte sensor and the set of sensors. In another embodiment of this aspect calibrating the long term sensor data further includes using sensor data from the short term analyte sensor to update the calibration of the long term analyte sensor.


In a second aspect of the first embodiment, the first and second analyte sensors are glucose sensors.


In a third aspect of the first embodiment, the sensor data from the first analyte sensor includes at least one sensor data point, wherein the sensor data from the second analyte sensor includes at least one data point, and wherein calibrating the sensor data further comprises forming one or more matched data pairs by matching at least one sensor data point from the first analyte sensor to at least one sensor data point from the second analyte sensor and forming a calibration set comprising at least one matched data pair.


In a fourth aspect of the first embodiment, the sensor data from the first analyte sensor includes at least six sensor data points, wherein the sensor data from the second analyte sensor includes at least six sensor data points, and wherein calibrating the sensor data further comprises forming at least six matched data pairs by matching each sensor data point from the first analyte sensor to a corresponding sensor data point from the second analyte sensor and forming a calibration set comprising at least six matched data pairs.


In a fifth aspect of the first embodiment, the sensor data from the first analyte sensor includes at least twenty sensor data points, wherein the sensor data from the second analyte sensor includes at least twenty sensor data points, and wherein calibrating the sensor data further comprises forming at least twenty matched data pairs by matching each sensor data point from the first analyte sensor to a corresponding sensor data point from the second analyte sensor and forming a calibration set comprising at least twenty matched data pairs.


In a sixth aspect of the first embodiment, the method further includes constructing a first curve from the sensor data from the first analyte sensor and constructing a second curve from the sensor data from the second analyte sensor, wherein calibrating the sensor data from the first analyte sensor comprises matching the first curve with the second curve.


In a seventh aspect of the first embodiment, the first analyte sensor is a short term substantially continuous analyte sensor and the second analyte sensor is a short term substantially continuous analyte sensor.


In a eighth aspect of the first embodiment, the first analyte sensor is a long term substantially continuous analyte sensor and the second analyte sensor is a long term substantially continuous analyte sensor.


In a ninth aspect of the first embodiment, the first analyte sensor is a short term substantially continuous analyte sensor and the second analyte sensor is a long term substantially continuous analyte sensor.


In a tenth aspect of the first embodiment, the method further includes receiving data from a non-continuous reference source, and wherein said calibrating further includes using data from the non-continuous reference source to calibrate the sensor data from the second analyte sensor.


In an eleventh aspect of the first embodiment, the non-continuous reference source is a blood glucose monitor.


In a twelfth aspect of the first embodiment, the non-continuous reference source is an in-vitro calibration.


In a thirteenth aspect of the first embodiment, the non-continuous reference source is an optical sensor.


In a fourteenth aspect of the first embodiment, calibrating the long term sensor data further includes using sensor data from the short term analyte sensor to update the calibration of the long term analyte sensor.


In a second embodiment, the invention includes a method of processing data from a substantially continuous analyte sensor, the method including testing an analyte sensor prior to insertion into a host to determine at least one sensor data characteristic, employing the analyte sensor in the host, receiving sensor data from the analyte sensor, and calibrating the sensor data using the sensor data characteristic.


In one aspect of the second embodiment, the substantially continuous analyte sensor is a short term sensor.


In a second aspect of the second embodiment, the substantially continuous analyte sensor is an implantable long term sensor.


In a third aspect of the second embodiment, the method further includes receiving reference data from a reference analyte monitor, the reference data comprising at least one reference data characteristic and calibrating the sensor data using the reference data characteristic.


In a fourth embodiment, the invention includes a system for calibrating a substantially continuous analyte sensor, the system including a first substantially continuous analyte sensor, a second substantially continuous analyte sensor, a first sensor data receiving module operably linked to said first sensor and configured to receive at least one sensor data point from said first sensor, a second sensor data receiving module operably linked to said second sensor and configured to receive at least one sensor data point from said second sensor, and a processor module in data communication with the first sensor data receiving module linked to said first sensor and further in data communication with the second sensor data receiving module linked to said second sensor, said processor module configured to calibrate the sensor data from the first sensor using sensor data from the second sensor.


In one aspect of the fourth embodiment, the processor module is further configured to match at least one time-matched data point from said first analyte sensor and said second analyte sensor to form at least one calibration set for calibrating the first analyte sensor including at least one matched data pair.


In a second aspect of the fourth embodiment, the first analyte sensor is a long term substantially continuous analyte sensor and the second analyte sensor is a short term substantially continuous analyte sensor.


In a third aspect of the fourth embodiment, the first analyte sensor is a short term substantially continuous analyte sensor and the second analyte sensor is a short term substantially continuous analyte sensor.


In a fourth aspect of the fourth embodiment, the first analyte sensor is a long term substantially continuous analyte sensor and the second analyte sensor is a long term substantially continuous analyte sensor.


In a fifth aspect of the fourth embodiment, the first analyte sensor is a short term substantially continuous analyte sensor and the second analyte sensor is a long term substantially continuous analyte sensor.


In a sixth aspect of the fourth embodiment, the first substantially continuous analyte sensor and said second substantially continuous analyte sensor are each glucose sensors.


In a fifth embodiment, the invention includes a method for simultaneously utilizing at least two analyte sensors, the method including receiving sensor data from a first analyte sensor, receiving sensor data from a second analyte sensor, and processing the sensor data from the first analyte sensor using the sensor data from the second analyte sensor.


In one aspect of the fifth embodiment, the sensor data from the second analyte sensor comprises time delay information and processing comprises modifying the sensor data from a first analyte sensor responsive to the time delay information.


In a second aspect of the fifth embodiment, processing comprises utilizing the sensor data from the second analyte sensor to assess performance of the first analyte sensor.


In a third aspect of the fifth embodiment, the first analyte sensor is a transcutaneous sensor.


In a fourth aspect of the fifth embodiment, the first analyte sensor is a wholly implantable sensor. In one embodiment of this aspect, the second analyte sensor is a transcutaneous sensor.


In a fifth aspect of the fifth embodiment, the second analyte sensor is a transcutaneous sensor.


In a sixth aspect of the fifth embodiment, the second analyte sensor is a wholly implantable sensor.


In a seventh aspect of the fifth embodiment, the processing comprises calibrating the first analyte sensor.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1A is a schematic of a system with one receiver where one sensor is used to calibrate another sensor.



FIG. 1B is a schematic of a system with more than one receiver where one sensor is used to calibrate another sensor.



FIG. 1C is a schematic of a system that uses sensor data from a short term sensor to calibrate sensor data from a long term sensor.



FIG. 1D is a schematic of a system that uses two or more short term sensors to calibrate short term sensors and/or long term sensors.



FIG. 1E is a schematic of a system that uses sensor data from a long term sensor to calibrate sensor data from another long term sensor.



FIG. 1F is a schematic of a system that uses sensor data from a short term sensor to calibrate sensor data from another short term sensor.



FIG. 2 is a perspective view of a transcutaneous analyte sensor system, including an applicator, a mounting unit, and an electronics unit.



FIG. 3 is a perspective view of a mounting unit, including the electronics unit in its functional position.



FIG. 4 is an exploded perspective view of a mounting unit, showing its individual components.



FIG. 5A is an exploded perspective view of a contact subassembly, showing its individual components.



FIG. 5B is a perspective view of an alternative contact configuration.



FIG. 5C is a perspective view of another alternative contact configuration.



FIGS. 5D to 5H are schematic cross-sectional views of a portion of the contact subassembly; namely, a variety of embodiments illustrating alternative sealing member configurations.



FIG. 6A is an expanded cutaway view of a proximal portion of a sensor.



FIG. 6B is an expanded cutaway view of a distal portion of a sensor.



FIG. 6C is a cross-sectional view through the sensor of FIG. 5B on line C-C, showing an exposed electroactive surface of a working electrode surrounded by a membrane system.



FIG. 7 is an exploded side view of an applicator, showing the components that facilitate sensor insertion and subsequent needle retraction.



FIGS. 8A to 8D are schematic side cross-sectional views that illustrate applicator components and their cooperating relationships.



FIG. 9A is a perspective view of an applicator and mounting unit in one embodiment including a safety latch mechanism.



FIG. 9B is a side view of an applicator matingly engaged to a mounting unit in one embodiment, prior to sensor insertion.



FIG. 9C is a side view of a mounting unit and applicator depicted in the embodiment of FIG. 9B, after the plunger subassembly has been pushed, extending the needle and sensor from the mounting unit.



FIG. 9D is a side view of a mounting unit and applicator depicted in the embodiment of FIG. 9B, after the guide tube subassembly has been retracted, retracting the needle back into the applicator.



FIG. 9E is a perspective view of an applicator, in an alternative embodiment, matingly engaged to the mounting unit after to sensor insertion.



FIG. 9F is a perspective view of the mounting unit and applicator, as depicted in the alternative embodiment of FIG. 9E, matingly engaged while the electronics unit is slidingly inserted into the mounting unit.



FIG. 9G is a perspective view of the electronics unit, as depicted in the alternative embodiment of FIG. 9E, matingly engaged to the mounting unit after the applicator has been released.



FIGS. 9H and 9I are comparative top views of the sensor system shown in the alternative embodiment illustrated in FIGS. 9E to 9G as compared to the embodiments illustrated in FIGS. 9B to 9D.



FIGS. 10A to 10C are side views of a sensor system adhered with an extensible adhesive pad in one embodiment. The figures illustrate the system prior to and during initial and continued release of the mounting unit from the host's skin.



FIGS. 11A and 11B are perspective and side cross-sectional views, respectively, of a sensor system showing the mounting unit immediately following sensor insertion and release of the applicator from the mounting unit.



FIGS. 12A and 12B are perspective and side cross-sectional views, respectively, of a sensor system showing the mounting unit after pivoting the contact subassembly to its functional position.



FIGS. 13A to 13C are perspective and side views, respectively, of the sensor system showing the sensor, mounting unit, and electronics unit in their functional positions.



FIG. 14 is a perspective view of a sensor system wirelessly communicating with a receiver.



FIGS. 15A and 15B are perspective views of a receiver in one preferred embodiment, wherein the receiver is provided with a docking station for receiving and holding the electronics unit (from the sensor assembly) when not in use.



FIG. 16 is an exploded perspective view of one exemplary embodiment of a continuous glucose sensor



FIG. 17 is a block diagram that illustrates electronics associated with a sensor system.



FIG. 18 is a graph that illustrates data smoothing of a raw data signal in one embodiment.



FIG. 19A illustrates a first embodiment wherein the receiver shows a numeric representation of the estimated analyte value on its user interface, which is described in more detail elsewhere herein.



FIG. 19B illustrates a second embodiment wherein the receiver shows an estimated glucose value and one hour of historical trend data on its user interface, which is described in more detail elsewhere herein.



FIG. 19C illustrates a third embodiment wherein the receiver shows an estimated glucose value and three hours of historical trend data on its user interface, which is described in more detail elsewhere herein.



FIG. 19D illustrates a fourth embodiment wherein the receiver shows an estimated glucose value and nine hours of historical trend data on its user interface, which is described in more detail elsewhere herein.



FIG. 20A is a block diagram that illustrates a configuration of a medical device including a continuous analyte sensor, a receiver, and an external device.



FIGS. 20B to 20D are illustrations of receiver liquid crystal displays showing embodiments of screen displays.



FIG. 21 is a flow chart that illustrates the initial calibration and data output of the sensor data in one embodiment.



FIG. 22A is a graph that illustrates a regression performed on a calibration set to obtain a conversion function in one exemplary embodiment.



FIG. 22B is a graph that illustrates one example of using prior information for slope and baseline.



FIG. 22C is a slope-baseline graph illustrating one example of using prior distribution information for determining a calibration slope and baseline.



FIG. 23 is a graph of two data pairs on a Clarke Error Grid to illustrate the evaluation of clinical acceptability in one exemplary embodiment.



FIG. 24 is a flow chart that illustrates the process of evaluation of calibration data for best calibration based on inclusion criteria of matched data pairs in one embodiment.



FIG. 25 is a flow chart that illustrates the process of evaluating the quality of the calibration in one embodiment.



FIG. 26A and FIG. 26B are graphs that illustrate an evaluation of the quality of calibration based on data association in one exemplary embodiment using a correlation coefficient.



FIG. 27 is a graph that illustrates an exemplary relationship between in-vitro and in-vivo sensitivity.



FIG. 28 is a graphical representation showing sensor data resulting from applying the in-vitro/in-vivo relationship of FIG. 27 to a substantially continuous analyte sensor and showing blood glucose readings over a period of time, from an exemplary application.



FIG. 29 is a graphical representation of glucose data from an analyte sensor and blood glucose readings over a time period from an exemplary application.



FIG. 30 is a graphical representation of sensor data from an un-calibrated long term sensor and a calibrated short term sensor employed on the same host.



FIG. 31 is a graphical representation of sensor data from a long term sensor, that was calibrated using the short term sensor data shown in FIG. 30, prospectively applied and compared to reference glucose measurements.



FIG. 32 is a graphical representation of sensor data from a short term sensor calibrated by sensor data from another short term sensor.



FIG. 33 is a graphical representation of a regression used to calibrate sensor data shown in FIG. 32.





DETAILED DESCRIPTION OF PREFERRED EMBODIMENT

The following description and examples illustrate a preferred embodiment of the present invention in detail. Those of skill in the art will recognize that there are numerous variations and modifications of this invention that are encompassed by its scope. Accordingly, the description of a preferred embodiment should not be deemed to limit the scope of the present invention.


Definitions

In order to facilitate an understanding of the disclosed invention, a number of terms are defined below.


The term “A/D Converter” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to hardware that converts analog signals into digital signals.


The term “analyte” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a substance or chemical constituent in a biological fluid (for example, blood, interstitial fluid, cerebral spinal fluid, lymph fluid or urine) that can be analyzed. Analytes can include naturally occurring substances, artificial substances, metabolites, and/or reaction products. In some embodiments, the analyte for measurement by the sensing regions, devices, and methods is glucose. However, other analytes are contemplated as well, including but not limited to acarboxyprothrombin; acylcarnitine; adenine phosphoribosyl transferase; adenosine deaminase; albumin; alpha-fetoprotein; amino acid profiles (arginine (Krebs cycle), histidine/urocanic acid, homocysteine, phenylalanine/tyrosine, tryptophan); andrenostenedione; antipyrine; arabinitol enantiomers; arginase; benzoylecgonine (cocaine); biotinidase; biopterin; c-reactive protein; carnitine; carnosinase; CD4; ceruloplasmin; chenodeoxycholic acid; chloroquine; cholesterol; cholinesterase; conjugated 1-β hydroxy-cholic acid; cortisol; creatine kinase; creatine kinase MM isoenzyme; cyclosporin A; d-penicillamine; de-ethylchloroquine; dehydroepiandrosterone sulfate; DNA (acetylator polymorphism, alcohol dehydrogenase, alpha 1-antitrypsin, cystic fibrosis. Duchenne/Becker muscular dystrophy, glucose-6-phosphate dehydrogenase, hemoglobin A, hemoglobin S, hemoglobin C, hemoglobin D, hemoglobin E, hemoglobin F, D-Punjab, beta-thalassemia, hepatitis B virus, HCMV, HIV-1, HTLV-1, Leber hereditary optic neuropathy, MCAD, RNA, PKU, Plasmodium vivax, sexual differentiation, 21-deoxycortisol); desbutylhalofantrine; dihydropteridine reductase; diptheria/tetanus antitoxin; erythrocyte arginase; erythrocyte protoporphyrin; esterase D; fatty acids/acylglycines; free β-human chorionic gonadotropin; free erythrocyte porphyrin; free thyroxine (FT4); free tri-iodothyronine (FT3); fumarylacetoacetase; galactose/gal-1-phosphate; galactose-1-phosphate uridyltransferase; gentamicin; glucose-6-phosphate dehydrogenase; glutathione; glutathione perioxidase; glycocholic acid; glycosylated hemoglobin; halofantrine; hemoglobin variants; hexosaminidase A; human erythrocyte carbonic anhydrase 1; 17-alpha-hydroxyprogesterone; hypoxanthine phosphoribosyl transferase; immunoreactive trypsin; lactate; lead; lipoproteins ((a), B/A-1, β); lysozyme; mefloquine; netilmicin; phenobarbitone; phenytoin; phytanic/pristanic acid; progesterone; prolactin; prolidase; purine nucleoside phosphorylase; quinine; reverse tri-iodothyronine (rT3); selenium; serum pancreatic lipase; sissomicin; somatomedin C; specific antibodies (adenovirus, anti-nuclear antibody, anti-zeta antibody, arbovirus, Aujeszky's disease virus, dengue virus, Dracunculus medinensis, Echinococcus granulosus, Entamoeba histolytica, enterovirus, Giardia duodenalisa, Helicobacter pylori, hepatitis B virus, herpes virus, HIV-1, IgE (atopic disease), influenza virus, Leishmania donovani, leptospira, measles/mumps/rubella, Mycobacterium leprae, Mycoplasma pneumoniae, Myoglobin, Onchocerca volvulus, parainfluenza virus, Plasmodium falciparum, poliovirus, Pseudomonas aeruginosa, respiratory syncytial virus, Rickettsia (scrub typhus), Schistosoma mansoni, Toxoplasma gondii, Trepenoma pallidium, Trypanosoma cruzi/rangeli, vesicular stomatis virus, Wuchereria bancrofti, yellow fever virus); specific antigens (hepatitis B virus, HIV-1); succinylacetone; sulfadoxine; theophylline; thyrotropin (TSH); thyroxine (T4); thyroxine-binding globulin; trace elements; transferrin; UDP-galactose-4-epimerase; urea; uroporphyrinogen I synthase; vitamin A; white blood cells; and zinc protoporphyrin. Salts, sugar, protein, fat, vitamins and hormones naturally occurring in blood or interstitial fluids can also constitute analytes in certain embodiments. The analyte can be naturally present in the biological fluid, for example, a metabolic product, a hormone, an antigen, an antibody, and the like. Alternatively, the analyte can be introduced into the body, for example, a contrast agent for imaging, a radioisotope, a chemical agent, a fluorocarbon-based synthetic blood, or a drug or pharmaceutical composition, including but not limited to insulin; ethanol; Cannabis (marijuana, tetrahydrocannabinol, hashish); inhalants (nitrous oxide, amyl nitrite, butyl nitrite, chlorohydrocarbons, hydrocarbons); cocaine (crack cocaine); stimulants (amphetamines, methamphetamines, Ritalin, Cylert, Preludin, Didrex, PreState, Voranil, Sandrex, Plegine); depressants (barbituates, methaqualone, tranquilizers such as Valium, Librium, Miltown, Serax, Equanil, Tranxene); hallucinogens (phencyclidine, lysergic acid, mescaline, peyote, psilocybin); narcotics (heroin, codeine, morphine, opium, meperidine, Percocet, Percodan, Tussionex, Fentanyl, Darvon, Talwin, Lomotil); designer drugs (analogs of fentanyl, meperidine, amphetamines, methamphetamines, and phencyclidine, for example, Ecstasy); anabolic steroids; and nicotine. The metabolic products of drugs and pharmaceutical compositions are also contemplated analytes, Analytes such as neurochemicals and other chemicals generated within the body can also be analyzed, such as, for example, ascorbic acid, uric acid, dopamine, noradrenaline, 3-methoxytyramine (3MT), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5-hydroxytryptamine (5HT), and 5-hydroxyindoleacetic acid (FHIAA).


The term “analyte sensor” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to any mechanism (e.g., enzymatic or non-enzymatic) by which analyte can be quantified. For example, some embodiments utilize a membrane that contains glucose oxidase that catalyzes the conversion of oxygen and glucose to hydrogen peroxide and gluconate:

Glucose+O2→Gluconate+H2O2

Because for each glucose molecule metabolized, there is a proportional change in the co-reactant O2 and the product H2O2, one can use an electrode to monitor the current change in either the co-reactant or the product to determine glucose concentration.


The term “biointerface membrane” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a permeable membrane that can be comprised of two or more domains and constructed of materials of a few microns thickness or more, which can be placed over the sensor body to keep host cells (e.g., macrophages) from gaining proximity to, and thereby damaging, the sensing membrane or forming a barrier cell layer and interfering with the transport of analyte across the tissue-device interface. The term “exit-site” as used herein is a broad term and is used in its ordinary sense, including, without limitation, the area where a medical device (for example, a sensor and/or needle) exits from the host's body.


The term “Clarke Error Grid” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to an error grid analysis, which evaluates the clinical significance of the difference between a reference glucose value and a sensor generated glucose value, taking into account (1) the value of the reference glucose measurement; (2) the value of the sensor glucose measurement; (3) the relative difference between the two values; and (4) the clinical significance of this difference. See Clarke et al., “Evaluating Clinical Accuracy of Systems for Self-Monitoring of Blood Glucose”, Diabetes Care, Volume 10. Number 5, September-October 1987.


The term “clinical acceptability” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to determination of the risk of inaccuracies to a patient. Clinical acceptability considers a deviation between time corresponding glucose measurements (e.g., data from a glucose sensor and data from a reference glucose monitor) and the risk (e.g., to the decision making of a diabetic patient) associated with that deviation based on the glucose value indicated by the sensor and/or reference data. One example of clinical acceptability can be 85% of a given set of measured analyte values within the “A” and “B” region of a standard Clarke Error Grid when the sensor measurements are compared to a standard reference measurement.


The term “concordant” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to being in agreement or harmony, and/or free from discord.


The term “congruence” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the quality or state of agreeing, coinciding, or being concordant. In one example, congruence can be determined using rank correlation.


The term “Consensus Error Grid” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to an error grid analysis that assigns a specific level of clinical risk to any possible error between two time corresponding glucose measurements. The Consensus Error Grid is divided into zones signifying the degree of risk posed by the deviation. See Parkes et al., “A New Consensus Error Grid to Evaluate the Clinical Significance of Inaccuracies in the Measurement of Blood Glucose”, Diabetes Care, Volume 23, Number 8, August 2000.


The phrase “continuous” as it relates to analyte sensing or an analyte sensor and as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to continuously, continually, and/or intermittently (regularly or irregularly) monitoring an analyte concentration, performed, for example, about every 1 second to 20 minutes.


The term “counts” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a unit of measurement of a digital signal. In one example, a raw data signal measured in counts is directly related to a voltage (converted by an A/D converter), which is directly related to current.


The terms “data association” and “data association function” as used herein are broad terms, and are to be given their ordinary and customary meaning to a person of ordinary skill in the art (and are not to be limited to a special or customized meaning), and refer without limitation to a statistical analysis of data and particularly its correlation to, or deviation from, from a particular curve. A data association function is used to show data association. For example, the data that forms that calibration set as described herein can be analyzed mathematically to determine its correlation to, or deviation from, a curve (e.g., line or set of lines) that defines the conversion function; this correlation or deviation is the data association. A data association function is used to determine data association. Examples of data association functions include, but are not limited to, linear regression, non-linear mapping/regression, rank (e.g., non-parametric) correlation, least mean square fit, mean absolute deviation (MAD), mean absolute relative difference. In one such example, the correlation coefficient of linear regression is indicative of the amount of data association of the calibration set that forms the conversion function, and thus the quality of the calibration.


The term “domain” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to regions of the biointerface membrane that can be layers, uniform or non-uniform gradients (for example, anisotropic) or provided as portions of the membrane.


The term “EEPROM” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to electrically erasable programmable read-only memory, which is user-modifiable read-only memory (ROM) that can be erased and reprogrammed (e.g., written to) repeatedly through the application of higher than normal electrical voltage.


The term “electrochemically reactive surface” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the surface of an electrode where an electrochemical reaction takes place. In one example, a working electrode measures hydrogen peroxide produced by the enzyme catalyzed reaction of the analyte being detected reacts creating an electric current (for example, detection of glucose analyte utilizing glucose oxidase produces H2O2 as a by product, H2O2 reacts with the surface of the working electrode producing two protons (2H+), two electrons (2e) and one molecule of oxygen (O2) which produces the electronic current being detected). In the case of the counter electrode, a reducible species, for example, O2 is reduced at the electrode surface in order to balance the current being generated by the working electrode.


The term “electronic connection” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to any electronic connection known to those in the art that can be utilized to interface the sensor head electrodes with the electronic circuitry of a device such as mechanical (e.g., pin and socket) or soldered.


The term “electronic connection” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to any electronic connection known to those in the art that can be utilized to interface the sensing region electrodes with the electronic circuitry of a device such as mechanical (for example, pin and socket) or soldered.


The term “ex vivo portion” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the portion of the device (for example, sensor) adapted to remain and/or exist outside the living body of a host.


The term “host” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to mammals, particularly humans.


The term “in vivo portion” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the portion of the device (for example, sensor) adapted for insertion and/or existence within the living body of a host.


The term “jitter” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to uncertainty or variability of waveform timing, which can be cause by ubiquitous noise caused by a circuit and/or environmental effects; jitter can be seen in amplitude, phase timing, or the width of the signal pulse.


The term “long term” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the lifespan of an analyte sensor. For example, the term “long term analyte sensor” is used herein relative to the term “short term analyte sensor” and designates an analyte sensor with a lifespan that is more than the lifespan of the short term analyte sensor. For example, a short term analyte sensor can have a lifespan of about less than about an hour to about three weeks, and a long term analyte sensor has a corresponding lifespan of longer than three weeks.


The term “matched data pairs” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to reference data (e.g., one or more reference analyte data points) matched with substantially time corresponding sensor data (e.g., one or more sensor data points).


The term “microprocessor” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a computer system or processor designed to perform arithmetic and logic operations using logic circuitry that responds to and processes the basic instructions that drive a computer.


The phrase “noncontinuous” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to single point analyte monitoring of an analyte concentration, for example, performed using blood glucose meters (e.g., using finger stick blood samples) and optical measuring techniques (e.g., near infrared spectroscopy, infrared spectroscopy, raman spectroscopy, photoacoustic spectroscopy, scatter and polarization changes), etc.


The terms “operable connection,” “operably connected,” and “operably linked” as used herein are broad terms, and are to be given their ordinary and customary meaning to a person of ordinary skill in the art (and are not to be limited to a special or customized meaning), and refer without limitation to one or more components being linked to another component(s) in a manner that allows transmission of signals between the components, e.g., wired or wirelessly. For example, one or more electrodes can be used to detect the amount of analyte in a sample and convert that information into a signal; the signal can then be transmitted to an electronic circuit means. In this case, the electrode is “operably linked” to the electronic circuitry.


The term “oxygen antenna domain” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a domain composed of a material that has higher oxygen solubility than aqueous media so that it concentrates oxygen from the biological fluid surrounding the biointerface membrane. The domain can then act as an oxygen reservoir during times of minimal oxygen need and has the capacity to provide on demand a higher oxygen gradient to facilitate oxygen transport across the membrane. This enhances function in the enzyme reaction domain and at the counter electrode surface when glucose conversion to hydrogen peroxide in the enzyme domain consumes oxygen from the surrounding domains. Thus, this ability of the oxygen antenna domain to apply a higher flux of oxygen to critical domains when needed improves overall sensor function.


The term “quality of calibration” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the statistical association of matched data pairs in the calibration set used to create the conversion function. For example, an R-value can be calculated for a calibration set to determine its statistical data association, wherein an R-value greater than 0.79 determines a statistically acceptable calibration quality, while an R-value less than 0.79 determines statistically unacceptable calibration quality.


The term “raw data signal” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to an analog or digital signal directly related to the measured analyte from the analyte sensor. In one example, the raw data signal is digital data in “counts” converted by an A/D converter from an analog signal (e.g., voltage or amps) representative of an analyte concentration.


The term “RF transceiver” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a radio frequency transmitter and/or receiver for transmitting and/or receiving signals.


The term “R-value” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to one conventional way of summarizing the correlation of data; that is, a statement of what residuals (e.g., root mean square deviations) are to be expected if the data are fitted to a straight line by the a regression.


The term “sensing membrane” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a permeable or semi-permeable membrane that can be comprised of two or more domains and constructed of materials of a few microns thickness or more, which are permeable to oxygen and can or can not be permeable to an analyte of interest. In one example, the sensing membrane comprises an immobilized glucose oxidase enzyme, which enables an electrochemical reaction to occur to measure a concentration of glucose.


The term “sensing region” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the region of a monitoring device responsible for the detection of a particular analyte. The sensing region generally comprises a non-conductive body, a working electrode (anode), a reference electrode (optional), and/or a counter electrode (cathode) passing through and secured within the body forming electrochemically reactive surfaces on the body and an electronic connective means at another location on the body, and a multi-domain membrane affixed to the body and covering the electrochemically reactive surface.


The term “sensor head” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the region of a monitoring device responsible for the detection of a particular analyte. In one example, a sensor head comprises a non-conductive body, a working electrode (anode), a reference electrode and a counter electrode (cathode) passing through and secured within the body forming an electrochemically reactive surface at one location on the body and an electronic connective means at another location on the body, and a sensing membrane affixed to the body and covering the electrochemically reactive surface. The counter electrode has a greater electrochemically reactive surface area than the working electrode. During general operation of the sensor a biological sample (e.g., blood or interstitial fluid) or a portion thereof contacts (directly or after passage through one or more membranes or domains) an enzyme (e.g., glucose oxidase); the reaction of the biological sample (or portion thereof) results in the formation of reaction products that allow a determination of the analyte (e.g., glucose) level in the biological sample. In some embodiments, the sensing membrane further comprises an enzyme domain (e.g., and enzyme layer), and an electrolyte phase (e.g., a free-flowing liquid phase comprising an electrolyte-containing fluid described further below).


The term “short term” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to the lifespan of an analyte sensor. For example, the term “short term analyte sensor” is used herein relative to the term “long term analyte sensor” and designates an analyte sensor with a lifespan less than the lifespan of a long term analyte sensor. For example, a short term analyte sensor can have a lifespan of less than an hour to about three weeks, and a long term analyte sensor has a corresponding lifespan of longer than three weeks.


The term “SRAM” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to static random access memory (RAM) that retains data bits in its memory as long as power is being supplied.


The term “substantially” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to being largely but not necessarily wholly that which is specified.


In the disclosure which follows, the following abbreviations apply: Eq and Eqs (equivalents); mEq (milliequivalents); M (molar); mM (millimolar) μM (micromolar); N (Normal); mol (moles); mmol (millimoles); μmol (micromoles); nmol (nanomoles); g (grams); mg (milligrams); μg (micrograms); Kg (kilograms); L (liters); mL (milliliters); dL (deciliters); μL (microliters); cm (centimeters); mm (millimeters); μm (micrometers); nm (nanometers); h and hr (hours); min. (minutes); s and sec. (seconds); ° C. (degrees Centigrade).


Overview


Some of the aspects of the invention relate to calibrating a substantially continuous analyte sensor (e.g., a subcutaneous, transdermal (e.g., transcutaneous), or intravascular device) using sensor data from another substantially continuous analyte sensor. The analyte sensor can be any type of sensor that measures a concentration of an analyte of interest or a substance indicative of the concentration or presence of the analyte. The analyte sensors can be short or long term sensors. For example, in some embodiments, the sensor data from a short term substantially continuous analyte sensor is used to calibrate the sensor data from another short term substantially continuous analyte sensor. In another embodiment, the sensor data from a short term substantially continuous analyte sensor is used to calibrate the sensor data from a long term substantially continuous analyte sensor. In one embodiment, the sensor data from a long term substantially continuous analyte sensor is used to calibrate the sensor data from another long term substantially continuous analyte sensor. In other embodiments, the sensor data from a long term substantially continuous analyte sensor is used to calibrate the sensor data from a short term substantially continuous analyte sensor. The analyte sensors can use any method of analyte-sensing, including enzymatic, chemical, physical, electrochemical, spectrophotometric, polarimetric, calorimetric, radiometric, or the like.



FIG. 1A is a schematic illustrating one embodiment of a system where data from one is used to calibrate another sensor. The system includes two substantially continuous analyte sensors, sensorA and sensorB, configured to provide sensor data to a receiver. SensorA and sensorB can be any substantially continuous analyte sensors capable of determining the level of an analyte in the body, for example glucose, oxygen, lactase, insulin, hormones, cholesterol, medicaments, viruses, or the like. SensorA and sensorB can be short term or long term sensors. SensorA and sensorB detect information relating to an analyte in the host 6 and transmit the information (e.g., sensor data) to the receiver 8. The transmission of the sensor data can be through a wire or wireless communication channel. In this embodiment, sensorA and sensorB measure the same analyte (e.g., glucose). If there is correlation and/or a predictive relationship between the sensor data from sensorA and sensorB, the sensor data from one analyte sensor can be used to calibrate the sensor data from the other analyte sensor. If sensorA and sensorB measure two different analytes but there is correlation and/or predictive behavior between the sensor data for the two different analytes, the sensor data from one analyte sensor can be used to calibrate the sensor data from the other analyte sensor. In such an embodiment, the receiver is configured to receive the sensor data from both sensors, process the data, and calibrate one of the sensors, using e.g., data processing and calibration techniques as described herein and other suitable sensor calibration techniques.



FIG. 1B is a schematic illustrating another embodiment of a system where data from one sensor is used to calibrate another sensor. This embodiment also includes two substantially continuous analyte sensors, sensorC and sensorD, that detect information relating to an analyte in the host 6 and transmit the information to a receiver. SensorA and sensorB can be short term or long term sensors. In this embodiment, sensorC transmits sensor data to receiverA and sensors transmits sensor data to receiverB. ReceiverA and receiverB are configured to communicate information with each other (e.g., analyte measurement information, corresponding timestamp of analyte measurement, etc.) so that the sensor data from one sensor can be used to calibrate the sensor data from the other. Here, for example, so long as the receivers can communicate, the communication protocol, content, and data format for one sensor and its receiver can be different than for the other sensor and its receiver. Some of the embodiments described and illustrated herein, e.g., FIGS. 1C and 1E, include one receiver that can receive data from one or more sensors. However, in such embodiments, additional receivers can be employed (e.g., one receiver for each sensor).



FIG. 1C is a schematic illustrating an embodiment of a system that calibrates a long term sensor using sensor data from a short term sensor. A long term analyte sensor can have an initial instability time period during which it is unstable for environmental, physiological, or other reasons. For example, for a long term analyte sensor implanted subcutaneously, its stabilization can be dependent upon the maturity of the tissue ingrowth around and within the sensor (see, e.g., U.S. Publication No. US-2005-0112169-A1). Accordingly, determination of sensor stability can include waiting a time period (e.g., an implantable sensor is known to require a time period for tissue, and a transdermal (e.g., transcutaneous) sensor is known to require time to equilibrate the sensor with the user's tissue); in some embodiments, this waiting period is from about one minute to about three weeks. This waiting period can be predetermined by prior testing the sensor under similar conditions, and/or by analysis of the data from the sensor to determine that the sensor is stable. In this embodiment, the short term sensor measures the analyte and provides data to a receiver during the waiting period. Once the long term sensor is deemed to be stable, the data from the long term sensor requires calibration to provide an accurate value. Where the sensor data from the short term sensor has a correlative or predictive relationship with the sensor data from the long term sensor, the data from the short term sensor can be used to calibrate the long term sensor. Calibration of the sensor data from a long term sensor using sensor data provided by the short term sensor facilitates the use of the long term sensor data sooner and/or reduces or obviates the need to calibrate the long term sensor with single point calibration techniques, e.g., using finger stick blood samples, optical measuring techniques etc.


The sensor data from a long term sensor can change over time, due to, for example, a decrease in its sensitivity. In one embodiment, a long term sensor can be re-calibrated by employing a short term sensor on the same host as the long term sensor and then using the sensor data from the short term sensor to calibrate the sensor data from the long term sensor. For example, on a host having a long term (e.g., wholly implantable) sensor, a substantially continuous short term (e.g., transcutaneous) analyte sensor can also be employed. A short term sensor taking a measurement every five minutes provides sensor data for 288 measurements in a day. The receiver translates the short sensor data to estimate analyte values, which are used to re-calibrate the long term sensor using e.g., data processing techniques described herein, including data processing techniques described in reference to FIGS. 16 and 17. As another example, a short term sensor can be used to trouble shoot a long term sensor, for example, when the long term sensor is wholly implanted in the host and experiences malfunctioning. In such a situation, a short term sensor can be inserted into the host (e.g., a transcutaneous sensor) and the data compared to that of the long term sensor (e.g., wholly implantable sensor) to diagnose potential problems with the long term sensor, for example, signal noise due to oxygen deficiencies or enzyme deficiency. In alternative embodiments, short and/or long term sensors can be used to diagnose problems in other short and/or long term sensors.



FIG. 1D is a schematic illustrating an embodiment of a system that calibrates a long term sensor using sensor data from one or more short term sensors. In certain circumstances a single short term sensor is not able to provide sensor data for the entire waiting period of the long term sensor. For example, the lifespan of the short term sensor may be less than the requisite waiting period. Accordingly, the use of two or more short term sensors can be used to provide sensor data for the entire waiting period for a long term sensor if the waiting period is greater than three days.


In FIG. 1D, two or more short term sensors are used to provide analyte measurements during the waiting period of a long term sensor. For example, a short term sensor A is used to provide analyte measurements to a receiver for its usable lifespan. Prior to the end of the lifespan of sensor A, short term sensor B is employed to also provide analyte measurements to a receiver for the host 6, so that sensor A and sensor B are both providing sensor data during an overlapping time period. If the waiting period of the long term sensor is longer than the period that can be covered by sensor A and B, another short-term sensor can be employed prior to the end of the lifespan of sensor B. Substitution of short term sensors in an overlapping manner can be repeated until the expiration of the waiting period. Once the long term sensor is stable, it can be calibrated using sensor data from one or more of the short term sensors. Alternatively, one or more short-term sensor may be implanted near the time when the long term sensor is expected to start working rather than having the short term sensors implanted during the entire waiting period of the long term sensor.


In one embodiment, where two or more short term sensors are used on the same host, the sensor data from one short term sensor can be used to calibrate the other short term sensor. For example, in the above-described embodiment, the receiver can use the sensor data from sensor A to calibrate the sensor data from B, which can be used to calibrate each successive short term sensor employed on the host 6.


In some embodiments, one or more of the short term sensors are calibrated in-vitro, e.g., by a benchtop calibration process that predetermines the information particular to the sensor. In such embodiments, the series of short term sensors need not overlap each other for calibration purposes. In one example, a benchtop calibrated short term sensor can be used to calibrate a long term implantable glucose sensor so that manual glucose measurements (SMBG) are not needed. According to one embodiment of a sensor, the sensing mechanism of an enzyme-electrode based glucose sensor depends on two phenomena that are linear with glucose concentration: (1) diffusion of glucose through a membrane system situated between interstitial fluid and the electrode surface, and (2) an enzymatic reaction within the membrane system. Because of this linearity, calibration/recalibration of the sensor consists of solving the line

y=mx+b

where y denotes the sensor signal (in units of A/D counts), x the estimated glucose concentration (mg/dl), in the sensor sensitivity to glucose (counts/mg/dl), and b the baseline signal (counts).


Typically, calibration requires at least two independent, paired measurements (x1, y1; x2, y2) to solve for m and b and thus allow glucose estimation when only the sensor signal, y is available. However, if prior information is available for m and/or b, then calibration can occur with fewer paired measurements. In one embodiment of a semi-benchtop calibration technique, prior information (e.g., benchtop tests) determine the sensitivity of the sensor and/or the baseline signal of the sensor by analyzing sensor data from measurements taken by the sensor of a controlled solution (e.g., prior to inserting the sensor). If there exists a predictive relationship between benchtop sensor parameters and in-vivo parameters, then this information can be used by the calibration procedure. For example, if a predictive relationship exists between benchtop sensitivity and in-vivo sensitivity, m≈f(mbenchtop), then the predicted in can be used, along with a single matched pair, to solve for b (b=y−mx, semi-benchtop calibration). If in addition, b can be assumed to be 0, for example with a biointerface electrode configuration, then both m and b are known a priori, matched pairs are not needed for calibration, and the sensor can be completely benchtop calibrated.


Other methods for using information obtained prior to sensor insertion in sensor calibration are discussed in more detail elsewhere herein.


In some embodiments, the long term sensor can be benchtop calibrated and then once implanted, the calibration of the data from the long term sensor can be adjusted using additional reference data, for example, reference data from a short term sensor. Typically for a long term sensor, as its biointerface matures, its m and b change. This change (a 10% change in signal amplitude, for example) over a period of time (two weeks) can be solved for with periodic use of a short term sensor as follows: a user implanted with a long term sensor inserts a short term sensor, the short term sensor glucose values (if collected at 5 min intervals, there are 288 per day) are used as the reference values, x, to which the long term sensor values, y, can be calibrated. This procedure would allow for accurate estimates of m, b, and time-lag (assuming the time-lag of the short term sensor signal relative to blood glucose). Accordingly, reference data from a short term glucose sensor can be used in the initial calibration process described herein and shown in FIG. 21, and the update calibration process described herein and shown in FIG. 24.


In the embodiment illustrated in FIG. 1E, the sensor data for one long term sensor is used to calibrate the sensor data from another long term sensor. Long term sensor A can be employed on the host 6 and calibrated using, e.g., data from a short term sensor, a long term sensor, or another calibration technique. Prior to the end of the lifespan of long term sensor A, long term sensor B can be implanted into the host 6. Once long term sensor B is stable, sensor data from long term sensor A can be used to calibrate the sensor data from long tem sensor B. This calibration process can be repeated for additional long term sensors employed on host 6, so that a series of long term sensors can be employed, with the sensor data from each newly employed sensor being calibrated using sensor data from the previously employed long term sensor. By this means, a patient can have continuity of data while only undergoing one procedure for each long term implant, for example, once per year. In one example, Sensor A is implanted at time 0. After 11 months. Sensor B is implanted, and Sensor A is left in place. During the next month. Sensor B starts up and is calibrated using data from sensor A. At time 23 months, Sensor C is implanted and Sensor A is removed. Sensor B is used to calibrate Sensor C, and so forth for as long as the patient wishes to continue placing new sensors. Other time frames of sensor implantation and overlap are also possible.



FIG. 1F is a schematic illustrating an embodiment of a system that calibrates a short term sensor using sensor data from a short term sensor. It is known that some transdermal (e.g., transcutaneous) sensors require time to equilibrate the sensor with the user's tissue (e.g., due to electrochemical break-in). For example, when a first short term sensor's lifespan is nearing its end, a second short term sensor can be implanted into the user's tissue (e.g., at another location) to allow that sensor to equilibrate while the first short term sensor is still providing data. In addition to providing data during the equilibration time of the second short term sensor (thereby allowing data continuity), the first short term sensor can provide additional data, including calibration information, time lag information, drift information, and the like, to the second short term sensor to increase its intelligence and enhance its performance.


The sensors of the preferred embodiments can be employed sequentially and/or simultaneously (e.g., redundant sensors). For example, one or more short or long term sensors can be used simultaneously in order to compare, trouble-shoot, and/or provide increased data to the host. In one situation, by providing at least two redundant sensors, transient problems experienced by one sensor can be negated by the use of the other sensor.


An analyte sensor uses any known method, including invasive, minimally invasive, and non-invasive sensing techniques, to provide an output signal indicative of the concentration of the analyte of interest. The output signal is typically a raw signal that is used to provide a value that can be used for calibrating another analyte sensor or an analyte sensor used in another application. Appropriate smoothing, calibration, and evaluation methods can be applied to the raw signal and/or system as a whole to provide relevant and acceptable analyte data for calibrating another analyte sensor or the same analyte sensor used in another application.


The analyte sensor(s) useful with the preferred embodiments can be any device capable of measuring the concentration of an analyte of interest. One exemplary embodiment is described below, which calibrates a long term implantable glucose sensor based on data from a short term implantable glucose sensor. However, it can be understood that the devices and methods described herein can be applied to any device capable of detecting a concentration of analyte of and providing an output signal that represents the concentration of the analyte for use in calibrating another sensor.


Short Term Sensor


In one embodiment, the short term sensors for use as described herein include a transcutaneous analyte sensor system that includes an applicator for inserting the transcutaneous (transdermal) analyte sensor under a host's skin. The sensor system includes a sensor for sensing the analyte, wherein the sensor is associated with a mounting unit adapted for mounting on the skin of the host. The mounting unit houses the electronics unit associated with the sensor and is adapted for fastening to the host's skin. In certain embodiments, the system further includes a receiver for receiving and/or processing sensor data.



FIG. 2 is a perspective view of a transcutaneous analyte sensor system 10. In the preferred embodiment of a system as depicted in FIG. 2, the sensor includes an applicator 12, a mounting unit 14, and an electronics unit 16. The system can further include a receiver 158, such as is described in more detail with reference to FIG. 14.


The mounting unit (housing) 14 includes a base 24 adapted for mounting on the skin of a host, a sensor adapted for transdermal (e.g., transcutaneous) insertion through the skin of a host (see FIG. 5A), and one or more contacts 28 configured to provide secure electrical contact between the sensor and the electronics unit 16. The mounting unit 14 is designed to maintain the integrity of the sensor in the host so as to reduce or eliminate translation of motion between the mounting unit, the host, and/or the sensor.


In one embodiment, an applicator 12 is provided for inserting the sensor 32 through the host's skin at the appropriate insertion angle with the aid of a needle (see FIGS. 7 through 9), and for subsequent removal of the needle using a continuous push-pull action. Preferably, the applicator comprises an applicator body 18 that guides the applicator components (see FIGS. 7 through 9) and includes an applicator body base 60 configured to mate with the mounting unit 14 during insertion of the sensor into the host. The mate between the applicator body base 60 and the mounting unit 14 can use any known mating configuration, for example, a snap-fit, a press-fit, an interference-fit, or the like, to discourage separation during use. One or more release latches 30 enable release of the applicator body base 60, for example, when the applicator body base 60 is snap fit into the mounting unit 14.


The electronics unit 16 includes hardware, firmware, and/or software that enable measurement of levels of the analyte via the sensor. For example, the electronics unit 16 can comprise a potentiostat, a power source for providing power to the sensor, other components useful for signal processing, and preferably an RF module for transmitting data from the electronics unit 16 to a receiver. Electronics can be affixed to a printed circuit board (PCB), or the like, and can take a variety of forms. For example, the electronics can take the form of an integrated circuit (IC), such as an Application-Specific Integrated Circuit (ASIC), a microcontroller, or a processor. Preferably, electronics unit 16 houses the sensor electronics, which comprise systems and methods for processing sensor analyte data. Examples of systems and methods for processing sensor analyte data are described in more detail in U.S. Publication No. US-2005-0027463-A1.


After insertion of the sensor using the applicator 12, and subsequent release of the applicator 12 from the mounting unit 14 (see FIGS. 9B to 9D), the electronics unit 16 is configured to releasably mate with the mounting unit 14 in a manner similar to that described above with reference to the applicator body base 60. The electronics unit 16 includes contacts on its backside (not shown) configured to electrically connect with the contacts 28, such as are described in more detail with reference to FIGS. 3 through 5. In one embodiment, the electronics unit 16 is configured with programming, for example initialization, calibration reset, failure testing, or the like, each time it is initially inserted into the mounting unit 14 and/or each time it initially communicates with the sensor 32.


Mounting Unit



FIG. 3 is a perspective view of a sensor system of a preferred embodiment, shown in its functional position, including a mounting unit and an electronics unit matingly engaged therein. FIGS. 13A to 13C illustrate the sensor is its functional position for measurement of an analyte concentration in a host.


In preferred embodiments, the mounting unit 14, also referred to as a housing, comprises a base 24 adapted for fastening to a host's skin. The base can be formed from a variety of hard or soft materials, and preferably comprises a low profile for minimizing protrusion of the device from the host during use. In some embodiments, the base 24 is formed at least partially from a flexible material, which is believed to provide numerous advantages over conventional transcutaneous sensors, which, unfortunately, can suffer from motion-related artifacts associated with the host's movement when the host is using the device. For example, when a transcutaneous analyte sensor is inserted into the host, various movements of the sensor (for example, relative movement between the in vivo portion and the ex vivo portion, movement of the skin, and/or movement within the host (dermis or subcutaneous)) create stresses on the device and can produce noise in the sensor signal. It is believed that even small movements of the skin can translate to discomfort and/or motion-related artifact, which can be reduced or obviated by a flexible or articulated base. Thus, by providing flexibility and/or articulation of the device against the host's skin, better conformity of the sensor system 10 to the regular use and movements of the host can be achieved. Flexibility or articulation is believed to increase adhesion (with the use of an adhesive pad) of the mounting unit 14 onto the skin, thereby decreasing motion-related artifact that can otherwise translate from the host's movements and reduced sensor performance.



FIG. 4 is an exploded perspective view of a sensor system of a preferred embodiment, showing a mounting unit, an associated contact subassembly, and an electronics unit. In some embodiments, the contacts 28 are mounted on or in a subassembly hereinafter referred to as a contact subassembly 26 (see FIG. 5A), which includes a contact holder 34 configured to fit within the base 24 of the mounting unit 14 and a hinge 38 that allows the contact subassembly 26 to pivot between a first position (for insertion) and a second position (for use) relative to the mounting unit 14, which is described in more detail with reference to FIGS. 11 and 12. The term “hinge” as used herein is a broad term and is used in its ordinary sense, including, without limitation, to refer to any of a variety of pivoting, articulating, and/or hinging mechanisms, such as an adhesive hinge, a sliding joint, and the like; the term hinge does not necessarily imply a fulcrum or fixed point about which the articulation occurs.


In certain embodiments, the mounting unit 14 is provided with an adhesive pad 8, preferably disposed on the mounting unit's back surface and preferably including a releasable backing layer 9. Thus, removing the backing layer 9 and pressing the base portion 24 of the mounting unit onto the host's skin adheres the mounting unit 14 to the host's skin. Additionally or alternatively, an adhesive pad can be placed over some or all of the sensor system after sensor insertion is complete to ensure adhesion, and optionally to ensure an airtight seal or watertight seal around the wound exit-site (or sensor insertion site) (not shown). Appropriate adhesive pads can be chosen and designed to stretch, elongate, conform to, and/or aerate the region (e.g., host's skin).


In preferred embodiments, the adhesive pad 8 is formed from spun-laced, open- or closed-cell foam, and/or non-woven fibers, and includes an adhesive disposed thereon, however a variety of adhesive pads appropriate for adhesion to the host's skin can be used, as is appreciated by one skilled in the art of medical adhesive pads. In some embodiments, a double-sided adhesive pad is used to adhere the mounting unit to the host's skin. In other embodiments, the adhesive pad includes a foam layer, for example, a layer wherein the foam is disposed between the adhesive pad's side edges and acts as a shock absorber.


In some embodiments, the surface area of the adhesive pad 8 is greater than the surface area of the mounting unit's back surface. Alternatively, the adhesive pad can be sized with substantially the same surface area as the back surface of the base portion. Preferably, the adhesive pad has a surface area on the side to be mounted on the host's skin that is greater than about 1, 1.25, 1.5, 1.75, 2, 2.25, or 2.5 times the surface area of the back surface 25 of the mounting unit base 24. Such a greater surface area can increase adhesion between the mounting unit and the host's skin, minimize movement between the mounting unit and the host's skin, and/or protect the wound exit-site (sensor insertion site) from environmental and/or biological contamination. In some alternative embodiments, however, the adhesive pad can be smaller in surface area than the back surface assuming a sufficient adhesion can be accomplished.


In some embodiments, the adhesive pad 8 is substantially the same shape as the back surface 25 of the base 24, although other shapes can also be advantageously employed, for example, butterfly-shaped, round, square, or rectangular. The adhesive pad backing can be designed for two-step release, for example, a primary release wherein only a portion of the adhesive pad is initially exposed to allow adjustable positioning of the device, and a secondary release wherein the remaining adhesive pad is later exposed to firmly and securely adhere the device to the host's skin once appropriately positioned. The adhesive pad is preferably waterproof. Preferably, a stretch-release adhesive pad is provided on the back surface of the base portion to enable easy release from the host's skin at the end of the useable life of the sensor, as is described in more detail with reference to FIGS. 10A to 10C.


In some circumstances, it has been found that a conventional bond between the adhesive pad and the mounting unit may not be sufficient, for example, due to humidity that can cause release of the adhesive pad from the mounting unit. Accordingly, in some embodiments, the adhesive pad can be bonded using a bonding agent activated by or accelerated by an ultraviolet, acoustic, radio frequency, or humidity cure. In some embodiments, a eutectic bond of first and second composite materials can form a strong adhesion. In some embodiments, the surface of the mounting unit can be pretreated utilizing ozone, plasma, chemicals, or the like, in order to enhance the bondability of the surface.


A bioactive agent is preferably applied locally at the insertion site (exit-site) prior to or during sensor insertion. Suitable bioactive agents include those which are known to discourage or prevent bacterial growth and infection, for example, anti-inflammatory agents, antimicrobials, antibiotics, or the like. It is believed that the diffusion or presence of a bioactive agent can aid in prevention or elimination of bacteria adjacent to the exit-site. Additionally or alternatively, the bioactive agent can be integral with or coated on the adhesive pad, or no bioactive agent at all is employed.



FIG. 5A is an exploded perspective view of the contact subassembly 26 in one embodiment, showing its individual components. Preferably, a watertight (waterproof or water-resistant) sealing member 36, also referred to as a sealing material or seal, fits within a contact holder 34 and provides a watertight seal configured to surround the electrical connection at the electrode terminals within the mounting unit in order to protect the electrodes (and the respective operable connection with the contacts of the electronics unit 16) from damage due to moisture, humidity, dirt, and other external environmental factors. In one embodiment, the sealing member 36 is formed from an elastomeric material, such as silicone; however, a variety of other elastomeric or sealing materials can also be used, for example, silicone-polyurethane hybrids, polyurethanes, and polysulfides. Preferably, the sealing member is configured to compress within the contact subassembly when the electronics unit is mated to the mounting unit. In some embodiments, the sealing member 36 comprises a self-lubricating material, for example, self-lubricating silicone or other materials impregnated with or otherwise comprising a lubricant configured to be released during use. In some embodiments, the sealing member 36 includes a self-sealing material, for example, one that leaches out a sealant such as a silicone oil. In some embodiments, bumps, ridges, or other raised portions (not shown), can be added to a component of the sensor system, such as to the contact subassembly 26 (e.g., housing adjacent to the sealing member), electronics unit 16 and/or sealing member 36 to provide additional compression and improve the seal formed around the contacts 28 and/or sensor 32 when the contacts 28 are mated to the sensor electronics.


Preferably, the sealing member is selected using a durometer. A durometer is an instrument used for measuring the indentation hardness of rubber, plastics, and other materials. Durometers are built to various standards from ASTM. DIN. JIS, and ISO. The hardness of plastics is most commonly measured by the Shore (Durometer) test or Rockwell hardness test. Both methods measure the resistance of plastics toward indentation and provide an empirical hardness value. Shore Hardness, using either the Shore A or Shore D scale, is the preferred method for rubbers/elastomers and is also commonly used for softer plastics such as polyolefins, fluoropolymers, and vinyls. The Shore A scale is used for softer rubbers while the Shore D scale is used for harder ones. In preferred embodiments, the Shore A scale is employed in connection with selection of a sealing member.


The Shore hardness is measured with a Durometer and sometimes referred to as “Durometer hardness.” The hardness value is determined by the penetration of the Durometer indenter foot into the sample. Because of the resilience of rubbers and plastics, the indentation reading may change over time, so the indentation time is sometimes reported along with the hardness number. The ASTM test method designation for the Shore Durometer hardness test is ASTM D2240. The results obtained from this test are a useful measure of relative resistance to indentation of various grades of polymers.


Using a durometer in the selection of a sealing member enables selection of a material with optimal durometer hardness that balances the advantages of a lower durometer hardness with the advantages of a higher durometer hardness. For example, when a guide tube (e.g., cannula) is utilized to maintain an opening in a silicone sealing member prior to sensor insertion, a compression set (e.g., some retention of a compressed shape caused by compression of the material over time) within the silicone can result due to compression over time of the sealing member by the guide tube. Compression set can also result from certain sterilization procedures (e.g., radiation sterilization such as electron beam or gamma radiation). Unfortunately, in some circumstances, the compression set of the sealing member may cause gaps or incompleteness of contact between the sealing member and the contacts and/or sensor. In general, a lower durometer hardness provides a better conformation (e.g., seal) surrounding the contacts and/or sensor as compared to a higher durometer hardness. Additionally, a lower durometer hardness enables a design wherein less force is required to create the seal (e.g., to snap the electronics unit into the mounting unit, for example, as in the embodiment illustrated in FIG. 5A) as compared to a higher durometer hardness, thereby increasing the ease of use of the device. However, the benefits of a lower durometer hardness silicone material must be balanced with potential disadvantages in manufacturing. For example, lower durometer hardness silicones are often produced by compounding with a silicone oil. In some circumstances, it is believed that some silicone oil may leach or migrate during manufacture and/or sterilization, which may corrupt aspects of the manufacturing process (e.g., adhesion of glues and/or effectiveness of coating processes). Additionally, a higher durometer hardness material generally provides greater stability of the material, which may reduce or avoid damage to the sealing member cause by pressure or other forces.


It is generally preferred that a sealing member 36 with a durometer hardness of from about 5 to about 80 Shore A is employed, more preferably a durometer hardness of from about 10 to about 50 Shore A, and even more preferably from about 20 to about 50 Shore A. In one embodiment, of a transcutaneous analyte sensor, the sealing member is fabricated using a silicone of about 20 Shore A to maximize the conformance of the seal around the contacts and/or sensor while minimizing the force required to compress the silicone for that conformance. In another embodiment, the sealing member is formed from a silicone of about 50 Shore A so as to provide increased strength of the sealing member (e.g., its resistance to compression). While a few representative examples have been provided above, one skilled in the art appreciates that higher or lower durometer hardness sealing material may also be suitable for use.


In one alternative embodiment, a sealing member 36 with a durometer hardness of about 10 Shore A is used. In this embodiment, the sealing material tends to “weep” out, further increasing conformance of the seal against the adjacent parts. In another alternative embodiment, a sealing material with a durometer hardness of about 0 (zero) Shore A is used as a sealant and/or in combination with a sealant, also referred to as a lubricant, which in some embodiments is a hydrophobic fluid filling material such as a grease, silicone, petroleum jelly, or the like. Preferably, the sensor and/or contacts are encased in a housing that contains the sealant, causing the material to “squeeze” around contacts and/or sensor. Any suitable hydrophobic fluid filling material can be employed. Especially preferred are synthetic or petroleum hydrocarbon-based materials, silicone-based materials, ester-based greases, and other pharmaceutical-grade materials.


In some embodiments, the sealing member can comprise a material that has been modified to enhance the desirable properties of the sealing member 36. For example, one or more filler materials or stiffening agents such as glass beads, polymer beads, composite beads, beads comprising various inert materials, carbon black, talc, titanium oxide, silicone dioxide, and the like. In some embodiments, the filler material is incorporated into the sealing member material to mechanically stiffen the sealing member. In general, however, use of a filler material or stiffening agent in the sealing member material can provide a variety of enhanced properties including increased modulus of elasticity, crosslink density, hardness, and stiffness, and decreased creep, for example. In some alternative embodiments, gases are chemically (or otherwise) injected into the sealing member material. For example, the sealing material can comprise a polymeric foam (e.g., a polyurethane foam, a latex foam, a styrene-butadiene foam, and the like), or a dispersion of gas bubbles in a grease or jelly.


In alternative embodiments, the seal 36 is designed to form an interference fit with the electronics unit and can be formed from a variety of materials, for example, flexible plastics, or noble metals. One of ordinary skill in the art appreciates that a variety of designs can be employed to provide a seal surrounding electrical contacts such as described herein. For example, the contact holder 34 can be integrally designed as a part of the mounting unit, rather than as a separate piece thereof. Additionally or alternatively, a sealant can be provided in or around the sensor (e.g., within or on the contact subassembly or sealing member), such as is described in more detail with reference to FIGS. 12A and 12B. In general, sealing materials with durometer hardnesses in the described ranges can provide improved sealing in a variety of sensor applications. For example, a sealing member as described in the preferred embodiments (e.g., selected using a durometer to ensure optimal durometer hardness, and the like) can be implemented adjacent to and/or to at least partially surrounding the sensor in a variety of sensor designs, including, for example, the sensor designs of the preferred embodiments, as well as a planar substrate such as described in U.S. Pat. No. 6,175,752.


In the illustrated embodiment of FIG. 5A, the sealing member 36 is formed with a raised portion 37 surrounding the contacts 28. The raised portion 37 enhances the interference fit surrounding the contacts 28 when the electronics unit 16 is mated to the mounting unit 14. Namely, the raised portion surrounds each contact and presses against the electronics unit 16 to form a tight seal around the electronics unit. However, a variety of alternative sealing member configurations are described with reference to FIGS. 5D to 5H, below.


Contacts 28 fit within the seal 36 and provide for electrical connection between the sensor 32 and the electronics unit 16. In general, the contacts are designed to ensure a stable mechanical and electrical connection of the electrodes that form the sensor 32 (see FIG. 6A to 6C) to mutually engaging contacts 28 thereon. A stable connection can be provided using a variety of known methods, for example, domed metallic contacts, cantilevered fingers, pogo pins, or the like, as is appreciated by one skilled in the art.


In preferred embodiments, the contacts 28 are formed from a conductive elastomeric material, such as a carbon black elastomer, through which the sensor 32 extends (see FIGS. 11B and 12B). Conductive elastomers are advantageously employed because their resilient properties create a natural compression against mutually engaging contacts, forming a secure press fit therewith. In some embodiments, conductive elastomers can be molded in such a way that pressing the elastomer against the adjacent contact performs a wiping action on the surface of the contact, thereby creating a cleaning action during initial connection. Additionally, in preferred embodiments, the sensor 32 extends through the contacts 28 wherein the sensor is electrically and mechanically secure by the relaxation of elastomer around the sensor (see FIGS. 8A to 8D).


In an alternative embodiment, a conductive, stiff plastic forms the contacts, which are shaped to comply upon application of pressure (for example, a leaf-spring shape). Contacts of such a configuration can be used instead of a metallic spring, for example, and advantageously avoid the need for crimping or soldering through compliant materials; additionally, a wiping action can be incorporated into the design to remove contaminants from the surfaces during connection. Non-metallic contacts can be advantageous because of their seamless manufacturability, robustness to thermal compression, non-corrosive surfaces, and native resistance to electrostatic discharge (ESD) damage due to their higher-than-metal resistance.



FIGS. 5B and 5C are perspective views of alternative contact configurations. FIG. 5B is an illustration of a narrow contact configuration. FIG. 5C is an illustration of a wide contact configuration. One skilled in the art appreciates that a variety of configurations are suitable for the contacts of the preferred embodiments, whether elastomeric, stiff plastic or other materials are used. In some circumstances, it can be advantageous to provide multiple contact configurations (such as illustrated in FIGS. 5A to 5C) to differentiate sensors from each other. In other words, the architecture of the contacts can include one or more configurations each designed (keyed) to fit with a particular electronics unit.



FIGS. 5D to 5H are schematic cross-sectional views of a portion of the contact subassembly; namely, a variety of alternative embodiments of the sealing member 36 are illustrated. In each of these embodiments (e.g., FIGS. 5D to 5H), a sensor 32 is shown, which is configured for operable connection to sensor electronics for measuring an analyte in a host such as described in more detail elsewhere herein. Additionally, two electrical contacts 28, as described in more detail elsewhere herein, are configured to operably connect the sensor to the sensor electronics. Thus, the sealing member 36 in each of these alternative configurations (e.g., FIGS. 5D to 5H) at least partially surrounds the sensor and/or the electrical contacts to seal the electrical contacts from moisture when the sensor is operably connected to the sensor electronics.



FIG. 5D is a schematic cross-sectional view of the sealing member 36 in an embodiment similar to FIG. 5A, including gaps 400 that are maintained when the one or more electrical contacts are operably connected to the sensor electronics. Preferably, these air gaps provide for some flexibility of the sealing member 36 to deform or compress to seal the electrical contacts 28 from moisture or other environmental effects.


In certain circumstances, such as during sensor insertion or needle/guide tube retraction (see FIGS. 8A to 8D), a sealing member with a certain elasticity can be compressed or deformed by the insertion and/or retraction forces applied thereto. Accordingly in some embodiments, the sealing member is configured to be maintained (e.g., held substantially in place) on the housing (e.g., contact subassembly 26 or base 34) without substantial translation, deformation, and/or compression (e.g., during sensor insertion). FIG. 5D illustrates one such implementation, wherein one or more depressions 402 are configured to receive mating protrusions (e.g., on the base 34 of the contact subassembly 26, not shown). A variety of male-female or other such mechanical structures can be implemented to hold the sealing member in place, as is appreciated by one skilled in the art. In one alternative embodiment, an adhesive (not shown) is configured to adhere the sealing member 36 to the housing (e.g., base 34 of the contact subassembly 26) to provide substantially the same benefit of holding the sealing member during sensor insertion/retraction without substantial deformation, as described in more detail, above. In another embodiment, the base 34 of the contact subassembly 26 (or equivalent structure) comprises reinforcing mechanical supports configured to hold the sealing member as described above. One skilled in the art appreciates a variety of mechanical and/or chemical methods that can be implemented to maintain a sealing member substantially stationary (e.g., without substantial translation, deformation and/or compression) when compression and/or deformation forces are applied thereto. Although one exemplary embodiment is illustrated with reference to FIG. 5D, a wide variety of systems and methods for holding the sealing member can be implemented with a sealing member of any particular design.



FIG. 5E is a schematic cross-sectional view of the sealing member 36 in an alternative embodiment without gaps. In certain circumstances, full contact between mating members may be preferred.


In certain circumstances moisture may “wick” along the length of the sensor (e.g., from an exposed end) through the sealing member 36 to the contacts 28. FIG. 5F is a schematic cross-sectional view of a sealing member 36 in an alternative embodiment wherein one or more gaps 400 are provided. In this embodiment, the gaps 400 extend into the sealing member and encompass at least a portion of the sensor 32. The gaps 400 or “deep wells” of FIG. 5F are designed to interrupt the path that moisture may take, avoiding contact of the moisture at the contacts 28. If moisture is able to travel along the path of the sensor, the abrupt change of surface tension at the opening 404 of the gap 400 in the sealing member 36 substantially deters the moisture from traveling to the contacts 28.



FIG. 5G is a schematic cross-sectional view of the sealing member 36 in another alternative embodiment wherein one or more gaps 400 are provided. In this embodiment, the gaps extend from the bottom side of the sealing member 36, which can be helpful in maintaining a stable position of the contacts 28 and/or reduces “pumping” of air gaps in some situations.


In some embodiments, gaps 400 can be filled by a sealant, which also may be referred to as a lubricant, for example, oil, grease, or gel. In one exemplary embodiment, the sealant includes petroleum jelly and is used to provide a moisture barrier surrounding the sensor. Referring to FIG. 5F, filling the gaps 400 with a sealant provides an additional moisture barrier to reduce or avoid moisture from traveling to the contacts 28. Sealant can be used to fill gaps or crevices in any sealing member configuration.


In some sealing member configurations, it can be advantageous to provide a channel 406 through the sealing member 36 in order to create an additional pathway for sealant (e.g. lubricant) in order to expel air and/or to provide a path for excess sealant to escape. In some embodiments, more than one channel is provided.



FIG. 5H is a schematic cross-sectional view of a sealing member 36 in an alternative embodiment wherein a large gap 400 is provided between the sealing member upper portion 408 and the sealing member lower portion 410. These portions 408, 410 may or may not be connected; however, they are configured to sandwich the sensor and sealant (e.g., grease) therebetween. The sealing member 36 illustrated with reference to FIG. 5H can provide ease of manufacture and/or product assembly with a comprehensive sealing ability. Additional gaps (with or without sealant) can be provided in a variety of locations throughout the sealing member 36; these additional gaps, for example, provide space for excess sealant.


Sensor


Preferably, the sensor 32 includes a distal portion 42, also referred to as the in vivo portion, adapted to extend out of the mounting unit for insertion under the host's skin, and a proximal portion 40, also referred to as an ex vivo portion, adapted to remain above the host's skin after sensor insertion and to operably connect to the electronics unit 16 via contacts 28. Preferably, the sensor 32 includes two or more electrodes: a working electrode 44 and at least one additional electrode, which can function as a counter electrode and/or reference electrode, hereinafter referred to as the reference electrode 46. A membrane system is preferably deposited over the electrodes, such as described in more detail with reference to FIGS. 6A to 6C, below.



FIG. 6A is an expanded cutaway view of a proximal portion 40 of the sensor in one embodiment, showing working and reference electrodes. In the illustrated embodiments, the working and reference electrodes 44, 46 extend through the contacts 28 to form electrical connection therewith (see FIGS. 11B and 12B). Namely, the working electrode 44 is in electrical contact with one of the contacts 28 and the reference electrode 46 is in electrical contact with the other contact 28, which in turn provides for electrical connection with the electronics unit 16 when it is mated with the mounting unit 14. Mutually engaging electrical contacts permit operable connection of the sensor 32 to the electronics unit 16 when connected to the mounting unit 14; however other methods of electrically connecting the electronics unit 16 to the sensor 32 are also possible. In some alternative embodiments, for example, the reference electrode can be configured to extend from the sensor and connect to a contact at another location on the mounting unit (e.g., non-coaxially). Detachable connection between the mounting unit 14 and electronics unit 16 provides improved manufacturability, namely, the relatively inexpensive mounting unit 14 can be disposed of when replacing the sensor system after its usable life, while the relatively more expensive electronics unit 16 can be reused with multiple sensor systems.


In alternative embodiments, the contacts 28 are formed into a variety of alternative shapes and/or sizes. For example, the contacts 28 can be discs, spheres, cuboids, and the like. Furthermore, the contacts 28 can be designed to extend from the mounting unit in a manner that causes an interference fit within a mating cavity or groove of the electronics unit, forming a stable mechanical and electrical connection therewith.



FIG. 6B is an expanded cutaway view of a distal portion of the sensor in one embodiment, showing working and reference electrodes. In preferred embodiments, the sensor is formed from a working electrode 44 and a reference electrode 46 helically wound around the working electrode 44. An insulator 45 is disposed between the working and reference electrodes to provide necessary electrical insulation therebetween. Certain portions of the electrodes are exposed to enable electrochemical reaction thereon, for example, a window 43 can be formed in the insulator to expose a portion of the working electrode 44 for electrochemical reaction.


In preferred embodiments, each electrode is formed from a fine wire with a diameter of from about 0.001 or less to about 0.010 inches or more, for example, and is formed from, e.g., a plated insulator, a plated wire, or bulk electrically conductive material. Although the illustrated electrode configuration and associated text describe one preferred method of forming a transcutaneous sensor, a variety of known transcutaneous sensor configurations can be employed with the transcutaneous analyte sensor system of the preferred embodiments, such as U.S. Pat. No. 5,711,861 to Ward et al., U.S. Pat. No. 6,642,015 to Vachon et al., U.S. Pat. No. 6,654,625 to Say et al., U.S. Pat. No. 6,565,509 to Say et al., U.S. Pat. No. 6,514,718 to Heller, U.S. Pat. No. 6,465,066 to Essenpreis et al., U.S. Pat. No. 6,214,185 to Offenbacher et al., U.S. Pat. No. 5,310,469 to Cunningham et al., and U.S. Pat. No. 5,683,562 to Shaffer et al., U.S. Pat. No. 6,579,690 to Bonnecaze et al., U.S. Pat. No. 6,484,046 to Say et al., U.S. Pat. No. 6,512,939 to Colvin et al., U.S. Pat. No. 6,424,847 to Mastrototaro et al., U.S. Pat. No. 6,424,847 to Mastrototaro et al., for example. All of the above patents are not inclusive of all applicable analyte sensors; in general, it should be understood that the disclosed embodiments are applicable to a variety of analyte sensor configurations. Much of the description of the preferred embodiments, for example the membrane system described below, can be implemented not only with in vivo sensors, but also with in vitro sensors, such as blood glucose meters (SMBG).


In preferred embodiments, the working electrode comprises a wire formed from a conductive material, such as platinum, platinum-iridium, palladium, graphite, gold, carbon, conductive polymer, alloys, or the like. Although the electrodes can by formed by a variety of manufacturing techniques (bulk metal processing, deposition of metal onto a substrate, or the like), it can be advantageous to form the electrodes from plated wire (e.g., platinum on steel wire) or bulk metal (e.g., platinum wire). It is believed that electrodes formed from bulk metal wire provide superior performance (e.g., in contrast to deposited electrodes), including increased stability of assay, simplified manufacturability, resistance to contamination (e.g., which can be introduced in deposition processes), and improved surface reaction (e.g., due to purity of material) without peeling or delamination.


The working electrode 44 is configured to measure the concentration of an analyte. In an enzymatic electrochemical sensor for detecting glucose, for example, the working electrode measures the hydrogen peroxide produced by an enzyme catalyzed reaction of the analyte being detected and creates a measurable electronic current For example, in the detection of glucose wherein glucose oxidase produces hydrogen peroxide as a byproduct, hydrogen peroxide reacts with the surface of the working electrode producing two protons (2H+), two electrons (2e) and one molecule of oxygen (O2), which produces the electronic current being detected.


In preferred embodiments, the working electrode 44 is covered with an insulating material 45, for example, a non-conductive polymer. Dip-coating, spray-coating, vapor-deposition, or other coating or deposition techniques can be used to deposit the insulating material on the working electrode. In one embodiment, the insulating material comprises parylene, which can be an advantageous polymer coating for its strength, lubricity, and electrical insulation properties. Generally, parylene is produced by vapor deposition and polymerization of para-xylylene (or its substituted derivatives). While not wishing to be bound by theory, it is believed that the lubricious (e.g., smooth) coating (e.g., parylene) on the sensors of the preferred embodiments contributes to minimal trauma and extended sensor life. While parylene coatings are generally preferred, any suitable insulating material can be used, for example, fluorinated polymers, polyethyleneterephthalate, polyurethane, polyimide, other nonconducting polymers, or the like. Glass or ceramic materials can also be employed. Other materials suitable for use include surface energy modified coating systems such as are marketed under the trade names AMC18, AMC148, AMC141, and AMC321 by Advanced Materials Components Express of Bellefonte, Pa. In some alternative embodiments, however, the working electrode may not require a coating of insulator.


The reference electrode 46, which can function as a reference electrode alone, or as a dual reference and counter electrode, is formed from silver, silver/silver chloride, or the like. Preferably, the reference electrode 46 is juxtapositioned and/or twisted with or around the working electrode 44; however other configurations are also possible (e.g., an intradermal or on-skin reference electrode). In the illustrated embodiments, the reference electrode 46 is helically wound around the working electrode 44. The assembly of wires is then optionally coated or adhered together with an insulating material, similar to that described above, so as to provide an insulating attachment.


In some embodiments, a silver wire is formed onto the sensor as described above, and subsequently chloridized to form silver/silver chloride reference electrode. Advantageously, chloridizing the silver wire as described herein enables the manufacture of a reference electrode with optimal in vivo performance. Namely, by controlling the quantity and amount of chloridization of the silver to form silver/silver chloride, improved break-in time, stability of the reference electrode, and extended life has been shown with the preferred embodiments. Additionally, use of silver chloride as described above allows for relatively inexpensive and simple manufacture of the reference electrode.


In embodiments wherein an outer insulator is disposed, a portion of the coated assembly structure can be stripped or otherwise removed, for example, by hand, excimer lasing, chemical etching, laser ablation, grit-blasting (e.g., with sodium bicarbonate or other suitable grit), or the like, to expose the electroactive surfaces. Alternatively, a portion of the electrode can be masked prior to depositing the insulator in order to maintain an exposed electroactive surface area. In one exemplary embodiment, grit blasting is implemented to expose the electroactive surfaces, preferably utilizing a grit material that is sufficiently hard to ablate the polymer material, while being sufficiently soft so as to minimize or avoid damage to the underlying metal electrode (e.g., a platinum electrode). Although a variety of “grit” materials can be used (e.g., sand, talc, walnut shell, ground plastic, sea salt, and the like), in some preferred embodiments, sodium bicarbonate is an advantageous grit-material because it is sufficiently hard to ablate, e.g., a parylene coating without damaging, e.g., an underlying platinum conductor. One additional advantage of sodium bicarbonate blasting includes its polishing action on the metal as it strips the polymer layer, thereby eliminating a cleaning step that might otherwise be necessary.


In the embodiment illustrated in FIG. 6B, a radial window 43 is formed through the insulating material 45 to expose a circumferential electroactive surface of the working electrode. Additionally, sections 41 of electroactive surface of the reference electrode are exposed. For example, the 41 sections of electroactive surface can be masked during deposition of an outer insulating layer or etched after deposition of an outer insulating layer.


In some applications, cellular attack or migration of cells to the sensor can cause reduced sensitivity and/or function of the device, particularly after the first day of implantation. However, when the exposed electroactive surface is distributed circumferentially about the sensor (e.g., as in a radial window), the available surface area for reaction can be sufficiently distributed so as to minimize the effect of local cellular invasion of the sensor on the sensor signal. Alternatively, a tangential exposed electroactive window can be formed, for example, by stripping only one side of the coated assembly structure. In other alternative embodiments, the window can be provided at the tip of the coated assembly structure such that the electroactive surfaces are exposed at the tip of the sensor. Other methods and configurations for exposing electroactive surfaces can also be employed.


In some embodiments, the working electrode has a diameter of from about 0.001 inches or less to about 0.010 inches or more, preferably from about 0.002 inches to about 0.008 inches, and more preferably from about 0.004 inches to about 0.005 inches. The length of the window can be from about 0.1 mm (about 0.004 inches) or less to about 2 mm (about 0.078 inches) or more, and preferably from about 0.5 mm (about 0.02 inches) to about 0.75 mm (0.03 inches). In such embodiments, the exposed surface area of the working electrode is preferably from about 0.000013 in2 (0.0000839 cm2) or less to about 0.0025 in2 (0.016129 cm2) or more (assuming a diameter of from about 0.001 inches to about 0.010 inches and a length of from about 0.004 inches to about 0.078 inches). The preferred exposed surface area of the working electrode is selected to produce an analyte signal with a current in the picoAmp range, such as is described in more detail elsewhere herein. However, a current in the picoAmp range can be dependent upon a variety of factors, for example the electronic circuitry design (e.g., sample rate, current draw. A/D converter bit resolution, etc.), the membrane system (e.g., permeability of the analyte through the membrane system), and the exposed surface area of the working electrode. Accordingly, the exposed electroactive working electrode surface area can be selected to have a value greater than or less than the above-described ranges taking into consideration alterations in the membrane system and/or electronic circuitry. In preferred embodiments of a glucose sensor, it can be advantageous to minimize the surface area of the working electrode while maximizing the diffusivity of glucose in order to optimize the signal-to-noise ratio while maintaining sensor performance in both high and low glucose concentration ranges.


In some alternative embodiments, the exposed surface area of the working (and/or other) electrode can be increased by altering the cross-section of the electrode itself. For example, in some embodiments the cross-section of the working electrode can be defined by a cross, star, cloverleaf, ribbed, dimpled, ridged, irregular, or other non-circular configuration; thus, for any predetermined length of electrode, a specific increased surface area can be achieved (as compared to the area achieved by a circular cross-section). Increasing the surface area of the working electrode can be advantageous in providing an increased signal responsive to the analyte concentration, which in turn can be helpful in improving the signal-to-noise ratio, for example.


In some alternative embodiments, additional electrodes can be included within the assembly, for example, a three-electrode system (working, reference, and counter electrodes) and/or an additional working electrode (e.g., an electrode which can be used to generate oxygen, which is configured as a baseline subtracting electrode, or which is configured for measuring additional analytes). U.S. Publication No. US-2005-0161346-A1 and U.S. Publication No. US-2005-0143635-A1 describe some systems and methods for implementing and using additional working, counter, and/or reference electrodes. In one implementation wherein the sensor comprises two working electrodes, the two working electrodes are juxtapositioned (e.g., extend parallel to each other), around which the reference electrode is disposed (e.g., helically wound). In some embodiments wherein two or more working electrodes are provided, the working electrodes can be formed in a double-, triple-, quad-, etc. helix configuration along the length of the sensor (for example, surrounding a reference electrode, insulated rod, or other support structure). The resulting electrode system can be configured with an appropriate membrane system, wherein the first working electrode is configured to measure a first signal comprising glucose and baseline and the additional working electrode is configured to measure a baseline signal consisting of baseline only (e.g., configured to be substantially similar to the first working electrode without an enzyme disposed thereon). In this way, the baseline signal can be subtracted from the first signal to produce a glucose-only signal that is substantially not subject to fluctuations in the baseline and/or interfering species on the signal.


Although the preferred embodiments illustrate one electrode configuration including one bulk metal wire helically wound around another bulk metal wire, other electrode configurations are also contemplated. In an alternative embodiment, the working electrode comprises a tube with a reference electrode disposed or coiled inside, including an insulator therebetween. Alternatively, the reference electrode comprises a tube with a working electrode disposed or coiled inside, including an insulator therebetween. In another alternative embodiment, a polymer (e.g., insulating) rod is provided, wherein the electrodes are deposited (e.g., electro-plated) thereon. In yet another alternative embodiment, a metallic (e.g., steel) rod is provided, coated with an insulating material, onto which the working and reference electrodes are deposited. In yet another alternative embodiment, one or more working electrodes are helically wound around a reference electrode.


Preferably, the electrodes and membrane systems of the preferred embodiments are coaxially formed, namely, the electrodes and/or membrane system all share the same central axis. While not wishing to be bound by theory, it is believed that a coaxial design of the sensor enables a symmetrical design without a preferred bend radius. Namely, in contrast to prior art sensors comprising a substantially planar configuration that can suffer from regular bending about the plane of the sensor, the coaxial design of the preferred embodiments do not have a preferred bend radius and therefore are not subject to regular bending about a particular plane (which can cause fatigue failures and the like). However, non-coaxial sensors can be implemented with the sensor system of the preferred embodiments.


In addition to the above-described advantages, the coaxial sensor design of the preferred embodiments enables the diameter of the connecting end of the sensor (proximal portion) to be substantially the same as that of the sensing end (distal portion) such that the needle is able to insert the sensor into the host and subsequently slide back over the sensor and release the sensor from the needle, without slots or other complex multi-component designs.


In one such alternative embodiment, the two wires of the sensor are held apart and configured for insertion into the host in proximal but separate locations. The separation of the working and reference electrodes in such an embodiment can provide additional electrochemical stability with simplified manufacture and electrical connectivity. It is appreciated by one skilled in the art that a variety of electrode configurations can be implemented with the preferred embodiments.


In some embodiments, the sensor includes an antimicrobial portion configured to extend through the exit-site when the sensor is implanted in the host. Namely, the sensor is designed with in vivo and ex vivo portions as described in more detail elsewhere herein; additionally, the sensor comprises a transition portion, also referred to as an antimicrobial portion, located between the in vivo and ex vivo portions 42, 40. The antimicrobial portion is designed to provide antimicrobial effects to the exit-site and adjacent tissue when implanted in the host.


In some embodiments, the antimicrobial portion comprises silver, e.g., the portion of a silver reference electrode that is configured to extend through the exit-site when implanted. Although exit-site infections are a common adverse occurrence associated with some conventional transcutaneous medical devices, the devices of preferred embodiments are designed at least in part to minimize infection, to minimize irritation, and/or to extend the duration of implantation of the sensor by utilizing a silver reference electrode to extend through the exit-site when implanted in a patient. While not wishing to be bound by theory, it is believed that the silver may reduce local tissue infections (within the tissue and at the exit-site); namely, steady release of molecular quantities of silver is believed to have an antimicrobial effect in biological tissue (e.g., reducing or preventing irritation and infection), also referred to as passive antimicrobial effects. Although one example of passive antimicrobial effects is described herein, one skilled in the art can appreciate a variety of passive anti-microbial systems and methods that can be implemented with the preferred embodiments. Additionally, it is believed that antimicrobial effects can contribute to extended life of a transcutaneous analyte sensor, enabling a functional lifetime past a few days, e.g., seven days or longer.


In some embodiments, active antimicrobial systems and methods are provided in the sensor system in order to further enhance the antimicrobial effects at the exit-site. In one such embodiment, an auxiliary silver wire is disposed on or around the sensor, wherein the auxiliary silver wire is connected to electronics and configured to pass a current sufficient to enhance its antimicrobial properties (active antimicrobial effects), as is appreciated by one skilled in the art. The current can be passed continuously or intermittently, such that sufficient antimicrobial properties are provided. Although one example of active antimicrobial effects is described herein, one skilled in the art can appreciate a variety of active anti-microbial systems and methods that can be implemented with the preferred embodiments.


Anchoring Mechanism


It is preferred that the sensor remains substantially stationary within the tissue of the host, such that migration or motion of the sensor with respect to the surrounding tissue is minimized. Migration or motion is believed to cause inflammation at the sensor implant site due to irritation, and can also cause noise on the sensor signal due to motion-related artifact, for example. Therefore, it can be advantageous to provide an anchoring mechanism that provides support for the sensor's in vivo portion to avoid the above-mentioned problems. Combining advantageous sensor geometry with an advantageous anchoring minimizes additional parts and allows for an optimally small or low profile design of the sensor. In one embodiment the sensor includes a surface topography, such as the helical surface topography provided by the reference electrode surrounding the working electrode. In alternative embodiments, a surface topography could be provided by a roughened surface, porous surface (e.g. porous parylene), ridged surface, or the like. Additionally (or alternatively), the anchoring can be provided by prongs, spines, barbs, wings, hooks, a bulbous portion (for example, at the distal end), an S-bend along the sensor, a rough surface topography, a gradually changing diameter, combinations thereof, or the like, which can be used alone or in combination with the helical surface topography to stabilize the sensor within the subcutaneous tissue.


Variable Stiffness


As described above, conventional transcutaneous devices are believed to suffer from motion artifact associated with host movement when the host is using the device. For example, when a transcutaneous analyte sensor is inserted into the host, various movements on the sensor (for example, relative movement within and between the subcutaneous space, dermis, skin, and external portions of the sensor) create stresses on the device, which is known to produce artifacts on the sensor signal. Accordingly, there are different design considerations (for example, stress considerations) on various sections of the sensor. For example, the distal portion 42 of the sensor can benefit in general from greater flexibility as it encounters greater mechanical stresses caused by movement of the tissue within the patient and relative movement between the in vivo and ex vivo portions of the sensor. On the other hand, the proximal portion 40 of the sensor can benefit in general from a stiffer, more robust design to ensure structural integrity and/or reliable electrical connections. Additionally, in some embodiments wherein a needle is retracted over the proximal portion 40 of the device (see FIGS. 7 to 9), a stiffer design can minimize crimping of the sensor and/or ease in retraction of the needle from the sensor. Thus, by designing greater flexibility into the in vivo (distal) portion 42, the flexibility is believed to compensate for patient movement, and noise associated therewith. By designing greater stiffness into the ex vivo (proximal) portion 40, column strength (for retraction of the needle over the sensor), electrical connections, and integrity can be enhanced. In some alternative embodiments, a stiffer distal end and/or a more flexible proximal end can be advantageous as described in U.S. Publication No. US-2006-0015024-A1.


The preferred embodiments provide a distal portion 42 of the sensor 32 designed to be more flexible than a proximal portion 40 of the sensor. The variable stiffness of the preferred embodiments can be provided by variable pitch of any one or more helically wound wires of the device, variable cross-section of any one or more wires of the device, and/or variable hardening and/or softening of any one or more wires of the device, such as is described in more detail with reference to U.S. Publication No. US-2006-0015024-A1.


Membrane System



FIG. 6C is a cross-sectional view through the sensor on line C-C of FIG. 6B showing the exposed electroactive surface of the working electrode surrounded by the membrane system in one embodiment. Preferably, a membrane system is deposited over at least a portion of the electroactive surfaces of the sensor 32 (working electrode and optionally reference electrode) and provides protection of the exposed electrode surface from the biological environment, diffusion resistance (limitation) of the analyte if needed, a catalyst for enabling an enzymatic reaction, limitation or blocking of interferents, and/or hydrophilicity at the electrochemically reactive surfaces of the sensor interface. Some examples of suitable membrane systems are described in U.S. Publication No. US-2005-0245799-A1.


In general, the membrane system includes a plurality of domains, for example, an electrode domain 47, an interference domain 48, an enzyme domain 49 (for example, including glucose oxidase), and a resistance domain 50, as shown in FIG. 6C, and can include a high oxygen solubility domain, and/or a bioprotective domain (not shown), such as is described in more detail in U.S. Publication No. US-2005-0245799-A1. The membrane system can be deposited on the exposed electroactive surfaces using known thin film techniques (for example, vapor deposition, spraying, electro-depositing, dipping, or the like). In alternative embodiments, however, other vapor deposition processes (e.g., physical and/or chemical vapor deposition processes) can be useful for providing one or more of the insulating and/or membrane layers, including ultrasonic vapor deposition, electrostatic deposition, evaporative deposition, deposition by sputtering, pulsed laser deposition, high velocity oxygen fuel deposition, thermal evaporator deposition, electron beam evaporator deposition, deposition by reactive sputtering molecular beam epitaxy, atmospheric pressure chemical vapor deposition (CVD), atomic layer CVD, hot wire CVD, low-pressure CVD, microwave plasma-assisted CVD, plasma-enhanced CVD, rapid thermal CVD, remote plasma-enhanced CVD, and ultra-high vacuum CVD, for example. However, the membrane system can be disposed over (or deposited on) the electroactive surfaces using any known method, as will be appreciated by one skilled in the art.


In some embodiments, one or more domains of the membrane systems are formed from materials such as described above in connection with the porous layer, such as silicone, polytetrafluoroethylene, polyethylene-co-tetrafluoroethylene, polyolefin, polyester, polycarbonate, biostable polytetrafluoroethylene, homopolymers, copolymers, terpolymers of polyurethanes, polypropylene (PP), polyvinylchloride (PVC), polyvinylidene fluoride (PVDF), polybutylene terephthalate (PBT), polymethylmethacrylate (PMMA), polyether ether ketone (PEEK), polyurethanes, cellulosic polymers, polysulfones and block copolymers thereof including, for example, di-block, tri-block, alternating, random and graft copolymers. U.S. Publication No. US-2005-0245799-A1 describes biointerface and membrane system configurations and materials that can be applied to the preferred embodiments.


Electrode Domain


In selected embodiments, the membrane system comprises an electrode domain. The electrode domain 47 is provided to ensure that an electrochemical reaction occurs between the electroactive surfaces of the working electrode and the reference electrode, and thus the electrode domain 47 is preferably situated more proximal to the electroactive surfaces than the interference and/or enzyme domain. Preferably, the electrode domain includes a coating that maintains a layer of water at the electrochemically reactive surfaces of the sensor. In other words, the electrode domain is present to provide an environment between the surfaces of the working electrode and the reference electrode which facilitates an electrochemical reaction between the electrodes. For example, a humectant in a binder material can be employed as an electrode domain; this allows for the full transport of ions in the aqueous environment. The electrode domain can also assist in stabilizing the operation of the sensor by accelerating electrode start-up and drifting problems caused by inadequate electrolyte. The material that forms the electrode domain can also provide an environment that protects against pH-mediated damage that can result from the formation of a large pH gradient due to the electrochemical activity of the electrodes.


In one embodiment, the electrode domain 47 includes a flexible, water-swellable, hydrogel film having a “dry film” thickness of from about 0.05 micron or less to about 20 microns or more, more preferably from about 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4.0.45, 0.5, 1, 1.5.2, 2.5, 3, or 3.5 microns to about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 19.5 microns, and more preferably still from about 2, 2.5 or 3 microns to about 3.5, 4, 4.5, or 5 microns. “Dry film” thickness refers to the thickness of a cured film cast from a coating formulation by standard coating techniques.


In certain embodiments, the electrode domain 47 is formed of a curable mixture of a urethane polymer and a hydrophilic polymer. Particularly preferred coatings are formed of a polyurethane polymer having carboxylate or hydroxyl functional groups and non-ionic hydrophilic polyether segments, wherein the polyurethane polymer is crosslinked with a water soluble carbodiimide (e.g., 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC)) in the presence of polyvinylpyrrolidone and cured at a moderate temperature of about 50° C.


In some preferred embodiments, the electrode domain 47 is formed from a hydrophilic polymer such as polyvinylpyrrolidone (PVP). An electrode domain formed from PVP has been shown to reduce break-in time of analyte sensors; for example, a glucose sensor utilizing a cellulosic-based interference domain such as described in more detail below.


Preferably, the electrode domain is deposited by vapor deposition, spray coating, dip coating, or other thin film techniques on the electroactive surfaces of the sensor. In one preferred embodiment, the electrode domain is formed by dip-coating the electroactive surfaces in an electrode layer solution and curing the domain for a time of from about 15 minutes to about 30 minutes at a temperature of from about 40° C. to about 55° C. (and can be accomplished under vacuum (e.g., 20 to 30 mmHg)). In embodiments wherein dip-coating is used to deposit the electrode domain, a preferred insertion rate of from about 1 to about 3 inches per minute into the electrode layer solution, with a preferred dwell time of from about 0.5 to about 2 minutes in the electrode layer solution, and a preferred withdrawal rate of from about 0.25 to about 2 inches per minute from the electrode layer solution provide a functional coating. However, values outside of those set forth above can be acceptable or even desirable in certain embodiments, for example, depending upon solution viscosity and solution surface tension, as is appreciated by one skilled in the art. In one embodiment, the electroactive surfaces of the electrode system are dip-coated one time (one layer) and cured at 50° C. under vacuum for 20 minutes.


Although an independent electrode domain 47 is described herein, in some embodiments sufficient hydrophilicity can be provided in the interference domain and/or enzyme domain (the domain adjacent to the electroactive surfaces) so as to provide for the full transport of ions in the aqueous environment (e.g. without a distinct electrode domain). In these embodiments, an electrode domain is not necessary.


Interference Domain


Interferents are molecules or other species that are reduced or oxidized at the electrochemically reactive surfaces of the sensor, either directly or via an electron transfer agent, to produce a false positive analyte signal. In preferred embodiments, an interference domain 48 is provided that substantially restricts, resists, or blocks the flow of one or more interfering species. Some known interfering species for a glucose sensor, as described in more detail above, include acetaminophen, ascorbic acid, bilirubin, cholesterol, creatinine, dopamine, ephedrine, ibuprofen. L-dopa, methyl dopa, salicylate, tetracycline, tolazamide, tolbutamide, triglycerides, and uric acid. In general, the interference domain of the preferred embodiments is less permeable to one or more of the interfering species than to the analyte, e.g., glucose.


In one embodiment, the interference domain 48 is formed from one or more cellulosic derivatives. In general, cellulosic derivatives include polymers such as cellulose acetate, cellulose acetate butyrate, 2-hydroxyethyl cellulose, cellulose acetate phthalate, cellulose acetate propionate, cellulose acetate trimellitate, and the like.


In one preferred embodiment, the interference domain 48 is formed from cellulose acetate butyrate. Cellulose acetate butyrate with a molecular weight of from about 10,000 daltons to about 75,000 daltons, preferably from about 15,000, 20,000, or 25,000 daltons to about 50,000, 55,000, 60,000, 65,000, or 70,000 daltons, and more preferably about 20,000 daltons is employed. In certain embodiments, however, higher or lower molecular weights can be preferred. Additionally, a casting solution or dispersion of cellulose acetate butyrate at a weight percent of from about 15% to about 25%, preferably from about 15%, 16%, 17%, 18%, 19% to about 20%, 21%, 22%, 23%, 24% or 25%, and more preferably about 18% is preferred. Preferably, the casting solution includes a solvent or solvent system, for example an acetone:ethanol solvent system. Higher or lower concentrations can be preferred in certain embodiments. A plurality of layers of cellulose acetate butyrate can be advantageously combined to form the interference domain in some embodiments, for example, three layers can be employed. It can be desirable to employ a mixture of cellulose acetate butyrate components with different molecular weights in a single solution, or to deposit multiple layers of cellulose acetate butyrate from different solutions comprising cellulose acetate butyrate of different molecular weights, different concentrations, and/or different chemistries (e.g., functional groups). It can also be desirable to include additional substances in the casting solutions or dispersions, e.g., functionalizing agents, crosslinking agents, other polymeric substances, substances capable of modifying the hydrophilicity/hydrophobicity of the resulting layer, and the like.


In one alternative embodiment, the interference domain 48 is formed from cellulose acetate. Cellulose acetate with a molecular weight of from about 30,000 daltons or less to about 100,000 daltons or more, preferably from about 35,000, 40,000, or 45,000 daltons to about 55,000, 60,000, 65,000, 70,000, 75,000, 80,000, 85,000, 90,000, or 95,000 daltons, and more preferably about 50,000 daltons is preferred. Additionally, a casting solution or dispersion of cellulose acetate at a weight percent of about 3% to about 10%, preferably from about 3.5%, 4.0%, 4.5%, 5.0%, 5.5%, 6.0%, or 6.5% to about 7.5%, 8.0%, 8.5%, 9.0%, or 9.5%, and more preferably about 8% is preferred. In certain embodiments, however, higher or lower molecular weights and/or cellulose acetate weight percentages can be preferred. It can be desirable to employ a mixture of cellulose acetates with molecular weights in a single solution, or to deposit multiple layers of cellulose acetate from different solutions comprising cellulose acetates of different molecular weights, different concentrations, or different chemistries (e.g., functional groups). It can also be desirable to include additional substances in the casting solutions or dispersions such as described in more detail above.


Layer(s) prepared from combinations of cellulose acetate and cellulose acetate butyrate, or combinations of layer(s) of cellulose acetate and layer(s) of cellulose acetate butyrate can also be employed to form the interference domain 48.


In some alternative embodiments, additional polymers, such as Nafion®, can be used in combination with cellulosic derivatives to provide equivalent and/or enhanced function of the interference domain 48. As one example, a 5 wt % Nafion® casting solution or dispersion can be used in combination with a 8 wt % cellulose acetate casting solution or dispersion, e.g., by dip coating at least one layer of cellulose acetate and subsequently dip coating at least one layer Nafion® onto a needle-type sensor such as described with reference to the preferred embodiments. Any number of coatings or layers formed in any order may be suitable for forming the interference domain of the preferred embodiments.


In some alternative embodiments, more than one cellulosic derivative can be used to form the interference domain 48 of the preferred embodiments. In general, the formation of the interference domain on a surface utilizes a solvent or solvent system in order to solvate the cellulosic derivative (or other polymer) prior to film formation thereon. In preferred embodiments, acetone and ethanol are used as solvents for cellulose acetate; however one skilled in the art appreciates the numerous solvents that are suitable for use with cellulosic derivatives (and other polymers). Additionally, one skilled in the art appreciates that the preferred relative amounts of solvent can be dependent upon the cellulosic derivative (or other polymer) used, its molecular weight, its method of deposition, its desired thickness, and the like. However, a percent solute of from about 1% to about 25% is preferably used to form the interference domain solution so as to yield an interference domain having the desired properties. The cellulosic derivative (or other polymer) used, its molecular weight, method of deposition, and desired thickness can be adjusted, depending upon one or more other of the parameters, and can be varied accordingly as is appreciated by one skilled in the art.


In some alternative embodiments, other polymer types that can be utilized as a base material for the interference domain 48 including polyurethanes, polymers having pendant ionic groups, and polymers having controlled pore size, for example. In one such alternative embodiment, the interference domain includes a thin, hydrophobic membrane that is non-swellable and restricts diffusion of low molecular weight species. The interference domain 48 is permeable to relatively low molecular weight substances, such as hydrogen peroxide, but restricts the passage of higher molecular weight substances, including glucose and ascorbic acid. Other systems and methods for reducing or eliminating interference species that can be applied to the membrane system of the preferred embodiments are described in U.S. Publication No. US-2005-0115832-A1, U.S. Publication No. US-2005-0176136-A1. U.S. Publication No. US-2005-0161346-A1, and U.S. Publication No. US-2005-0143635-A1. In some alternative embodiments, a distinct interference domain is not included.


In preferred embodiments, the interference domain 48 is deposited directly onto the electroactive surfaces of the sensor for a domain thickness of from about 0.05 microns or less to about 20 microns or more, more preferably from about 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 1, 1.5, 2, 2.5, 3, or 3.5 microns to about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 19.5 microns, and more preferably still from about 1, 1.5 or 2 microns to about 2.5 or 3 microns. Thicker membranes can also be desirable in certain embodiments, but thinner membranes are generally preferred because they have a lower impact on the rate of diffusion of hydrogen peroxide from the enzyme membrane to the electrodes.


In general, the membrane systems of the preferred embodiments can be formed and/or deposited on the exposed electroactive surfaces (e.g., one or more of the working and reference electrodes) using known thin film techniques (for example, casting, spray coating, drawing down, electro-depositing, dip coating, and the like), however casting or other known application techniques can also be utilized. Preferably, the interference domain is deposited by vapor deposition, spray coating, or dip coating. In one exemplary embodiment of a needle-type (transcutaneous) sensor such as described herein, the interference domain is formed by dip coating the sensor into an interference domain solution using an insertion rate of from about 20 inches/min to about 60 inches/min, preferably 40 inches/min, a dwell time of from about 0 minute to about 5 seconds, preferably 0 seconds, and a withdrawal rate of from about 20 inches/minute to about 60 inches/minute, preferably about 40 inches/minute, and curing (drying) the domain from about 1 minute to about 30 minutes, preferably from about 3 minutes to about 15 minutes (and can be accomplished at room temperature or under vacuum (e.g., 20 to 30 mmHg)). In one exemplary embodiment including cellulose acetate butyrate interference domain, a 3-minute cure (i.e., dry) time is preferred between each layer applied. In another exemplary embodiment employing a cellulose acetate interference domain, a 15 minute cure (i.e., dry) time is preferred between each layer applied.


The dip process can be repeated at least one time and up to 10 times or more. The preferred number of repeated dip processes depends upon the cellulosic derivative(s) used, their concentration, conditions during deposition (e.g., dipping) and the desired thickness (e.g., sufficient thickness to provide functional blocking of (or resistance to) certain interferents), and the like. In some embodiments, 1 to 3 microns may be preferred for the interference domain thickness; however, values outside of these can be acceptable or even desirable in certain embodiments, for example, depending upon viscosity and surface tension, as is appreciated by one skilled in the art. In one exemplary embodiment, an interference domain is formed from three layers of cellulose acetate butyrate. In another exemplary embodiment, an interference domain is formed from 10 layers of cellulose acetate. In alternative embodiments, the interference domain can be formed using any known method and combination of cellulose acetate and cellulose acetate butyrate, as will be appreciated by one skilled in the art.


In some embodiments, the electroactive surface can be cleaned prior to application of the interference domain 48. In some embodiments, the interference domain 48 of the preferred embodiments can be useful as a bioprotective or biocompatible domain, namely, a domain that interfaces with host tissue when implanted in an animal (e.g., a human) due to its stability and biocompatibility.


Enzyme Domain


In preferred embodiments, the membrane system further includes an enzyme domain 49 disposed more distally from the electroactive surfaces than the interference domain 48; however other configurations can be desirable. In the preferred embodiments, the enzyme domain provides an enzyme to catalyze the reaction of the analyte and its co-reactant, as described in more detail below. In the preferred embodiments of a glucose sensor, the enzyme domain includes glucose oxidase; however other oxidases, for example, galactose oxidase or uricase oxidase, can also be used.


For an enzyme-based electrochemical glucose sensor to perform well, the sensor's response is preferably limited by neither enzyme activity nor co-reactant concentration. Because enzymes, including glucose oxidase, are subject to deactivation as a function of time even in ambient conditions, this behavior is compensated for in forming the enzyme domain. Preferably, the enzyme domain is constructed of aqueous dispersions of colloidal polyurethane polymers including the enzyme. However, in alternative embodiments the enzyme domain is constructed from an oxygen enhancing material, for example, silicone, or fluorocarbon, in order to provide a supply of excess oxygen during transient ischemia. Preferably, the enzyme is immobilized within the domain. See, e.g., U.S. Publication No. US-2005-0054909-A1.


In preferred embodiments, the enzyme domain is deposited onto the interference domain for a domain thickness of from about 0.05 micron or less to about 20 microns or more, more preferably from about 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 1, 1.5, 2, 2.5, 3, or 3.5 microns to about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 19.5 microns, and more preferably still from about 2, 2.5 or 3 microns to about 3.5, 4, 4.5, or 5 microns. However in some embodiments, the enzyme domain can be deposited directly onto the electroactive surfaces. Preferably, the enzyme domain is deposited by spray or dip coating. In one embodiment of needle-type (transcutaneous) sensor such as described herein, the enzyme domain is formed by dip coating the interference domain coated sensor into an enzyme domain solution and curing the domain for from about 15 to about 30 minutes at a temperature of from about 40° C. to about 55° C. (and can be accomplished under vacuum (e.g., 20 to 30 mmHg)). In embodiments wherein dip coating is used to deposit the enzyme domain at room temperature, a preferred insertion rate of from about 0.25 inch per minute to about 3 inches per minute, with a preferred dwell time of from about 0.5 minutes to about 2 minutes, and a preferred withdrawal rate of from about 0.25 inch per minute to about 2 inches per minute provides a functional coating. However, values outside of those set forth above can be acceptable or even desirable in certain embodiments, for example, depending upon viscosity and surface tension, as is appreciated by one skilled in the art. In one embodiment, the enzyme domain is formed by dip coating two times (namely, forming two layers) in an enzyme domain solution and curing at 50° C. under vacuum for 20 minutes. However, in some embodiments, the enzyme domain can be formed by dip coating and/or spray coating one or more layers at a predetermined concentration of the coating solution, insertion rate, dwell time, withdrawal rate, and/or desired thickness.


Resistance Domain


In preferred embodiments, the membrane system includes a resistance domain 50 disposed more distal from the electroactive surfaces than the enzyme domain. Although the following description is directed to a resistance domain for a glucose sensor, the resistance domain can be modified for other analytes and co-reactants as well.


There exists a molar excess of glucose relative to the amount of oxygen in blood; that is, for every free oxygen molecule in extracellular fluid, there are typically more than 100 glucose molecules present (see Updike et al., Diabetes Care 5:207-21(1982)). However, an immobilized enzyme-based glucose sensor employing oxygen as co-reactant is preferably supplied with oxygen in non-rate-limiting excess in order for the sensor to respond linearly to changes in glucose concentration, while not responding to changes in oxygen concentration. Specifically, when a glucose-monitoring reaction is oxygen limited, linearity is not achieved above minimal concentrations of glucose. Without a semipermeable membrane situated over the enzyme domain to control the flux of glucose and oxygen, a linear response to glucose levels can be obtained only for glucose concentrations of up to about 40 mg/dL. However, in a clinical setting, a linear response to glucose levels is desirable up to at least about 400 mg/dL.


The resistance domain includes a semipermeable membrane that controls the flux of oxygen and glucose to the underlying enzyme domain, preferably rendering oxygen in a non-rate-limiting excess. As a result, the upper limit of linearity of glucose measurement is extended to a much higher value than that which is achieved without the resistance domain. In one embodiment, the resistance domain exhibits an oxygen to glucose permeability ratio of from about 50:1 or less to about 400:1 or more, preferably about 200:1. As a result, one-dimensional reactant diffusion is adequate to provide excess oxygen at all reasonable glucose and oxygen concentrations found in the subcutaneous matrix (see Rhodes et al., Anal. Chem., 66:1520-1529 (1994)).


In alternative embodiments, a lower ratio of oxygen-to-glucose can be sufficient to provide excess oxygen by using a high oxygen solubility domain (for example, a silicone or fluorocarbon-based material or domain) to enhance the supply/transport of oxygen to the enzyme domain. If more oxygen is supplied to the enzyme, then more glucose can also be supplied to the enzyme without creating an oxygen rate-limiting excess. In alternative embodiments, the resistance domain is formed from a silicone composition, such as is described in U.S. Publication No. US-2005-0090607-A1.


In a preferred embodiment, the resistance domain includes a polyurethane membrane with both hydrophilic and hydrophobic regions to control the diffusion of glucose and oxygen to an analyte sensor, the membrane being fabricated easily and reproducibly from commercially available materials. A suitable hydrophobic polymer component is a polyurethane, or polyetherurethaneurea. Polyurethane is a polymer produced by the condensation reaction of a diisocyanate and a difunctional hydroxyl-containing material. A polyurethaneurea is a polymer produced by the condensation reaction of a diisocyanate and a difunctional amine-containing material. Preferred diisocyanates include aliphatic diisocyanates containing from about 4 to about 8 methylene units. Diisocyanates containing cycloaliphatic moieties can also be useful in the preparation of the polymer and copolymer components of the membranes of preferred embodiments. The material that forms the basis of the hydrophobic matrix of the resistance domain can be any of those known in the art as appropriate for use as membranes in sensor devices and as having sufficient permeability to allow relevant compounds to pass through it, for example, to allow an oxygen molecule to pass through the membrane from the sample under examination in order to reach the active enzyme or electrochemical electrodes. Examples of materials which can be used to make non-polyurethane type membranes include vinyl polymers, polyethers, polyesters, polyamides, inorganic polymers such as polysiloxanes and polycarbosiloxanes, natural polymers such as cellulosic and protein based materials, and mixtures or combinations thereof.


In a preferred embodiment, the hydrophilic polymer component is polyethylene oxide. For example, one useful hydrophobic-hydrophilic copolymer component is a polyurethane polymer that includes about 20% hydrophilic polyethylene oxide. The polyethylene oxide portions of the copolymer are thermodynamically driven to separate from the hydrophobic portions of the copolymer and the hydrophobic polymer component. The 20% polyethylene oxide-based soft segment portion of the copolymer used to form the final blend affects the water pick-up and subsequent glucose permeability of the membrane.


In preferred embodiments, the resistance domain is deposited onto the enzyme domain to yield a domain thickness of from about 0.05 microns or less to about 20 microns or more, more preferably from about 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 1, 1.5, 2, 2.5, 3, or 3.5 microns to about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 19.5 microns, and more preferably still from about 2, 2.5 or 3 microns to about 3.5, 4, 4.5, or 5 microns. Preferably, the resistance domain is deposited onto the enzyme domain by vapor deposition, spray coating, or dip coating. In one preferred embodiment, spray coating is the preferred deposition technique. The spraying process atomizes and mists the solution, and therefore most or all of the solvent is evaporated prior to the coating material settling on the underlying domain, thereby minimizing contact of the solvent with the enzyme.


In another preferred embodiment, physical vapor deposition (e.g., ultrasonic vapor deposition) is used for coating one or more of the membrane domain(s) onto the electrodes, wherein the vapor deposition apparatus and process include an ultrasonic nozzle that produces a mist of micro-droplets in a vacuum chamber. In these embodiments, the micro-droplets move turbulently within the vacuum chamber, isotropically impacting and adhering to the surface of the substrate. Advantageously, vapor deposition as described above can be implemented to provide high production throughput of membrane deposition processes (e.g., at least about 20 to about 200 or more electrodes per chamber), greater consistency of the membrane on each sensor, and increased uniformity of sensor performance, for example, as described below.


In some embodiments, depositing the resistance domain (for example, as described in the preferred embodiments above) includes formation of a membrane system that substantially blocks or resists ascorbate (a known electrochemical interferant in hydrogen peroxide-measuring glucose sensors). While not wishing to be bound by theory, it is believed that during the process of depositing the resistance domain as described in the preferred embodiments, a structural morphology is formed that is characterized in that ascorbate does not substantially permeate therethrough.


In a preferred embodiment, the resistance domain is deposited on the enzyme domain by spray coating a solution of from about 1 wt. % to about 5 wt. % polymer and from about 95 wt. % to about 99 wt. % solvent. In spraying a solution of resistance domain material, including a solvent, onto the enzyme domain, it is desirable to mitigate or substantially reduce any contact with enzyme of any solvent in the spray solution that can deactivate the underlying enzyme of the enzyme domain. Tetrahydrofuran (THF) is one solvent that minimally or negligibly affects the enzyme of the enzyme domain upon spraying. Other solvents can also be suitable for use, as is appreciated by one skilled in the art.


Although a variety of spraying or deposition techniques can be used, spraying the resistance domain material and rotating the sensor at least one time by 180° can typically provide adequate coverage by the resistance domain. Spraying the resistance domain material and rotating the sensor at least two times by 120° provides even greater coverage (one layer of 360° coverage), thereby ensuring resistivity to glucose, such as is described in more detail above.


In preferred embodiments, the resistance domain is spray coated and subsequently cured for a time of from about 15 minutes to about 90 minutes at a temperature of from about 40° C. to about 60° C. (and can be accomplished under vacuum (e.g., from 20 to 30 mmHg)). A cure time of up to about 90 minutes or more can be advantageous to ensure complete drying of the resistance domain.


In one embodiment, the resistance domain is formed by spray coating at least six layers (namely, rotating the sensor seventeen times by 120° for at least six layers of 360° coverage) and curing at 50° C. under vacuum for 60 minutes. However, the resistance domain can be formed by dip coating or spray coating any layer or plurality of layers, depending upon the concentration of the solution, insertion rate, dwell time, withdrawal rate, and/or the desired thickness of the resulting film. Additionally, curing in a convention oven can also be employed.


In certain embodiments, a variable frequency microwave oven can be used to cure the membrane domains/layers. In general, microwave ovens directly excite the rotational mode of solvents. Consequently, microwave ovens cure coatings from the inside out rather than from the outside in as with conventional convection ovens. This direct rotational mode excitation is responsible for the typically observed “fast” curing within a microwave oven. In contrast to conventional microwave ovens, which rely upon a fixed frequency of emission that can cause arcing of dielectric (metallic) substrates if placed within a conventional microwave oven. Variable Frequency Microwave (VFM) ovens emit thousands of frequencies within 100 milliseconds, which substantially eliminates arcing of dielectric substrates. Consequently, the membrane domains/layers can be cured even after deposition on metallic electrodes as described herein. While not wishing to be bound by theory, it is believe that VFM curing can increase the rate and completeness of solvent evaporation from a liquid membrane solution applied to a sensor, as compared to the rate and completeness of solvent evaporation observed for curing in conventional convection ovens.


In certain embodiments. VFM is can be used together with convection oven curing to further accelerate cure time. In some sensor applications wherein the membrane is cured prior to application on the electrode (see, for example, U.S. Publication No. US-2005-0245799-A1), conventional microwave ovens (e.g., fixed frequency microwave ovens) can be used to cure the membrane layer.


Treatment of Interference Domain/Membrane System


Although the above-described methods generally include a curing step in formation of the membrane system, including the interference domain, the preferred embodiments further include an additional treatment step, which can be performed directly after the formation of the interference domain and/or some time after the formation of the entire membrane system (or anytime in between). In some embodiments, the additional treatment step is performed during (or in combination with) sterilization of the sensor.


In some embodiments, the membrane system (or interference domain) is treated by exposure to ionizing radiation, for example, electron beam radiation. UV radiation. X-ray radiation, gamma radiation, and the like. Alternatively, the membrane can be exposed to visible light when suitable photoinitiators are incorporated into the interference domain. While not wishing to be bound by theory, it is believed that exposing the interference domain to ionizing radiation substantially crosslinks the interference domain and thereby creates a tighter, less permeable network than an interference domain that has not been exposed to ionizing radiation.


In some embodiments, the membrane system (or interference domain) is crosslinked by forming free radicals, which may include the use of ionizing radiation, thermal initiators, chemical initiators, photoinitiators (e.g., UV and visible light), and the like. Any suitable initiator or any suitable initiator system can be employed, for example, α-hydroxyketone, α-aminoketone, ammonium persulfate (APS), redox systems such as APS/bisulfite, or potassium permanganate. Suitable thermal initiators include but are not limited to potassium persulfate, ammonium persulfate, sodium persulfate, and mixtures thereof.


In embodiments wherein electron beam radiation is used to treat the membrane system (or interference domain), a preferred exposure time is from about 6k or 12 kGy to about 25 or 50 kGy, more preferably about 25 kGy. However, one skilled in the art appreciates that choice of molecular weight, composition of cellulosic derivative (or other polymer), and/or the thickness of the layer can affect the preferred exposure time of membrane to radiation. Preferably, the exposure is sufficient for substantially crosslinking the interference domain to form free radicals, but does not destroy or significantly break down the membrane or does not significantly damage the underlying electroactive surfaces.


In embodiments wherein UV radiation is employed to treat the membrane, UV rays from about 200 nm to about 400 nm are preferred; however values outside of this range can be employed in certain embodiments, dependent upon the cellulosic derivative and/or other polymer used.


In some embodiments, for example, wherein photoinitiators are employed to crosslink the interference domain, one or more additional domains can be provided adjacent to the interference domain for preventing delamination that may be caused by the crosslinking treatment. These additional domains can be “tie layers” (i.e., film layers that enhance adhesion of the interference domain to other domains of the membrane system). In one exemplary embodiment, a membrane system is formed that includes the following domains: resistance domain, enzyme domain, electrode domain, and cellulosic-based interference domain, wherein the electrode domain is configured to ensure adhesion between the enzyme domain and the interference domain. In embodiments wherein photoinitiators are employed to crosslink the interference domain, UV radiation of greater than about 290 nm is preferred. Additionally, from about 0.01 to about 1 wt % photoinitiator is preferred weight-to-weight with a preselected cellulosic polymer (e.g., cellulose acetate); however values outside of this range can be desirable dependent upon the cellulosic polymer selected.


In general, sterilization of the transcutaneous sensor can be completed after final assembly, utilizing methods such as electron beam radiation, gamma radiation, glutaraldehyde treatment, or the like. The sensor can be sterilized prior to or after packaging. In an alternative embodiment, one or more sensors can be sterilized using variable frequency microwave chamber(s), which can increase the speed and reduce the cost of the sterilization process. In another alternative embodiment, one or more sensors can be sterilized using ethylene oxide (EtO) gas sterilization, for example, by treating with 100% ethylene oxide, which can be used when the sensor electronics are not detachably connected to the sensor and/or when the sensor electronics must undergo a sterilization process. In one embodiment, one or more packaged sets of transcutaneous sensors (e.g., 1, 2, 3, 4, or 5 sensors or more) are sterilized simultaneously.


Mutarotase Enzyme


In some embodiments, mutarotase, an enzyme that converts α D-glucose to β D-glucose, is incorporated into the membrane system. Mutarotase can be incorporated into the enzyme domain and/or can be incorporated into another domain of the membrane system. In general, glucose exists in two distinct isomers, α and β, which are in equilibrium with one another in solution and in the blood or interstitial fluid. At equilibrium, a is present at a relative concentration of about 35.5% and β is present in the relative concentration of about 64.5% (see Okuda et. al., Anal Biochem. 1971 September; 43(1):312-5). Glucose oxidase, which is a conventional enzyme used to react with glucose in glucose sensors, reacts with p D-glucose and not with a D-glucose. Since only the p D-glucose isomer reacts with the glucose oxidase, errant readings may occur in a glucose sensor responsive to a shift of the equilibrium between the a D-glucose and the p D-glucose. Many compounds, such as calcium, can affect equilibrium shifts of a D-glucose and β D-glucose. For example, as disclosed in U.S. Pat. No. 3,964,974 to Banaugh et al., compounds that exert a mutarotation accelerating effect on a D-glucose include histidine, aspartic acid, imidazole, glutamic acid, a hydroxyl pyridine, and phosphate.


Accordingly, a shift in α D-glucose and β D-glucose equilibrium can cause a glucose sensor based on glucose oxidase to err high or low. To overcome the risks associated with errantly high or low sensor readings due to equilibrium shifts, the sensor of the preferred embodiments can be configured to measure total glucose in the host, including α D-glucose and β D-glucose by the incorporation of the mutarotase enzyme, which converts α D-glucose to β D-glucose.


Although sensors of some embodiments described herein include an interference domain in order to block or reduce one or more interferents, sensors with the membrane systems of the preferred embodiments, including an electrode domain 47, an enzyme domain 48, and a resistance domain 49, have been shown to inhibit ascorbate without an additional interference domain. Namely, the membrane system of the preferred embodiments, including an electrode domain 47, an enzyme domain 48, and a resistance domain 49, has been shown to be substantially non-responsive to ascorbate in physiologically acceptable ranges. While not wishing to be bound by theory, it is believed that the processing process of spraying the depositing the resistance domain by spray coating, as described herein, forms results in a structural morphology that is substantially resistance resistant to ascorbate.


Oxygen Conduit


As described above, certain sensors depend upon an enzyme within the membrane system through which the host's bodily fluid passes and in which the analyte (for example, glucose) within the bodily fluid reacts in the presence of a co-reactant (for example, oxygen) to generate a product. The product is then measured using electrochemical methods, and thus the output of an electrode system functions as a measure of the analyte. For example, when the sensor is a glucose oxidase based glucose sensor, the species measured at the working electrode is H2O2. An enzyme, glucose oxidase, catalyzes the conversion of oxygen and glucose to hydrogen peroxide and gluconate according to the following reaction:

Glucose+O2→Gluconate+H2O2


Because for each glucose molecule reacted there is a proportional change in the product, H2O2, one can monitor the change in H2O2 to determine glucose concentration. Oxidation of H2O2 by the working electrode is balanced by reduction of ambient oxygen, enzyme generated H2O2 and other reducible species at a counter electrode, for example. See Fraser. D. M., “An Introduction to In vivo Biosensing: Progress and Problems.” In “Biosensors and the Body.” D. M. Fraser, ed., 1997, pp. 1-56 John Wiley and Sons, New York)).


In vivo, glucose concentration is generally about one hundred times or more that of the oxygen concentration. Consequently, oxygen is a limiting reactant in the electrochemical reaction, and when insufficient oxygen is provided to the sensor, the sensor is unable to accurately measure glucose concentration. Thus, depressed sensor function or inaccuracy is believed to be a result of problems in availability of oxygen to the enzyme and/or electroactive surface(s).


Accordingly, in an alternative embodiment, an oxygen conduit (for example, a high oxygen solubility domain formed from silicone or fluorochemicals) is provided that extends from the ex vivo portion of the sensor to the in vivo portion of the sensor to increase oxygen availability to the enzyme. The oxygen conduit can be formed as a part of the coating (insulating) material or can be a separate conduit associated with the assembly of wires that forms the sensor.


Porous Biointerface Materials


In alternative embodiments, the distal portion 42 includes a porous material disposed over some portion thereof, which modifies the host's tissue response to the sensor. In some embodiments, the porous material surrounding the sensor advantageously enhances and extends sensor performance and lifetime in the short term by slowing or reducing cellular migration to the sensor and associated degradation that would otherwise be caused by cellular invasion if the sensor were directly exposed to the in vivo environment. Alternatively, the porous material can provide stabilization of the sensor via tissue ingrowth into the porous material in the long term. Suitable porous materials include silicone, polytetrafluoroethylene, expanded polytetrafluoroethylene, polyethylene-co-tetrafluoroethylene, polyolefin, polyester, polycarbonate, biostable polytetrafluoroethylene, homopolymers, copolymers, terpolymers of polyurethanes, polypropylene (PP), polyvinylchloride (PVC), polyvinylidene fluoride (PVDF), polyvinyl alcohol (PVA), polybutylene terephthalate (PBT), polymethylmethacrylate (PMMA), polyether ether ketone (PEEK), polyamides, polyurethanes, cellulosic polymers, polysulfones and block copolymers thereof including, for example, di-block, tri-block, alternating, random and graft copolymers, as well as metals, ceramics, cellulose, hydrogel polymers, poly (2-hydroxyethyl methacrylate, pHEMA), hydroxyethyl methacrylate. (HEMA), polyacrylonitrile-polyvinyl chloride (PAN-PVC), high density polyethylene, acrylic copolymers, nylon, polyvinyl difluoride, polyanhydrides, poly(l-lysine), poly (L-lactic acid), hydroxyethylmethacrylate, hydroxyapeptite, alumina, zirconia, carbon fiber, aluminum, calcium phosphate, titanium, titanium alloy, nintinol, stainless steel, and CoCr alloy, or the like, such as are described in U.S. Publication No. US-2005-0031689-A1 and U.S. Publication No. US-2005-0112169-A1.


In some embodiments, the porous material surrounding the sensor provides unique advantages in the short term (e.g., one to 30 days) that can be used to enhance and extend sensor performance and lifetime. However, such materials can also provide advantages in the long term too (e.g., greater than 30 days) and thus are useful in the long term sensors described below. Particularly, the in vivo portion of the sensor (the portion of the sensor that is implanted into the host's tissue) is encased (partially or fully) in a porous material. The porous material can be wrapped around the sensor (for example, by wrapping the porous material around the sensor or by inserting the sensor into a section of porous material sized to receive the sensor). Alternately, the porous material can be deposited on the sensor (for example, by electrospinning of a polymer directly thereon). In yet other alternative embodiments, the sensor is inserted into a selected section of porous biomaterial. Other methods for surrounding the in vivo portion of the sensor with a porous material can also be used as is appreciated by one skilled in the art.


The porous material surrounding the sensor advantageously slows or reduces cellular migration to the sensor and associated degradation that would otherwise be caused by cellular invasion if the sensor were directly exposed to the in vivo environment. Namely, the porous material provides a barrier that makes the migration of cells towards the sensor more tortuous and therefore slower (providing short term advantages). It is believed that this reduces or slows the sensitivity loss normally observed in a short-term sensor over time.


In an embodiment wherein the porous material is a high oxygen solubility material, such as porous silicone, the high oxygen solubility porous material surrounds some of or the entire in vivo portion 42 of the sensor. High oxygen solubility materials are materials that dynamically retain a high availability of oxygen that can be used to compensate for the local oxygen deficit during times of transient ischemia (e.g., silicone and fluorocarbons). It is believed that some signal noise normally seen by a conventional sensor can be attributed to an oxygen deficit. In one exemplary embodiment, porous silicone surrounds the sensor and thereby effectively increases the concentration of oxygen local (proximal) to the sensor. Thus, an increase in oxygen availability proximal to the sensor as achieved by this embodiment ensures that an excess of oxygen over glucose is provided to the sensor, thereby reducing the likelihood of oxygen limited reactions therein. Accordingly, by providing a high oxygen solubility material (e.g., porous silicone) surrounding the in vivo portion of the sensor, it is believed that increased oxygen availability, reduced signal noise, longevity, and ultimately enhanced sensor performance can be achieved.


Bioactive Agents


In some alternative embodiments, a bioactive agent is incorporated into the above described porous material and/or membrane system, which diffuses out into the environment adjacent to the sensing region, such as is described in U.S. Publication No. US-2005-0031689-A1. Additionally or alternately, a bioactive agent can be administered locally at the exit-site or implantation-site. Suitable bioactive agents are those that modify the host's tissue response to the sensor, for example anti-inflammatory agents, anti-infective agents, anesthetics, inflammatory agents, growth factors, immunosuppressive agents, antiplatelet agents, anti-coagulants, anti-proliferates, ACE inhibitors, cytotoxic agents, anti-barrier cell compounds, vascularization-inducing compounds, anti-sense molecules, or mixtures thereof, such as are described in more detail in co-pending U.S. Patent Publication No. US-2005-0031689-A1.


In embodiments wherein the porous material is designed to enhance short-term (e.g., from about 1 to about 30 days) lifetime or performance of the sensor, a suitable bioactive agent can be chosen to ensure that tissue ingrowth does not substantially occur within the pores of the porous material. Namely, by providing a tissue modifying bioactive agent, such as an anti-inflammatory agent (for example, Dexamethasone), substantially tissue ingrowth can be inhibited, at least in the short term, in order to maintain sufficient glucose transport through the pores of the porous material to maintain a stable sensitivity.


In embodiments wherein the porous material is designed to enhance long-term (e.g., from about a day to about a year or more) lifetime or performance of the sensor, a suitable bioactive agent, such as a vascularization-inducing compound or anti-barrier cell compound, can be chosen to encourage tissue ingrowth without barrier cell formation.


In some alternative embodiments, the in vivo portion of the sensor is designed with porosity therethrough, for example, a design wherein the sensor wires are configured in a mesh, loose helix configuration (namely, with spaces between the wires), or with micro-fabricated holes therethrough. Porosity within the sensor modifies the host's tissue response to the sensor, because tissue ingrowth into and/or through the in vivo portion of the sensor increases stability of the sensor and/or improves host acceptance of the sensor, thereby extending the lifetime of the sensor in vivo.


Sensor Manufacture


In some embodiments, the sensor is manufactured partially or wholly using a continuous reel-to-reel process, wherein one or more manufacturing steps are automated. In such embodiments, a manufacturing process can be provided substantially without the need for manual mounting and fixing steps and substantially without the need human interaction. A process can be utilized wherein a plurality of sensors of the preferred embodiments, including the electrodes, insulator, and membrane system, are continuously manufactured in a semi-automated or automated process.


In one embodiment, a plurality of twisted pairs is continuously formed into a coil, wherein a working electrode is coated with an insulator material around which a plurality of reference electrodes is wound. The plurality of twisted pairs are preferably indexed and subsequently moved from one station to the next whereby the membrane system is serially deposited according to the preferred embodiments. Preferably, the coil is continuous and remains as such during the entire sensor fabrication process, including winding of the electrodes, insulator application, and membrane coating processes. After drying of the membrane system, each individual sensor is cut from the continuous coil.


A continuous reel-to-reel process for manufacturing the sensor eliminates possible sensor damage due to handling by eliminating handling steps, and provides faster manufacturing due to faster trouble shooting by isolation when a product fails. Additionally, a process run can be facilitated because of elimination of steps that would otherwise be required (e.g., steps in a manual manufacturing process). Finally, increased or improved product consistency due to consistent processes within a controlled environment can be achieved in a machine or robot driven operation.


In certain embodiments, vapor deposition (e.g., physical vapor deposition) is utilized to deposit one or more of the membrane domains onto the sensor. Vapor deposition can be used to coat one or more insulating layers onto the electrodes and one or more of the domains of the membrane system onto the electrochemically reactive surfaces. The vapor deposition process can be a part of a continuous manufacturing process, for example, a semi-automated or fully-automated manufacturing process. Physical vapor deposition processes are generally preferred. In such physical vapor deposition processes in the gas phase for forming a thin film, source material is physically transferred in a vacuum to the substrate without any chemical reaction(s) involved. Physical vapor deposition processes include evaporation (e.g., by thermal or e-beam) and sputtering processes. In alternative embodiments, chemical vapor deposition can be used. In chemical vapor deposition processes for depositing a thin film, the substrate is exposed to one or more volatile precursors, which react and/or decompose on the substrate surface to produce the desired deposit. Advantageously, vapor deposition processes can be implemented to provide high production throughput of membrane deposition processes (e.g., deposition on at least about 20 to about 200 or more electrodes per chamber), greater consistency of the membrane on each sensor, and increased uniformity of sensor performance.


Applicator



FIG. 7 is an exploded side view of an applicator, showing the components that enable sensor and needle insertion. In this embodiment, the applicator 12 includes an applicator body 18 that aides in aligning and guiding the applicator components. Preferably, the applicator body 18 includes an applicator body base 60 that matingly engages the mounting unit 14 and an applicator body cap 62 that enables appropriate relationships (for example, stops) between the applicator components.


The guide tube subassembly 20 includes a guide tube carrier 64 and a guide tube 66. In some embodiments, the guide tube is a cannula. The guide tube carrier 64 slides along the applicator body 18 and maintains the appropriate relative position of the guide tube 66 during insertion and subsequent retraction. For example, prior to and during insertion of the sensor, the guide tube 66 extends through the contact subassembly 26 to maintain an opening that enables easy insertion of the needle therethrough (see FIGS. 8A to 8D). During retraction of the sensor, the guide tube subassembly 20 is pulled back, engaging with and causing the needle and associated moving components to retract back into the applicator 12 (See FIGS. 8C and 8D). In some embodiments, a lubricant (e.g., petroleum jelly) is placed within the sealing member 36 of the contact subassembly such that it surrounds the guide tube (e.g., cannula), thereby allowing the guide tube to easily retract back into the applicator, for example, without causing compression or deformation of the sealing member 36.


A needle subassembly 68 is provided that includes a needle carrier 70 and needle 72. The needle carrier 70 cooperates with the other applicator components and carries the needle 72 between its extended and retracted positions. The needle can be of any appropriate size that can encompass the sensor 32 and aid in its insertion into the host. Preferred sizes include from about 32 gauge or less to about 18 gauge or more, more preferably from about 28 gauge to about 25 gauge, to provide a comfortable insertion for the host. Referring to the inner diameter of the needle, approximately 0.006 inches to approximately 0.023 inches is preferable, and 0.013 inches is most preferable. The needle carrier 70 is configured to engage with the guide tube carrier 64, while the needle 72 is configured to slidably nest within the guide tube 66, which allows for easy guided insertion (and retraction) of the needle through the contact subassembly 26.


A push rod subassembly 74 is provided that includes a push rod carrier 76 and a push rod 78. The push rod carrier 76 cooperates with other applicator components to ensure that the sensor is properly inserted into the host's skin, namely the push rod carrier 76 carries the push rod 78 between its extended and retracted positions. In this embodiment, the push rod 78 is configured to slidably nest within the needle 72, which allows for the sensor 32 to be pushed (released) from the needle 72 upon retraction of the needle, which is described in more detail with reference to FIGS. 8A through 8D. In some embodiments, a slight bend or serpentine shape is designed into or allowed in the sensor in order to maintain the sensor within the needle by interference. While not wishing to be bound by theory, it is believed that a slight friction fit of the sensor within the needle minimizes motion of the sensor during withdrawal of the needle and maintains the sensor within the needle prior to withdrawal of the needle.


A plunger subassembly 22 is provided that includes a plunger 80 and plunger cap 82. The plunger subassembly 22 cooperates with other applicators components to ensure proper insertion and subsequent retraction of the applicator components. In this embodiment, the plunger 80 is configured to engage with the push rod to ensure the sensor remains extended (namely, in the host) during retraction, such as is described in more detail with reference to FIG. 8C.


Sensor Insertion



FIGS. 8A through 8D are schematic side cross-sectional views that illustrate the applicator components and their cooperating relationships at various stages of sensor insertion. FIG. 8A illustrates the needle and sensor loaded prior to sensor insertion. FIG. 8B illustrates the needle and sensor after sensor insertion. FIG. 8C illustrates the sensor and needle during needle retraction. FIG. 8D illustrates the sensor remaining within the contact subassembly after needle retraction. Although the embodiments described herein suggest manual insertion and/or retraction of the various components, automation of one or more of the stages can also be employed. For example, spring-loaded mechanisms that can be triggered to automatically insert and/or retract the sensor, needle, or other cooperative applicator components can be implemented.


Referring to FIG. 8A, the sensor 32 is shown disposed within the needle 72, which is disposed within the guide tube 66. In this embodiment, the guide tube 66 is provided to maintain an opening within the contact subassembly 26 and/or contacts 28 to provide minimal friction between the needle 72 and the contact subassembly 26 and/or contacts 28 during insertion and retraction of the needle 72. However, the guide tube is an optional component, which can be advantageous in some embodiments wherein the contact subassembly 26 and/or the contacts 28 are formed from an elastomer or other material with a relatively high friction coefficient, and which can be omitted in other embodiments wherein the contact subassembly 26 and or the contacts 28 are formed from a material with a relatively low friction coefficient (for example, hard plastic or metal). A guide tube, or the like, can be preferred in embodiments wherein the contact subassembly 26 and/or the contacts 28 are formed from a material designed to frictionally hold the sensor 32 (see FIG. 8D), for example, by the relaxing characteristics of an elastomer, or the like. In these embodiments, the guide tube is provided to ease insertion of the needle through the contacts, while allowing for a frictional hold of the contacts on the sensor 32 upon subsequent needle retraction. Stabilization of the sensor in or on the contacts 28 is described in more detail with reference to FIG. 8D and following. Although FIG. 8A illustrates the needle and sensor inserted into the contacts subassembly as the initial loaded configuration, alternative embodiments contemplate a step of loading the needle through the guide tube 66 and/or contacts 28 prior to sensor insertion.


Referring to FIG. 8B, the sensor 32 and needle 72 are shown in an extended position. In this stage, the pushrod 78 has been forced to a forward position, for example by pushing on the plunger shown in FIG. 7, or the like. The plunger 22 (FIG. 7) is designed to cooperate with other of the applicator components to ensure that sensor 32 and the needle 72 extend together to a forward position (as shown); namely, the push rod 78 is designed to cooperate with other of the applicator components to ensure that the sensor 32 maintains the forward position simultaneously within the needle 72.


Referring to FIG. 8C, the needle 72 is shown during the retraction process. In this stage, the push rod 78 is held in its extended (forward) position in order to maintain the sensor 32 in its extended (forward) position until the needle 72 has substantially fully retracted from the contacts 28. Simultaneously, the cooperating applicator components retract the needle 72 and guide tube 66 backward by a pulling motion (manual or automated) thereon. In preferred embodiments, the guide tube carrier 64 (FIG. 7) engages with cooperating applicator components such that a backward (retraction) motion applied to the guide tube carrier retracts the needle 72 and guide tube 66, without (initially) retracting the push rod 78. In an alternative embodiment, the push rod 78 can be omitted and the sensor 32 held it its forward position by a cam, elastomer, or the like, which is in contact with a portion of the sensor while the needle moves over another portion of the sensor. One or more slots can be cut in the needle to maintain contact with the sensor during needle retraction.


Referring to FIG. 8D, the needle 72, guide tube 66, and push rod 78 are all retracted from contact subassembly 26, leaving the sensor 32 disposed therein. The cooperating applicator components are designed such that when the needle 72 has substantially cleared from the contacts 28 and/or contact subassembly 26, the push rod 78 is retracted along with the needle 72 and guide tube 66. The applicator 12 can then be released (manually or automatically) from the contacts 28, such as is described in more detail elsewhere herein, for example with reference to FIGS. 9D and 10A.


The preferred embodiments are generally designed with elastomeric contacts to ensure a retention force that retains the sensor 32 within the mounting unit 14 and to ensure stable electrical connection of the sensor 32 and its associated contacts 28. Although the illustrated embodiments and associated text describe the sensor 32 extending through the contacts 28 to form a friction fit therein, a variety of alternatives are contemplated. In one alternative embodiment, the sensor is configured to be disposed adjacent to the contacts (rather than between the contacts). The contacts can be constructed in a variety of known configurations, for example, metallic contacts, cantilevered fingers, pogo pins, or the like, which are configured to press against the sensor after needle retraction.


It is generally preferred that a contact 28 is formed from a material with a durometer hardness of from about 5 to about 80 Shore A, more preferably from about 10 to about 50 Shore A, and even more preferably from about 20 to about 50 Shore A. In one implementation of a transcutaneous analyte sensor as described with reference to the preferred embodiments, the contact 28 is formed from a material with a durometer hardness of about 20 Shore A to maximize conformance (e.g., compression) of the contact around the sensor and/or within the sealing member. In another implementation of a transcutaneous analyte sensor as described with reference to the preferred embodiments, the contact 28 is formed from a material with a durometer hardness of about 50 Shore A to increase the strength of the contact 28 (e.g., increase resistance to compression). While a few examples have been provided above, one skilled in the art will appreciate that higher or lower durometer hardness sealing materials can also be advantageously employed.


In some embodiments, the durometer hardness of the elastomeric contacts 28 is higher than the durometer hardness of the sealing member 36. In one example, the durometer hardness of the contacts is about 50 Shore A and the durometer hardness of the sealing member is about 20 Shore A; however, a variety of durometer hardness materials within the preferred range (typically, from about 5 Shore A to about 80 Shore A) can be chosen. In these embodiments, the higher durometer hardness contacts generally provide greater stability while the lower durometer hardness sealing member generally provides superior compression and/or seal around the contacts.


In some embodiments, the durometer hardness of the sealing member 36 is higher than the durometer hardness of the elastomeric contacts 28. In one example, the durometer hardness of the sealing member is about 50 Shore A and the durometer hardness of the contacts is about 20 Shore A, however a variety of durometer hardness materials within the preferred range (typically, from about 5 Shore A to about 80 Shore A) can be chosen. In these embodiments, the higher durometer hardness sealing member provides greater stability while the lower durometer hardness contacts provide superior compression and/or seal.


The illustrated embodiments are designed with coaxial contacts 28; namely, the contacts 28 are configured to contact the working and reference electrodes 44, 46 axially along the distal portion 42 of the sensor 32 (see FIG. 6A). As shown in FIG. 6A, the working electrode 44 extends farther than the reference electrode 46, which allows coaxial connection of the electrodes 44, 46 with the contacts 28 at locations spaced along the distal portion of the sensor (see also FIGS. 10B and 11B). Although the illustrated embodiments employ a coaxial design, other designs are contemplated within the scope of the preferred embodiments. For example, the reference electrode can be positioned substantially adjacent to (but spaced apart from) the working electrode at the distal portion of the sensor. In this way, the contacts 28 can be designed side-by-side rather than co-axially along the axis of the sensor.



FIG. 9A is a perspective view of an applicator and mounting unit in one embodiment including a safety latch mechanism 84. The safety latch mechanism 84 is configured to lock the plunger subassembly 22 in a stationary position such that it cannot be accidentally pushed prior to release of the safety latch mechanism. In this embodiment, the sensor system 10 is preferably packaged (e.g., shipped) in this locked configuration, wherein the safety latch mechanism 84 holds the plunger subassembly 22 in its extended position, such that the sensor 32 cannot be prematurely inserted (e.g., accidentally released). The safety latch mechanism 84 is configured such that a pulling force shown in the direction of the arrow (see FIG. 9A) releases the lock of the safety latch mechanism on the plunger subassembly, thereby allowing sensor insertion. Although one safety latch mechanism that locks the plunger subassembly is illustrated and described herein, a variety of safety latch mechanism configurations that lock the sensor to prevent it from prematurely releasing (i.e., that lock the sensor prior to release of the safety latch mechanism) are contemplated, as can be appreciated by one skilled in the art, and fall within the scope of the preferred embodiments.



FIG. 9A additionally illustrates a force-locking mechanism 86 included in certain alternative embodiments of the sensor system, wherein the force-locking mechanism 86 is configured to ensure a proper mate between the electronics unit 16 and the mounting unit 14 (see FIG. 13A, for example). In embodiments wherein a seal is formed between the mounting unit and the electronics unit, as described in more detail elsewhere herein, an appropriate force may be required to ensure a seal has sufficiently formed therebetween; in some circumstances, it can be advantageous to ensure the electronics unit has been properly mated (e.g., snap-fit or sealingly mated) to the mounting unit. Accordingly, upon release of the applicator 12 from the mounting unit 14 (after sensor insertion), and after insertion of the electronics unit 16 into the mounting unit 14, the force-locking mechanism 86 allows the user to ensure a proper mate and/or seal therebetween. In practice, a user pivots (e.g., lifts or twists) the force-locking mechanism such that it provides force on the electronics unit 16 by pulling up on the circular tab illustrated in FIG. 9A; the force-locking mechanism is preferably released thereafter. Although one system and one method for providing a secure and/or sealing fit between the electronics unit and the mounting unit are illustrated, various other force-locking mechanisms can be employed that utilize a variety of systems and methods for providing a secure and/or sealing fit between the electronics unit and the mounting unit (housing).



FIGS. 9B to 9D are side views of an applicator and mounting unit in one embodiment, showing various stages of sensor insertion. FIG. 9B is a side view of the applicator matingly engaged to the mounting unit prior to sensor insertion. FIG. 9C is a side view of the mounting unit and applicator after the plunger subassembly has been pushed, extending the needle and sensor from the mounting unit (namely, through the host's skin). FIG. 9D is a side view of the mounting unit and applicator after the guide tube subassembly has been retracted, retracting the needle back into the applicator. Although the drawings and associated text illustrate and describe embodiments wherein the applicator is designed for manual insertion and/or retraction, automated insertion and/or retraction of the sensor/needle, for example, using spring-loaded components, can alternatively be employed.


The preferred embodiments advantageously provide a system and method for easy insertion of the sensor and subsequent retraction of the needle in a single push-pull motion. Because of the mechanical latching system of the applicator, the user provides a continuous force on the plunger cap 82 and guide tube carrier 64 that inserts and retracts the needle in a continuous motion. When a user grips the applicator, his or her fingers grasp the guide tube carrier 64 while his or her thumb (or another finger) is positioned on the plunger cap 82. The user squeezes his or her fingers and thumb together continuously, which causes the needle to insert (as the plunger slides forward) and subsequently retract (as the guide tube carrier slides backward) due to the system of latches located within the applicator (FIGS. 7 to 9) without any necessary change of grip or force, leaving the sensor implanted in the host. In some embodiments, a continuous torque, when the applicator components are configured to rotatingly engage one another, can replace the continuous force. Some prior art sensors, in contrast to the sensors of the preferred embodiments, suffer from complex, multi-step, or multi-component insertion and retraction steps to insert and remove the needle from the sensor system.



FIG. 9B shows the mounting unit and applicator in the ready position. The sensor system can be shipped in this configuration, or the user can be instructed to mate the applicator 12 with the mounting unit 14 prior to sensor insertion. The insertion angle α is preferably fixed by the mating engagement of the applicator 12. In the illustrated embodiment, the insertion angle α is fixed in the applicator 12 by the angle of the applicator body base 60 with the shaft of the applicator body 18. However, a variety of systems and methods of ensuring proper placement can be implemented. Proper placement ensures that at least a portion of the sensor 32 extends below the dermis of the host upon insertion. In alternative embodiments, the sensor system 10 is designed with a variety of adjustable insertion angles. A variety of insertion angles can be advantageous to accommodate a variety of insertion locations and/or individual dermis configurations (for example, thickness of the dermis). In preferred embodiments, the insertion angle α is from about 0 to about 90 degrees, more preferably from about 30 to about 60 degrees, and even more preferably about 45 degrees.


In practice, the mounting unit is placed at an appropriate location on the host's skin, for example, the skin of the arm, thigh, or abdomen. Thus, removing the backing layer 9 from the adhesive pad 8 and pressing the base portion of the mounting unit on the skin adheres the mounting unit to the host's skin.



FIG. 9C shows the mounting unit and applicator after the needle 72 has been extended from the mounting unit 14 (namely, inserted into the host) by pushing the push rod subassembly 22 into the applicator 12. In this position, the sensor 32 is disposed within the needle 72 (namely, in position within the host), and held by the cooperating applicator components. In alternative embodiments, the mounting unit and/or applicator can be configured with the needle/sensor initially extended. In this way, the mechanical design can be simplified and the plunger-assisted insertion step can be eliminated or modified. The needle can be simply inserted by a manual force to puncture the host's skin, and only one (pulling) step is required on the applicator, which removes the needle from the host's skin.



FIG. 9D shows the mounting unit and applicator after the needle 72 has been retracted into the applicator 12, exposing the sensor 32 to the host's tissue. During needle retraction, the push rod subassembly maintains the sensor in its extended position (namely, within the host). In preferred embodiments, retraction of the needle irreversibly locks the needle within the applicator so that it cannot be accidentally and/or intentionally released, reinserted, or reused. The applicator is preferably configured as a disposable device to reduce or eliminate a possibility of exposure of the needle after insertion into the host. However a reusable or reloadable applicator is also contemplated in some alternative embodiments. After needle retraction, the applicator 12 can be released from the mounting unit, for example, by pressing the release latch(es) 30, and the applicator disposed of appropriately. In alternative embodiments, other mating and release configurations can be implemented between the mounting unit and the applicator, or the applicator can automatically release from the mounting unit after sensor insertion and subsequent needle retraction. In one alternative embodiment, a retention hold (e.g., ball and detent configuration) holds and releases the electronics unit (or applicator).


In one alternative embodiment, the mounting unit is configured to releasably mate with the applicator and electronics unit in a manner such that when the applicator is releasably mated to the mounting unit (e.g., after sensor insertion), the electronics unit is configured to slide into the mounting unit, thereby triggering release of the applicator and simultaneous mating of the electronics unit to the mounting unit. Cooperating mechanical components, for example, sliding ball and detent type configurations, can be used to accomplish the simultaneous mating of electronics unit and release of the applicator.



FIGS. 9E to 9G are perspective views of a sensor system 310 of an alternative embodiment, including an applicator 312, electronics unit 316, and mounting unit 314, showing various stages of applicator release and/or electronic unit mating. FIG. 9E is a perspective view of the applicator matingly engaged to the mounting unit after sensor insertion. FIG. 9F is a perspective view of the mounting unit and applicator matingly engaged while the electronics unit is slidingly inserted into the mounting unit. FIG. 9G is a perspective view of the electronics unit matingly engaged with the mounting unit after the applicator has been released.


In general, the sensor system 310 comprises a sensor adapted for transcutaneous insertion into a host's skin; a housing 314 adapted for placement adjacent to the host's skin; an electronics unit 316 releasably attachable to the housing; and an applicator 312 configured to insert the sensor through the housing 314 and into the skin of the host, wherein the applicator 312 is adapted to releasably mate with the housing 314, and wherein the system 310 is configured to release the applicator 312 from the housing when the electronics unit 316 is attached to the housing 314.



FIG. 9E shows the sensor system 310 after the sensor has been inserted and prior to release of the applicator 312. In this embodiment, the electronics unit 316 is designed to slide into the mounting unit 314. Preferably, the electronics unit 316 is configured and arranged to slide into the mounting unit 314 in only one orientation. In the illustrated embodiment, the insertion end is slightly tapered and dovetailed in order to guide insertion of the electronics unit 316 into the housing 314; however other self-alignment configurations are possible. In this way, the electronics unit 316 self-aligns and orients the electronics unit 316 in the housing, ensuring a proper fit and a secure electronic connection with the sensor.



FIG. 9F shows the sensor system 310 after the electronics unit 316 has been inserted therein. Preferably, the electronic unit 316 slide-fits into the mounting unit. In some embodiments, the sensor system 310 can be designed to allow the electronics unit 316 to be attached to the mounting unit 314 (i.e., operably connected to the sensor) before the sensor system 310 is affixed to the host. Advantageously, this design provides mechanical stability for the sensor during transmitter insertion.



FIG. 9G shows the sensor system 310 upon release of the applicator 312 from the mounting unit 314 and electronics unit 316. In this embodiment, the sensor system 310 is configured such that mating the electronics unit to the mounting unit triggers the release of the applicator 312 from the mounting unit 314.


Thus, the above described sensor system 310, also referred to as the slide-in system, allows for self-alignment of the electronics unit, creates an improved seal around the contacts due to greater holding force, provides mechanical stability for the sensor during insertion of the electronics unit, and causes automatic release of the applicator and simultaneous lock of the electronics unit into the mounting unit.


Although the overall design of the sensor system 10 results in a miniaturized volume as compared to numerous conventional devices, as described in more detail below; the sensor system 310 further enables a reduction in volume, as compared to, for example, the sensor system 10 described above.



FIGS. 9H and 9I are comparative top views of the sensor system shown in the alternative embodiment illustrated in FIGS. 9E to 9G and compared to the embodiments illustrated elsewhere (see FIGS. 1 to 3 and 10 to 12, for example). Namely, the alternative embodiment described with reference to FIGS. 9E to 9G further enables reduced size (e.g., mass, volume, and the like) of the device as compared to certain other devices. It has been discovered that the size (including volume and/or surface area) of the device can affect the function of the device. For example, motion of the mounting unit/electronics unit caused by external influences (e.g., bumping or other movement on the skin) is translated to the sensor in vivo, causing motion artifact (e.g., an effect on the signal, or the like). Accordingly, by enabling a reduction of size, a more stable signal with overall improved patient comfort can be achieved.


Accordingly, slide-in system 310 described herein, including the systems and methods for inserting the sensor and connecting the electronics unit to the mounting unit, enables the mounting unit 316/electronics unit 314 subassembly to have a volume of less than about 10 cm3, more preferably less than about 8 cm3, and even more preferably less than about 6 cm3, 5 cm3, or 4 cm3 or less. In general, the mounting unit 316/electronics unit 314 subassembly comprises a first major surface and a second major surface opposite the first major surface. The first and second major surfaces together preferably account for at least about 50% of the surface area of the device; the first and second major surfaces each define a surface area, wherein the surface area of each major surface is less than or equal to about 10 cm2, preferably less than or equal to about 8 cm2, and more preferably less than or equal to about 6.5 cm2, 6 cm2, 5.5 cm2, 5 cm2, 4.5 cm2, or 4 cm2 or less. Typically, the mounting unit 316/electronics unit 314 subassembly has a length 320 of less than about 40 mm by a width 322 of less than about 20 mm and a thickness of less than about 10 mm, and more preferably a length 320 less than or equal to about 35 mm by a width 322 less than or equal to about 18 mm by a thickness of less than or equal to about 9 mm.


In some embodiments, the mounting unit 14/electronics unit 16 assembly has the following dimensional properties: preferably a length of about 6 cm or less, more preferably about 5 cm or less, more preferably still about 4.6 cm or less, even more preferably 4 cm or less, and most preferably about 3 cm or less; preferably a width of about 5 cm or less, more preferably about 4 cm or less, even more preferably 3 cm or less, even more preferably still about 2 cm or less, and most preferably about 1.5 cm or less; and/or preferably a thickness of about 2 cm or less, more preferably about 1.3 cm or less, more preferably still about 1 cm or less, even more preferably still about 0.7 cm or less, and most preferably about 0.5 cm or less. The mounting unit 14/electronics unit 16 assembly preferably has a volume of about 20 cm3 or less, more preferably about 10 cm3 or less, more preferably still about 5 cm3 or less, and most preferably about 3 cm3 or less; and preferably weighs 12 g or less, more preferably about 9 g or less, and most preferably about 6 g or less, although in some embodiments the electronics unit may weigh more than about 12 g, e.g., up to about 25 g, 45 g, or 90 g.


In some embodiments, the sensor 32 exits the base of the mounting unit 14 at a location distant from an edge of the base. In some embodiments, the sensor 32 exits the base of the mounting unit 14 at a location substantially closer to the center than the edges thereof. While not wishing to be bound by theory, it is believed that by providing an exit port for the sensor 32 located away from the edges, the sensor 32 can be protected from motion between the body and the mounting unit, snagging of the sensor by an external source, and/or environmental contaminants (e.g., microorganisms) that can migrate under the edges of the mounting unit. In some embodiments, the sensor exits the mounting unit away from an outer edge of the device.


In some alternative embodiments, however, the sensor exits the mounting unit 14 at an edge or near an edge of the device. In some embodiments, the mounting unit is configured such that the exit port (location) of the sensor is adjustable; thus, in embodiments wherein the depth of the sensor insertion is adjustable, six-degrees of freedom can thereby be provided.


Extensible Adhesive Pad


In certain embodiments, an adhesive pad is used with the sensor system. A variety of design parameters are desirable when choosing an adhesive pad for the mounting unit. For example: 1) the adhesive pad can be strong enough to maintain full contact at all times and during all movements (devices that release even slightly from the skin have a greater risk of contamination and infection), 2) the adhesive pad can be waterproof or water permeable such that the host can wear the device even while heavily perspiring, showering, or even swimming in some cases, 3) the adhesive pad can be flexible enough to withstand linear and rotational forces due to host movements, 4) the adhesive pad can be comfortable for the host, 5) the adhesive pad can be easily releasable to minimize host pain, 6) and/or the adhesive pad can be easily releasable so as to protect the sensor during release. Unfortunately, these design parameters are difficult to simultaneously satisfy using known adhesive pads, for example, strong medical adhesive pads are available but are usually non-precise (for example, requiring significant “ripping” force during release) and can be painful during release due to the strength of their adhesion.


Therefore, the preferred embodiments provide an adhesive pad 8′ for mounting the mounting unit onto the host, including a sufficiently strong medical adhesive pad that satisfies one or more strength and flexibility requirements described above, and further provides a for easy, precise and pain-free release from the host's skin. FIG. 10A is a side view of the sensor assembly, illustrating the sensor implanted into the host with mounting unit adhered to the host's skin via an adhesive pad in one embodiment. Namely, the adhesive pad 8′ is formed from an extensible material that can be removed easily from the host's skin by stretching it lengthwise in a direction substantially parallel to (or up to about 35 degrees from) the plane of the skin. It is believed that this easy, precise, and painless removal is a function of both the high extensibility and easy stretchability of the adhesive pad.


In one embodiment, the extensible adhesive pad includes a polymeric foam layer or is formed from adhesive pad foam. It is believed that the conformability and resiliency of foam aids in conformation to the skin and flexibility during movement of the skin. In another embodiment, a stretchable solid adhesive pad, such as a rubber-based or an acrylate-based solid adhesive pad can be used. In another embodiment, the adhesive pad comprises a film, which can aid in increasing load bearing strength and rupture strength of the adhesive pad



FIGS. 10B to 10C illustrate initial and continued release of the mounting unit from the host's skin by stretching the extensible adhesive pad in one embodiment. To release the device, the backing adhesive pad is pulled in a direction substantially parallel to (or up to about 35 degrees from) the plane of the device. Simultaneously, the extensible adhesive pad stretches and releases from the skin in a relatively easy and painless manner.


In one implementation, the mounting unit is bonded to the host's skin via a single layer of extensible adhesive pad 8′, which is illustrated in FIGS. 10A to 10C. The extensible adhesive pad includes a substantially non-extensible pull-tab 52, which can include a light adhesive pad layer that allows it to be held on the mounting unit 14 prior to release. Additionally, the adhesive pad can further include a substantially non-extensible holding tab 54, which remains attached to the mounting unit during release stretching to discourage complete and/or uncontrolled release of the mounting unit from the skin.


In one alternative implementation, the adhesive pad 8′ includes two-sides, including the extensible adhesive pad and a backing adhesive pad (not shown). In this embodiment, the backing adhesive pad is bonded to the mounting unit's back surface 25 while the extensible adhesive pad 8′ is bonded to the host's skin. Both adhesive pads provide sufficient strength, flexibility, and waterproof or water permeable characteristics appropriate for their respective surface adhesion. In some embodiments, the backing and extensible adhesive pads are particularly designed with an optimized bond for their respective bonding surfaces (namely, the mounting unit and the skin).


In another alternative implementation, the adhesive pad 8′ includes a double-sided extensible adhesive pad surrounding a middle layer or backing layer (not shown). The backing layer can comprise a conventional backing film or can be formed from foam to enhance comfort, conformability, and flexibility. Preferably, each side of the double-sided adhesive pad is respectively designed for appropriate bonding surface (namely, the mounting unit and skin). A variety of alternative stretch-release configurations are possible. Controlled release of one or both sides of the adhesive pad can be facilitated by the relative lengths of each adhesive pad side, by incorporation of a non-adhesive pad zone, or the like.



FIGS. 11A and 11B are perspective and side cross-sectional views, respectively, of the mounting unit immediately following sensor insertion and release of the applicator from the mounting unit. In one embodiment, such as illustrated in FIGS. 11A and 11B, the contact subassembly 26 is held in its insertion position, substantially at the insertion angle α of the sensor. Maintaining the contact subassembly 26 at the insertion angle α during insertion enables the sensor 32 to be easily inserted straight through the contact subassembly 26. The contact subassembly 26 further includes a hinge 38 that allows movement of the contact subassembly 26 from an angled to a flat position. The term “hinge,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, a mechanism that allows articulation of two or more parts or portions of a device. The term is broad enough to include a sliding hinge, for example, a ball and detent type hinging mechanism.


Although the illustrated embodiments describe a fixed insertion angle designed into the applicator, alternative embodiments can design the insertion angle into other components of the system. For example, the insertion angle can be designed into the attachment of the applicator with the mounting unit, or the like. In some alternative embodiments, a variety of adjustable insertion angles can be designed into the system to provide for a variety of host dermis configurations.



FIG. 11B illustrates the sensor 32 extending from the mounting unit 14 by a preselected distance, which defines the depth of insertion of the sensor into the host. The dermal and subcutaneous make-up of animals and humans is variable and a fixed depth of insertion may not be appropriate for all implantations. Accordingly, in an alternative embodiment, the distance that the sensor extends from the mounting unit is adjustable to accommodate a variety of host body-types. For example, the applicator 12 can be designed with a variety of adjustable settings, which control the distance that the needle 72 (and therefore the sensor 32) extends upon sensor insertion. One skilled in the art appreciates a variety of means and mechanisms can be employed to accommodate adjustable sensor insertion depths, which are considered within the scope of the preferred embodiments. The preferred insertion depth is from about 0.1 mm or less to about 2 cm or more, preferably from about 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, or 0.45 mm to about 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, or 1.9 cm.



FIGS. 12A and 12B are perspective and side cross-sectional views, respectively, of the mounting unit after articulating the contact subassembly to its functional position (which is also referred to as an inserted, implanted, or sensing position). The hinge 38 enables the contact subassembly 26 to tilt from its insertion position (FIG. 11) to its functional position (FIG. 12) by pressing downward on the contact subassembly, for example. Certain embodiments provide this pivotal movement via two separate pieces (the contact subassembly 26 and the mounting unit 14 connected by a hinge, for example, a mechanical or adhesive pad joint or hinge). A variety of pivoting, articulating, and/or hinging mechanisms can be employed with the sensors of preferred embodiments. For example, the hinge can be formed as a part of the contact subassembly 26. The contact subassembly can be formed from a flexible piece of material (such as silicone, urethane rubber, or other flexible or elastomeric material), wherein the material is sufficiently flexible to enable bending or hinging of the contact subassembly from an angle appropriate for insertion (FIGS. 11A and 11B) to a lower functional configuration (FIGS. 12A and 12B).


The relative pivotal movement of the contact subassembly is advantageous, for example, for enabling the design of a low profile device while providing support for an appropriate needle insertion angle. In its insertion position, the sensor system is designed for easy sensor insertion while forming a stable electrical connection with the associated contacts 28. In its functional position, the sensor system maintains a low profile for convenience, comfort, and discreetness during use. Thus, the sensor systems of preferred embodiments are advantageously designed with a hinging configuration to provide an optimum guided insertion angle while maintaining a low profile device during sensor use.


In some embodiments, a shock-absorbing member or feature is incorporated into the design of the sensor and configured to absorb movement of the in vivo and/or ex vivo portion of the sensor. Conventional analyte sensors can suffer from motion-related artifact associated with host movement when the host is using the device. For example, when a transcutaneous analyte sensor is inserted into the host, various movements on the sensor (for example, relative movement between the in vivo portion and the ex vivo portion and/or movement within the host) create stresses on the device and can produce noise in the sensor signal. Accordingly in some embodiments, a shock-absorbing member is located on the sensor/mounting unit in a location that absorbs stresses associated with the above-described movement.


In the preferred embodiments, the sensor 32 bends from a substantially straight to substantially bent configuration upon pivoting of the contact subassembly from the insertion to functional position. The substantially straight sensor configuration during insertion advantageously provides ease of sensor insertion, while the substantial bend in the sensor in its functional position advantageously provides stability on the proximal end of the sensor with flexibility/mobility on the distal end of the sensor. Additionally, motion within the mounting unit (e.g., caused by external forces to the mounting unit, movement of the skin, and the like) does not substantially translate to the in vivo portion of the sensor. Namely, the bend formed within the sensor 32 functions to break column strength, causing flexion that effectively absorbs movements on the sensor during use. Additionally, the sensor can be designed with a length such that when the contact subassembly 26 is pivoted to its functional position (FIG. 11B), the sensor pushes forward and flexes, allowing it to absorb motion between the in vivo and ex vivo portions of the sensor. It is believed that both of the above advantages minimize motion artifact on the sensor signal and/or minimize damage to the sensor caused by movement, both of which (motion artifact and damage) have been observed in conventional transcutaneous sensors.


In some alternative embodiments, the shock-absorbing member can be an expanding and contracting member, such as a spring, accordion, telescoping, or bellows-type device. In general, the shock absorbing member can be located such that relative movement between the sensor, the mounting unit, and the host is absorbed without (or minimally) affecting the connection of the sensor to the mounting unit and/or the sensor stability within the implantation site; for example, the shock-absorbing member can be formed as a part of or connected to the sensor 32.



FIGS. 13A to 13C are perspective and side views of a sensor system including the mounting unit 14 and electronics unit 16 attached thereto. After sensor insertion, the transcutaneous analyte sensor system 10 measures a concentration of an analyte or a substance indicative of the concentration or presence of the analyte as described above. Although the examples are directed to a glucose sensor, the analyte sensor can be a sensor capable of determining the level of any suitable analyte in the body, for example, oxygen, lactase, insulin, hormones, cholesterol, medicaments, viruses, or the like. Once the electronics unit 16 is connected to the mounting unit 14, the sensor 32 is able to measure levels of the analyte in the host.


Detachable connection between the mounting unit 14 and electronics unit 16 provides improved manufacturability, namely, the relatively inexpensive mounting unit 14 can be disposed of when replacing the sensor system after its usable life, while the relatively more expensive electronics unit 16 can be reusable with multiple sensor systems. In certain embodiments, the electronics unit 16 is configured with programming, for example, initialization, calibration reset, failure testing, or the like, each time it is initially inserted into the cavity and/or each time it initially communicates with the sensor 32. However, an integral (non-detachable) electronics unit can be configured as is appreciated by one skilled in the art.


Referring to the mechanical fit between the mounting unit 14 and the electronics unit 16 (and/or applicator 12), a variety of mechanical joints are contemplated, for example, snap fit, interference fit, or slide fit. In the illustrated embodiment of FIGS. 13A to 13C, tabs 120 are provided on the mounting unit 14 and/or electronics unit 16 that enable a secure connection therebetween. The tabs 120 of the illustrated embodiment can improve ease of mechanical connection by providing alignment of the mounting unit and electronics unit and additional rigid support for force and counter force by the user (e.g., fingers) during connection. However, other configurations with or without guiding tabs are contemplated, such as illustrated in FIGS. 11 and 12, for example.


In some circumstances, a drift of the sensor signal can cause inaccuracies in sensor performance and/or require re-calibration of the sensor. Accordingly, it can be advantageous to provide a sealant, whereby moisture (e.g., water and water vapor) cannot substantially penetrate to the sensor and its connection to the electrical contacts. The sealant described herein can be used alone or in combination with the sealing member 36 described in more detail above, to seal the sensor from moisture in the external environment.


Preferably, the sealant fills in holes, crevices, or other void spaces between the mounting unit 14 and electronics unit 16 and/or around the sensor 32 within the mounting unit 32. For example, the sealant can surround the sensor in the portion of the sensor 32 that extends through the contacts 28. Additionally, the sealant can be disposed within the additional void spaces, for example a hole 122 that extends through the sealing member 36.


Preferably, the sealant comprises a water impermeable material or compound, for example, oil, grease, or gel. In one exemplary embodiment, the sealant, which also can be referred to as a lubricant in certain embodiments, comprises petroleum jelly and is used to provide a moisture barrier surrounding the sensor 32. In one experiment, petroleum jelly was liquefied by heating, after which a sensor 32 was immersed into the liquefied petroleum jelly to coat the outer surfaces thereof. The sensor was then assembled into a housing and inserted into a host, during which deployment the sensor was inserted through the electrical contacts 28 and the petroleum jelly conforming therebetween. Sensors incorporating petroleum jelly, such as described above, when compared to sensors without the petroleum jelly moisture barrier exhibited less or no signal drift over time when studied in a humid or submersed environment. While not wishing to be bound by theory, it is believed that incorporation of a moisture barrier surrounding the sensor, especially between the sensor and its associated electrical contacts, reduces or eliminates the effects of humidity on the sensor signal. The viscosity of grease or oil-based moisture barriers allows penetration into and through even small cracks or crevices within the sensor and mounting unit, displacing moisture and thereby increasing the sealing properties thereof. U.S. Pat. Nos. 4,259,540 and 5,285,513 disclose materials suitable for use as a water impermeable material (sealant).


Referring to the electrical fit between the sensor 32 and the electronics unit 16, contacts 28 (through which the sensor extends) are configured to electrically connect with mutually engaging contacts on the electronics unit 16. A variety of configurations are contemplated; however, the mutually engaging contacts operatively connect upon detachable connection of the electronics unit 16 with the mounting unit 14, and are substantially sealed from external moisture by sealing member 36. Even with the sealing member, some circumstances can exist wherein moisture can penetrate into the area surrounding the sensor 32 and or contacts, for example, exposure to a humid or wet environment (e.g., caused by sweat, showering, or other environmental causes). It has been observed that exposure of the sensor to moisture can be a cause of baseline signal drift of the sensor over time. For example in a glucose sensor, the baseline is the component of a glucose sensor signal that is not related to glucose (the amount of signal if no glucose is present), which is ideally constant over time. However, some circumstances my exist wherein the baseline can fluctuate over time, also referred to as drift, which can be caused, for example, by changes in a host's metabolism, cellular migration surrounding the sensor, interfering species, humidity in the environment, and the like.


In some embodiments, the mounting unit is designed to provide ventilation (e.g., a vent hole 124) between the exit-site and the sensor. In certain embodiments, a filter (not shown) is provided in the vent hole 124 that allows the passage of air, while preventing contaminants from entering the vent hole 124 from the external environment. While not wishing to be bound by theory, it is believed that ventilation to the exit-site (or to the sensor 32) can reduce or eliminate trapped moisture or bacteria, which can otherwise increase the growth and/or lifetime of bacteria adjacent to the sensor.


In some alternative embodiments, a sealing material is provided, which seals the needle and/or sensor from contamination of the external environment during and after sensor insertion. For example, one problem encountered in conventional transcutaneous devices is infection of the exit-site of the wound. For example, bacteria or contaminants can migrate from ex vivo, for example, any ex vivo portion of the device or the ex vivo environment, through the exit-site of the needle/sensor, and into the subcutaneous tissue, causing contamination and infection. Bacteria and/or contaminants can originate from handling of the device, exposed skin areas, and/or leakage from the mounting unit (external to) on the host. In many conventional transcutaneous devices, there exists some path of migration for bacteria and contaminants to the exit-site, which can become contaminated during sensor insertion or subsequent handling or use of the device. Furthermore, in some embodiments of a transcutaneous analyte sensor, the insertion-aiding device (for example, needle) is an integral part of the mounting unit; namely, the device stores the insertion device after insertion of the sensor, which is isolated from the exit-site (namely, point-of-entry of the sensor) after insertion.


Accordingly, these alternative embodiments provide a sealing material on the mounting unit, interposed between the housing and the skin, wherein the needle and/or sensor are adapted to extend through, and be sealed by, the sealing material. The sealing material is preferably formed from a flexible material that substantially seals around the needle/sensor. Appropriate flexible materials include malleable materials, elastomers, gels, greases, or the like (e.g., see U.S. Pat. Nos. 4,259,540 and 5,285,513). However, not all embodiments include a sealing material, and in some embodiments a clearance hole or other space surrounding the needle and/or sensor is preferred.


In one embodiment, the base 24 of the mounting unit 14 is formed from a flexible material, for example silicone, which by its elastomeric properties seals the needle and/or sensor at the exit port 126, such as is illustrated in FIGS. 12A and 12B. Thus, sealing material can be formed as a unitary or integral piece with the back surface 25 of the mounting unit 14, or with an adhesive pad 8 on the back surface of the mounting unit, however alternatively can be a separate part secured to the device. In some embodiments, the sealing material can extend through the exit port 126 above or below the plane of the adhesive pad surface, or the exit port 126 can comprise a septum seal such as those used in the medical storage and disposal industries (for example, silica gel sandwiched between upper and lower seal layers, such as layers comprising chemically inert materials such as PTFE). A variety of known septum seals can be implemented into the exit port of the preferred embodiments described herein. Whether the sealing material is integral with or a separate part attached to the mounting unit 14, the exit port 126 is advantageously sealed so as to reduce or eliminate the migration of bacteria or other contaminants to or from the exit-site of the wound and/or within the mounting unit.


During use, a host or caretaker positions the mounting unit at the appropriate location on or near the host's skin and prepares for sensor insertion. During insertion, the needle aids in sensor insertion, after which the needle is retracted into the mounting unit leaving the sensor in the subcutaneous tissue. In this embodiment, the exit-port 126 includes a layer of sealing material, such as a silicone membrane, that encloses the exit-port in a configuration that protects the exit-site from contamination that can migrate from the mounting unit or spacing external to the exit-site. Thus, when the sensor 32 and/or needle 72 extend through, for example, an aperture or a puncture in the sealing material, to provide communication between the mounting unit and subcutaneous space, a seal is formed therebetween. Elastomeric sealing materials can be advantageous in some embodiments because the elasticity provides a conforming seal between the needle/sensor and the mounting unit and/or because the elasticity provides shock-absorbing qualities allowing relative movement between the device and the various layers of the host's tissue, for example.


In some alternative embodiments, the scaling material includes a bioactive agent incorporated therein. Suitable bioactive agents include those which are known to discourage or prevent bacteria and infection, for example, anti-inflammatory, antimicrobials, antibiotics, or the like. It is believed that diffusion or presence of a bioactive agent can aid in prevention or elimination of bacteria adjacent to the exit-site.


In practice, after the sensor 32 has been inserted into the host's tissue, and an electrical connection formed by mating the electronics unit 16 to the mounting unit 14, the sensor measures an analyte concentration continuously or continually, for example, at an interval of from about fractions of a second to about 10 minutes or more.



FIG. 14 is a perspective view of a sensor system, including wireless communication between a sensor and a receiver. Preferably the electronics unit 16 is wirelessly connected to a receiver 158 via one- or two-way RF transmissions or the like. However, a wired connection is also contemplated. The receiver 158 provides much of the processing and display of the sensor data, and can be selectively worn and/or removed at the host's convenience. Thus, the sensor system 10 can be discreetly worn, and the receiver 158, which provides much of the processing and display of the sensor data, can be selectively worn and/or removed at the host's convenience. Particularly, the receiver 158 includes programming for retrospectively and/or prospectively initiating a calibration, converting sensor data, updating the calibration, evaluating received reference and sensor data, and evaluating the calibration for the analyte sensor, such as described in more detail with reference to U.S. Publication No. US-2005-0027463-A1.



FIGS. 15A and 15B are perspective views of a receiver in one preferred embodiment, wherein the receiver, also referred to as a communication station, is provided with a docking station for receiving and holding the electronics unit (from the sensor assembly) when not in use. Preferably, the electronics unit 16 is detachable from and reusable with multiple sensor assemblies 10, in multiple applications, such as described herein. This embodiment provides a docking station 98 on the receiver 158 that enables storage, electrical connection, and/or battery recharge, for example, for the electronics unit 16 while not in use on a sensor assembly 10. Complementary contacts or pins can be provided on the electronics unit 16 and the docking station 98 that enable operable connection therebetween. In some embodiments, the receiver includes programming that resets calibration when the electronics unit 16 is docked on the receiver 158. In some embodiments, the receiver is configured to reset states in the battery, such as initializing a new (unused) electronics unit to work with the receiver when the electronics unit 16 is docked on the receiver 158.


After a sensor's usable life, the host's removes and disposes of the sensor assembly 10, saving the reusable electronics unit 16 for use with another sensor assembly, which can be a few minutes to a few days later, or more, after disposing of the previous sensor assembly. In some alternative embodiments, the docketing station is provided on an alternative communication station other than the receiver, for example a personal computer, server, personal digital assistant, or the like; wherein the functionality described below can be implemented in a similar manner. In some embodiments, the receiver is configured to test operation of the electronics unit by stepping the electrodes through different current draws and disabling usage of the electronics unit if a failure is detected.


Thus, the described embodiments provide an analyte sensor assembly that enables a comfortable and reliable system for measuring an analyte level for short term applications, e.g., up to 7 days or more, without surgery. After the usable life of the sensor (for example, due to a predetermined expiration, potential infection, or level of inflammation), the host can remove the sensor and mounting from the skin, dispose of the sensor and mounting unit (preferably saving the electronics unit for reuse). The reusable electronics unit can be inserted with another sensor assembly or be implanted surgically and thus provide continuous sensor output for short or long periods of time in another application. Data provided by the analyte sensor assembly can be used to calibrate other sensors, e.g., long term sensors including the implantable long term glucose sensor described hereinbelow.


Long Term Sensor



FIG. 16 is an exploded perspective view of one exemplary embodiment of a long term continuous glucose sensor 1310A. In this embodiment, the sensor is preferably wholly implanted into the subcutaneous tissue of a host, such as described in U.S. Publication No. US-2006-0015020-A1; U.S. Publication No. US-2005-0245799-A1; U.S. Publication No. US-2005-0192557-A1; U.S. Publication No. US-2004-0199059-A1; U.S. Publication No. US-2005-0027463-A1; and U.S. Pat. No. 6,001,067. In this exemplary embodiment, a body 1320 and a sensing region 1321 house the electrodes 1322 and sensor electronics (see FIG. 17). The three electrodes 1322 are operably connected to the sensor electronics (see FIG. 17) and are covered by a sensing membrane 1323 and a biointerface membrane 1324, which are attached by a clip 1325.


In one embodiment, the three electrodes 1322 include a platinum working electrode, a platinum counter electrode, and a silver/silver chloride reference electrode. The top ends of the electrodes are in contact with an electrolyte phase (not shown), which is a free-flowing fluid phase disposed between the sensing membrane 1323 and the electrodes 1322. The sensing membrane 1323 includes an enzyme, for example, glucose oxidase, and covers the electrolyte phase. The biointerface membrane 1324, such as described above, covers the sensing membrane 1323 and serves, at least in part, to protect the sensor 1310A from external forces that can result in environmental stress cracking of the sensing membrane 1323. U.S. Publication No. US-2005-0112169-A1 describes a biointerface membrane that can be used in conjunction with the preferred embodiments.


In one embodiment, the biointerface membrane 1324 generally includes a cell disruptive domain most distal from the electrochemically reactive surfaces and a cell impermeable domain less distal from the electrochemically reactive surfaces than the cell disruptive domain. The cell disruptive domain is preferably designed to support tissue ingrowth, disrupt contractile forces typically found in a foreign body response, encourage vascularity within the membrane, and disrupt the formation of a barrier cell layer. The cell impermeable domain is preferably resistant to cellular attachment, impermeable to cells, and composed of a biostable material.


In one embodiment, the sensing membrane 1323 generally provides one or more of the following functions: 1) supporting tissue ingrowth; 2) protection of the exposed electrode surface from the biological environment, 3) diffusion resistance (limitation) of the analyte, 4) a catalyst for enabling an enzymatic reaction, 5) limitation or blocking of interfering species, and 6) hydrophilicity at the electrochemically reactive surfaces of the sensor interface, such as described in U.S. Publication No. US-2005-0245799-A1. Accordingly, the sensing membrane 1323 preferably includes a plurality of domains or layers, for example, an electrolyte domain, an interference domain, an enzyme domain (for example, glucose oxidase), a resistance domain, and can additionally include an oxygen domain (not shown), and/or a bioprotective domain (not shown), such as described in more detail herein and in U.S. Publication No. US-2005-0245799-A1. However, it is understood that a sensing membrane modified for other devices, for example, by including fewer or additional domains is within the scope of the preferred embodiments.


In some embodiments, the domains of the biointerface and sensing membranes are formed from materials such as silicone, polytetrafluoroethylene, polyethylene-co-tetrafluoroethylene, polyolefin, polyester, polycarbonate, biostable polytetrafluoroethylene, homopolymers, copolymers, terpolymers of polyurethanes, polypropylene (PP), polyvinylchloride (PVC), polyvinylidene fluoride (PVDF), polybutylene terephthalate (PBT), polymethylmethacrylate (PMMA), polyether ether ketone (PEEK), polyurethanes, cellulosic polymers, polysulfones and block copolymers thereof including, for example, di-block, tri-block, alternating, random and graft copolymers. U.S. Publication No. US-2005-0245799-A1 describes biointerface and sensing membrane configurations and materials that can be applied to the preferred embodiments.


In the illustrated embodiment, the counter electrode is provided to balance the current generated by the species being measured at the working electrode. In the case of a glucose oxidase based glucose sensor, the species being measured at the working electrode is H2O2. Glucose oxidase catalyzes the conversion of oxygen and glucose to hydrogen peroxide and gluconate according to the following reaction:

Glucose+O2→Gluconate+H2O2


The change in H2O2 can be monitored to determine glucose concentration because for each glucose molecule metabolized, there is a proportional change in the product H2O2. Oxidation of H2O2 by the working electrode is balanced by reduction of ambient oxygen, enzyme generated H2O2, or other reducible species at the counter electrode. The H2O2 produced from the glucose oxidase reaction further reacts at the surface of working electrode and produces two protons (2H+), two electrons (2e), and one oxygen molecule (O2).


In one embodiment, a potentiostat is employed to monitor the electrochemical reaction at the electrochemical cell. The potentiostat applies a constant potential to the working and reference electrodes to determine a current value. The current that is produced at the working electrode (and flows through the circuitry to the counter electrode) is substantially proportional to the amount of H2O2 that diffuses to the working electrode. Accordingly, a raw signal can be produced that is representative of the concentration of glucose in the user's body, and therefore can be utilized to estimate a meaningful glucose value, such as is described herein.


Sensor Electronics


One example of sensor electronics that may be utilized with either the short term or long term sensors is depicted in the block diagram of FIG. 17, illustrating the electronics 132 associated with the sensor system in one embodiment. In this embodiment, a potentiostat 134 is shown, which is operably connected to an electrode system (such as described above) and provides a voltage to the electrodes, which biases the sensor to enable measurement of an current signal indicative of the analyte concentration in the host (also referred to as the analog portion). In some embodiments, the potentiostat includes a resistor (not shown) that translates the current into voltage. In some alternative embodiments, a current to frequency converter is provided that is configured to continuously integrate the measured current, for example, using a charge counting device.


An A/D converter 136 digitizes the analog signal into a digital signal, also referred to as “counts” for processing. Accordingly, the resulting raw data stream in counts, also referred to as raw sensor data, is directly related to the current measured by the potentiostat 134.


A processor module 138 includes the central control unit that controls the processing of the sensor electronics 132. In some embodiments, the processor module includes a microprocessor, however a computer system other than a microprocessor can be used to process data as described herein, for example an ASIC can be used for some or all of the sensor's central processing. The processor typically provides semi-permanent storage of data, for example, storing data such as sensor identifier (ID) and programming to process data streams (for example, programming for data smoothing and/or replacement of signal artifacts such as is described in U.S. Publication No. US-2005-0043598-A1). The processor additionally can be used for the system's cache memory, for example for temporarily storing recent sensor data. In some embodiments, the processor module comprises memory storage components such as ROM, RAM, dynamic-RAM, static-RAM, non-static RAM, EEPROM, rewritable ROMs, flash memory, or the like.


In some embodiments, the processor module comprises a digital filter, for example, an infinite impulse response (IIR) or finite impulse response (FIR) filter, configured to smooth the raw data stream from the A/D converter. Generally, digital filters are programmed to filter data sampled at a predetermined time interval (also referred to as a sample rate). In some embodiments, wherein the potentiostat is configured to measure the analyte at discrete time intervals, these time intervals determine the sample rate of the digital filter. In some alternative embodiments, wherein the potentiostat is configured to continuously measure the analyte, for example, using a current-to-frequency converter as described above, the processor module can be programmed to request a digital value from the A/D converter at a predetermined time interval, also referred to as the acquisition time. In these alternative embodiments, the values obtained by the processor are advantageously averaged over the acquisition time due the continuity of the current measurement. Accordingly, the acquisition time determines the sample rate of the digital filter. In preferred embodiments, the processor module is configured with a programmable acquisition time, namely, the predetermined time interval for requesting the digital value from the A/D converter is programmable by a user within the digital circuitry of the processor module. An acquisition time of from about 2 seconds to about 512 seconds is preferred; however any acquisition time can be programmed into the processor module. A programmable acquisition time is advantageous in optimizing noise filtration, time lag, and processing/battery power.


Preferably, the processor module is configured to build the data packet for transmission to an outside source, for example, an RF transmission to a receiver as described in more detail below. Generally, the data packet comprises a plurality of bits that can include a preamble, a unique identifier identifying the electronics unit, the receiver, or both. (e.g., sensor ID code), data (e.g., raw data, filtered data, and/or an integrated value) and/or error detection or correction. Preferably, the data (transmission) packet has a length of from about 8 bits to about 128 bits, preferably about 48 bits; however, larger or smaller packets can be desirable in certain embodiments. The processor module can be configured to transmit any combination of raw and/or filtered data. In one exemplary embodiment, the transmission packet contains a fixed preamble, a unique ID of the electronics unit, a single five-minute average (e.g., integrated) sensor data value, and a cyclic redundancy code (CRC).


In some embodiments, the processor module further comprises a transmitter portion that determines the transmission interval of the sensor data to a receiver, or the like. In some embodiments, the transmitter portion, which determines the interval of transmission, is configured to be programmable. In one such embodiment, a coefficient can be chosen (e.g., a number of from about 1 to about 100, or more), wherein the coefficient is multiplied by the acquisition time (or sampling rate), such as described above, to define the transmission interval of the data packet. Thus, in some embodiments, the transmission interval is programmable from about 2 seconds to about 850 minutes, more preferably from about 30 second to about 5 minutes; however, any transmission interval can be programmable or programmed into the processor module. However, a variety of alternative systems and methods for providing a programmable transmission interval can also be employed. By providing a programmable transmission interval, data transmission can be customized to meet a variety of design criteria (e.g., reduced battery consumption, timeliness of reporting sensor values, etc.)


Conventional glucose sensors measure current in the nanoAmp range. In contrast to conventional glucose sensors, the preferred embodiments are configured to measure the current flow in the picoAmp range, and in some embodiments, femtoAmps. Namely, for every unit (mg/dL) of glucose measured, at least one picoAmp of current is measured. Preferably, the analog portion of the A/D converter 136 is configured to continuously measure the current flowing at the working electrode and to convert the current measurement to digital values representative of the current. In one embodiment, the current flow is measured by a charge counting device (e.g., a capacitor). Preferably, a charge counting device provides a value (e.g., digital value) representative of the current flow integrated over time (e.g., integrated value). In some embodiments, the value is integrated over a few seconds, a few minutes, or longer. In one exemplary embodiment, the value is integrated over 5 minutes; however, other integration periods can be chosen. Thus, a signal is provided, whereby a high sensitivity maximizes the signal received by a minimal amount of measured hydrogen peroxide (e.g., minimal glucose requirements without sacrificing accuracy even in low glucose ranges), reducing the sensitivity to oxygen limitations in vivo (e.g., in oxygen-dependent glucose sensors).


In some embodiments, the electronics unit is programmed with a specific ID, which is programmed (automatically or by the user) into a receiver to establish a secure wireless communication link between the electronics unit and the receiver. Preferably, the transmission packet is Manchester encoded; however, a variety of known encoding techniques can also be employed.


A battery 144 is operably connected to the sensor electronics 132 and provides the power for the sensor. In one embodiment, the battery is a lithium manganese dioxide battery; however, any appropriately sized and powered battery can be used (for example, AAA, nickel-cadmium, zinc-carbon, alkaline, lithium, nickel-metal hydride, lithium-ion, zinc-air, zinc-mercury oxide, silver-zinc, and/or hermetically-sealed). In some embodiments, the battery is rechargeable, and/or a plurality of batteries can be used to power the system. The sensor can be transcutaneously powered via an inductive coupling, for example. In some embodiments, a quartz crystal 96 is operably connected to the processor 138 and maintains system time for the computer system as a whole, for example for the programmable acquisition time within the processor module.


Optional temperature probe 140 is shown, wherein the temperature probe is located on the electronics assembly or the glucose sensor itself. The temperature probe can be used to measure ambient temperature in the vicinity of the glucose sensor. This temperature measurement can be used to add temperature compensation to the calculated glucose value.


An RF module 148 is operably connected to the processor 138 and transmits the sensor data from the sensor to a receiver within a wireless transmission 150 via antenna 152. In some embodiments, a second quartz crystal 154 provides the time base for the RF carrier frequency used for data transmissions from the RF transceiver. In some alternative embodiments, however, other mechanisms, such as optical, infrared radiation (IR), ultrasonic, or the like, can be used to transmit and/or receive data.


In the RF telemetry module of the preferred embodiments, the hardware and software are designed for low power requirements to increase the longevity of the device (for example, to enable a life of from about 3 to about 24 months, or more) with maximum RF transmittance from the in vivo environment to the ex vivo environment for wholly implantable sensors (for example, a distance of from about one to ten meters or more). Preferably, a high frequency carrier signal of from about 402 MHz to about 433 MHz is employed in order to maintain lower power requirements. In some embodiments, the RF module employs a one-way RF communication link to provide a simplified ultra low power data transmission and receiving scheme. The RF transmission can be OOK or FSK modulated, preferably with a radiated transmission power (EIRP) fixed at a single power level of typically less than about 100 microwatts, preferably less than about 75 microwatts, more preferably less than about 50 microwatts, and most preferably less than about 25 microwatts.


Additionally, in wholly implantable devices, the carrier frequency is adapted for physiological attenuation levels, which is accomplished by tuning the RF module in a simulated in vivo environment to ensure RF functionality after implantation; accordingly, the preferred glucose sensor can sustain sensor function for 3 months, 6 months, 12 months, or 24 months or more.


When a sensor is first implanted into host tissue, the sensor and receiver are initialized. This is referred to as start-up mode, and involves optionally resetting the sensor data and calibrating the sensor 32. In selected embodiments (e.g., transcutaneous sensors), mating the electronics unit 16 to the mounting unit 14 triggers a start-up mode. In other embodiments, the start-up mode is triggered by the receiver, which is described in more detail with reference to FIG. 21, below.


Preferably, the electronics unit 16 indicates to the receiver (FIGS. 14 and 17) that calibration is to be initialized (or re-initialized). The electronics unit 16 transmits a series of bits within a transmitted data packet wherein a sensor code can be included in the periodic transmission of the device. The status code is used to communicate sensor status to the receiving device. The status code can be inserted into any location in the transmitted data packet, with or without other sensor information. In one embodiment, the status code is designed to be unique or near unique to an individual sensor, which can be accomplished using a value that increments, decrements, or changes in some way after the transmitter detects that a sensor has been removed and/or attached to the transmitter. In an alternative embodiment, the status code can be configured to follow a specific progression, such as a BCD interpretation of a Gray code.


In some embodiments (e.g., transcutaneous sensors), the sensor electronics 132 are configured to detect a current drop to zero in the working electrode 44 associated with removal of a sensor 32 from the host (or the electronics unit 16 from the mounting unit 14), which can be configured to trigger an increment of the status code. If the incremented value reaches a maximum, it can be designed to roll over to 0. In some embodiments, the sensor electronics are configured to detect a voltage change cycle associated with removal and/or re-insertion of the sensor, which can be sensed in the counter electrode (e.g., of a three-electrode sensor), which can be configured to trigger an increment of the status code.


In some embodiments, the sensor electronics 132 can be configured to send a special value (for example, 0) that indicates that the electronics unit is not attached when removal of the sensor (or electronics unit) is detected. This special value can be used to trigger a variety of events, for example, to halt display of analyte values. Incrementing or decrementing routines can be used to skip this special value.


Data Smoothing


Typically, an analyte sensor (both short and long term) produces a raw data signal that is indicative of the analyte concentration of a user. The above described glucose sensor is only one example of an abundance of analyte sensors that are able to provide a raw data signal output indicative of the concentration of the analyte of interest. The devices and methods of the preferred embodiments, including data smoothing, calibration, evaluation, and other data processing, can be applied to raw data obtained from any analyte sensor capable of producing a output signal.


Raw data signals received from an analyte sensor can include signal noise, which degrades the quality of the data. The use of smoothing algorithms help improve the signal-to-noise ratio in the sensor by reducing signal jitter, for example. One example of a conventional data smoothing algorithms include finite impulse response filter (FIR), which is particularly suited for reducing high-frequency noise (see Steil et al. U.S. Pat. No. 6,558,351). Other analyte sensors have utilized heuristic and moving average type algorithms to accomplish data smoothing of signal jitter in data signals, for example.


It is advantageous to also reduce signal noise by attenuating transient, low frequency, non-analyte related signal fluctuations (e.g., transient ischemia and/or long transient periods of postural effects that interfere with sensor function due to lack of oxygen and/or other physiological effects).


In one embodiment, this attenuation of transient low frequency non-analyte related signal noise is accomplished using a recursive filter. In contrast to conventional non-recursive (e.g., FIR) filters in which each computation uses new input data sets, a recursive filter is an equation that uses moving averages as inputs; that is, a recursive filter includes previous averages as part of the next filtered output. Recursive filters are advantageous at least in part due to their computational efficiency.



FIG. 18 is a graph that illustrates data smoothing of a raw data signal in one embodiment. In this embodiment, the recursive filter is implemented as a digital infinite impulse response filter (IIR) filter, wherein the output is computed using 6 additions and 7 multiplies as shown in the following equation:







y

(
n
)

=







a
0



x


(
n
)



+


a
1



x


(

n
-
1

)



+








a
2



x


(

n
-
2

)



+


a
3



x

(

n
-
3

)


-








b
1



y


(

n
-
1

)



-


b
2



y


(

n
-
2

)



-


b
3



y


(

n
-
3

)








b
0







This polynomial equation includes coefficients that are dependent on sample rate and frequency behavior of the filter. In this exemplary embodiment, frequency behavior passes low frequencies up to cycle lengths of 40 minutes, and is based on a 30 second sample rate.


In some embodiments, data smoothing can be implemented in the sensor and the smoothed data transmitted to a receiver for additional processing. In other embodiments, raw data can be sent from the sensor to a receiver for data smoothing and additional processing therein. In yet other embodiments, the sensor is integral with the receiver and therefore no transmission of data is required.


In one exemplary embodiment, where the sensor is an implantable glucose sensor, data smoothing is performed in the sensor to ensure a continuous stream of data. In alternative embodiments, data smoothing can be transmitted from the sensor to the receiver, and the data smoothing performed at the receiver; however that there can be a risk of transmit-loss in the radio transmission from the sensor to the receiver when the transmission is wireless. For example, in embodiments wherein a sensor is implemented in vivo, the raw sensor signal can be more consistent within the sensor (in vivo) than the raw signal transmitted to a source (e.g., receiver) outside the body (e.g., if a patient were to take the receiver off to shower, communication between the sensor and receiver can be lost and data smoothing in the receiver would halt accordingly.) Consequently, a multiple point data loss in the filter can take, for example, anywhere from 25 to 40 minutes for the smoothed data to recover to where it would have been had there been no data loss.


Other systems and methods for data smoothing and/or for detecting and/or replacing certain sensor data (e.g., signal artifacts or system noise) are described in U.S Publication No. US-2005-0043598-A1.


Receiver



FIGS. 19A to 19D are schematic views of a receiver in first, second, third, and fourth embodiments, respectively. A receiver 1640 comprises systems necessary to receive, process, and display sensor data from an analyte sensor, such as described elsewhere herein. Particularly, the receiver 1640 can be a pager-sized device, for example, and comprise a user interface that has a plurality of buttons 1642 and a liquid crystal display (LCD) screen 1644, and which can include a backlight. In some embodiments the user interface can also include a keyboard, a speaker, and a vibrator such as described with reference to FIG. 20A.


In some embodiments a user is able to toggle through some or all of the screens shown in FIGS. 19A to 19D using a toggle button on the receiver. In some embodiments, the user is able to interactively select the type of output displayed on their user interface. In some embodiments, the sensor output can have alternative configurations.



FIG. 20A is a block diagram that illustrates the configuration of the medical device in one embodiment, including a continuous analyte sensor, a receiver, and an external device. In general, the analyte sensor system is any sensor configuration that provides an output signal indicative of a concentration of an analyte (e.g., invasive, minimally-invasive, and/or non-invasive sensors as described above). The output signal is sent to a receiver 158 and received by an input module 174, which is described in more detail below. The output signal is typically a raw data stream that is used to provide a useful value of the measured analyte concentration to a patient or a doctor, for example. In some embodiments, the raw data stream can be continuously or periodically algorithmically smoothed or otherwise modified to diminish outlying points that do not accurately represent the analyte concentration, for example due to signal noise or other signal artifacts, such as described in U.S. Pat. No. 6,931,327.


Referring again to FIG. 20A, the receiver 158, which is operatively linked to the sensor system 10, receives a data stream from the sensor system 10 via the input module 174. In one embodiment, the input module includes a quartz crystal operably connected to an RF transceiver (not shown) that together function to receive and synchronize data streams from the sensor system 10. However, the input module 174 can be configured in any manner that is capable of receiving data from the sensor. Once received, the input module 174 sends the data stream to a processor 176 that processes the data stream, such as is described in more detail below.


The processor 176 is the central control unit that performs the processing, such as storing data, analyzing data streams, calibrating analyte sensor data, estimating analyte values, comparing estimated analyte values with time corresponding measured analyte values, analyzing a variation of estimated analyte values, downloading data, and controlling the user interface by providing analyte values, prompts, messages, warnings, alarms, or the like. The processor includes hardware and software that performs the processing described herein, for example flash memory provides permanent or semi-permanent storage of data, storing data such as sensor ID, receiver ID, and programming to process data streams (for example, programming for performing estimation and other algorithms described elsewhere herein) and random access memory (RAM) stores the system's cache memory and is helpful in data processing.


Preferably, the input module 174 or processor module 176 performs a Cyclic Redundancy Check (CRC) to verify data integrity, with or without a method of recovering the data if there is an error. In some embodiments, error correction techniques such as those that use Hamming codes or Reed-Solomon encoding/decoding methods are employed to correct for errors in the data stream. In one alternative embodiment, an iterative decoding technique is employed, wherein the decoding is processed iteratively (e.g., in a closed loop) to determine the most likely decoded signal. This type of decoding can allow for recovery of a signal that is as low as 0.5 dB above the noise floor, which is in contrast to conventional non-iterative decoding techniques (such as Reed-Solomon), which requires approximately 3 dB or about twice the signal power to recover the same signal (e.g., a turbo code).


An output module 178, which is integral with and/or operatively connected with the processor 176, includes programming for generating output based on the data stream received from the sensor system 10 and its processing incurred in the processor 176. In some embodiments, output is generated via a user interface 160.


The user interface 160 comprises a keyboard 162, speaker 164, vibrator 166, backlight 168, liquid crystal display (LCD) screen 170, and one or more buttons 172. The components that comprise the user interface 160 include controls to allow interaction of the user with the receiver. The keyboard 162 can allow, for example, input of user information about himself/herself, such as mealtime, exercise, insulin administration, customized therapy recommendations, and reference analyte values. The speaker 164 can produce, for example, audible signals or alerts for conditions such as present and/or estimated hyperglycemic or hypoglycemic conditions in a person with diabetes. The vibrator 166 can provide, for example, tactile signals or alerts for reasons such as described with reference to the speaker, above. The backlight 168 can be provided, for example, to aid the user in reading the LCD 170 in low light conditions. The LCD 170 can be provided, for example, to provide the user with visual data output, such as is described in U.S. Publication No. US-2005-0203360-A1. FIGS. 20B to 20D illustrate some additional visual displays that can be provided on the screen 170. In some embodiments, the LCD is a touch-activated screen, enabling each selection by a user, for example, from a menu on the screen. The buttons 172 can provide for toggle, menu selection, option selection, mode selection, and reset, for example. In some alternative embodiments, a microphone can be provided to allow for voice-activated control.


In some embodiments, prompts or messages can be displayed on the user interface to convey information to the user, such as reference outlier values, requests for reference analyte values, therapy recommendations, deviation of the measured analyte values from the estimated analyte values, or the like. Additionally, prompts can be displayed to guide the user through calibration or trouble-shooting of the calibration.


In some embodiments, the receiver and/or a device connected to the receiver is configured to audibly output the user's analyte value(s), trend information (increasing or decreasing analyte values), and the like, hereinafter referred to as the audible output module. In some embodiments, the audible output module additionally includes: high and low blood glucose limits at which the module will audibly output the user's analyte value and/or trend information; English and non-English language versions; and choice of male or female voice. In some embodiments, the audible output is transmitted to an earbud worn by the patient for use where privacy is required or by a patient who is somewhat audibly impaired. The audible output module can be particularly advantageous in applications wherein the user is visually and/or hearing impaired, or is unable to visually check their receiver due to other circumstances (e.g., operating a motor vehicle or machinery, engaged in a business meeting or social event, or the like).


Additionally, data output from the output module 178 can provide wired or wireless, one- or two-way communication between the receiver 158 and an external device 180. The external device 180 can be any device that wherein interfaces or communicates with the receiver 158. In some embodiments, the external device 180 is a computer, and the receiver 158 is able to download historical data for retrospective analysis by the patient or physician, for example. In some embodiments, the external device 180 is a modem or other telecommunications station, and the receiver 158 is able to send alerts, warnings, emergency messages, or the like, via telecommunication lines to another party, such as a doctor or family member. In some embodiments, the external device 180 is an insulin pen, and the receiver 158 is able to communicate therapy recommendations, such as insulin amount and time to the insulin pen. In some embodiments, the external device 180 is an insulin pump, and the receiver 158 is able to communicate therapy recommendations, such as insulin amount and time to the insulin pump. The external device 180 can include other technology or medical devices, for example pacemakers, implanted analyte sensor patches, other infusion devices, telemetry devices, or the like.


The user interface 160, including keyboard 162, buttons 172, a microphone (not shown), and the external device 180, can be configured to allow input of data. Data input can be helpful in obtaining information about the patient (for example, meal time, exercise, or the like), receiving instructions from a physician (for example, customized therapy recommendations, targets, or the like), and downloading software updates, for example. Keyboard, buttons, touch-screen, and microphone are all examples of mechanisms by which a user can input data directly into the receiver. A server, personal computer, personal digital assistant, insulin pump, and insulin pen are examples of external devices that can provide useful information to the receiver. Other devices internal or external to the sensor that measure other aspects of a patient's body (for example, temperature sensor, accelerometer, heart rate monitor, oxygen monitor, or the like) can be used to provide input helpful in data processing. In one embodiment, the user interface can prompt the patient to select an activity most closely related to their present activity, which can be helpful in linking to an individual's physiological patterns, or other data processing. In another embodiment, a temperature sensor and/or heart rate monitor can provide information helpful in linking activity, metabolism, and glucose excursions of an individual. While a few examples of data input have been provided here, a variety of information can be input, which can be helpful in data processing.



FIG. 20B is an illustration of an LCD screen 170 showing continuous and single point glucose information in the form of a trend graph 184 and a single numerical value 186. The trend graph shows upper and lower boundaries 182 representing a target range between which the host should maintain his/her glucose values. Preferably, the receiver is configured such that these boundaries 182 can be configured or customized by a user, such as the host or a care provider. By providing visual boundaries 182, in combination with continuous analyte values over time (e.g., a trend graph 184), a user can better learn how to control his/her analyte concentration (e.g., a person with diabetes can better learn how to control his/her glucose concentration) as compared to single point (single numerical value 186) alone. Although FIG. 20B illustrates a 1 hour trend graph (e.g., depicted with a time range 188 of 1 hour), a variety of time ranges can be represented on the screen 170, for example, 3 hour, 9 hour, 1 day, and the like.



FIG. 20C is an illustration of an LCD screen 170 showing a low alert screen that can be displayed responsive to a host's analyte concentration falling below a lower boundary (see boundaries 182). In this exemplary screen, a host's glucose concentration has fallen to 55 mg/dL, which is below the lower boundary set in FIG. 20B, for example. The arrow 190 represents the direction of the analyte trend, for example, indicating that the glucose concentration is continuing to drop. The annotation 192 (“LOW”) is helpful in immediately and clearly alerting the host that his/her glucose concentration has dropped below a preset limit, and what may be considered to be a clinically safe value, for example. FIG. 20D is an illustration of an LCD screen 170 showing a high alert screen that can be displayed responsive to a host's analyte concentration rising above an upper boundary (see boundaries 182). In this exemplary screen, a host's glucose concentration has risen to 200 mg/dL, which is above a boundary set by the host, thereby triggering the high alert screen. The arrow 190 represents the direction of the analyte trend, for example, indicating that the glucose concentration is continuing to rise. The annotation 192 (“HIGH”) is helpful in immediately and clearly alerting the host that his/her glucose concentration has above a preset limit, and what may be considered to be a clinically safe value, for example.


Although a few exemplary screens are depicted herein, a variety of screens can be provided for illustrating any of the information described in the preferred embodiments, as well as additional information. A user can toggle between these screens (e.g., using buttons 172) and/or the screens can be automatically displayed responsive to programming within the receiver 158, and can be simultaneously accompanied by another type of alert (audible or tactile, for example).


In some embodiments the receiver 158 can have a length of from about 8 cm to about 15 cm, a width of from about 3.5 cm to about 10 cm, and/or a thickness of from about 1 cm to about 3.5 cm. In some embodiments the receiver 158 can have a volume of from about 120 cm3 to about 180 cm3, and can have a weight of from about 70 g to 130 g. The dimensions and volume can be higher or lower, depending, e.g., on the type of devices integrated (e.g., finger stick devices, pumps. PDAs, and the like.), the type of user interface employed, and the like.


In some embodiments, the receiver 158 is an application-specific device. In some embodiments the receiver 158 can be a device used for other functions, such as are described in U.S. Pat. No. 6,558,320. For example, the receiver 158 can be integrated into a personal computer (PC), a personal digital assistant (PDA), a cell phone, or another fixed or portable computing device. The integration of the receiver 158 function into a more general purpose device can comprise the addition of software and/or hardware to the device. Communication between the sensor electronics 16 and the receiver 158 function of the more general purpose device can be implemented with wired or wireless technologies. For example, a PDA can be configured with a data communications port and/or a wireless receiver. After the user establishes a communication link between the electronics unit 16 and the PDA, the electronics unit 16 transmits data to the PDA which then processes the data according to software which has been loaded thereon so as to display.


Sensor Calibration


Reference is now made to FIG. 21, which is a flow chart that illustrates the initial calibration and data output of sensor data from a sensor, e.g., a short term or long term analyte sensor. Calibration of an analyte sensor comprises data processing that uses sensor data and other information to determine an estimated analyte measurement that is meaningful to a user or useful for further data processing. One or more reference values can be used to calibrate the sensor data. In some embodiments, reference values can be obtained from sensor data of another analyte sensor. For example, a substantially continuous short term sensor can be used to calibrate another substantially continuous short term sensor or a substantially continuous long term sensor, or a substantially continuous long term sensor can be used to calibrate another substantially continuous long term sensor or a substantially continuous short term sensor. Reference values can also be obtained from a non-continuous monitoring system, such as a self-monitored blood analyte test (e.g., finger stick blood samples), an optical sensor, etc. However, using sensor data from an already employed substantially continuous short term sensor or a substantially continuous long term sensor can reduce or obviate the need for non-continuous manual measurements to obtain reference data. In addition, reference values can be obtained from in-vitro benchtop sources during a benchtop calibration process. For example, reference solutions of analyte may be used for in-vitro calibration where the reference value for the concentration is known from the reference solution preparation.



FIG. 21 illustrates initial calibration of an analyte sensor using reference data from any reference analyte source, including another analyte sensor (for example, a previously calibrated analyte sensor). At block 261, a sensor data receiving module, also referred to as the sensor data module, receives sensor data (e.g., a data stream), including one or more time-spaced sensor data points, from a sensor via the receiver, which can be in wired or wireless communication with the sensor. The sensor data point(s) can be smoothed, such as described with reference to FIG. 18, above. During the initialization of the sensor, prior to initial calibration, the receiver (e.g., computer system) receives and stores the sensor data. However, the receiver can be configured so that data is not displayed to a user until initial calibration and possibly stabilization of the sensor has been determined.


At block 262, a reference data receiving module, also referred to as the reference input module, receives reference data from a reference analyte source, including one or more reference data points. In one embodiment, the reference data is based on sensor data from another substantially continuous analyte sensor, e.g., an analyte sensor described herein, or another type of suitable analyte sensor. For example, a previously calibrated short or long term glucose sensor providing sensor data for a host can provide reference data for use in calibrating sensor data from a long term glucose sensor implanted in the same host.


At block 263, a data matching module, also referred to as the processor module, matches reference data (e.g., one or more reference analyte data points) with substantially time corresponding sensor data (e.g., one or more sensor data points) to provide one or more matched data pairs. In one embodiment, one reference data point is matched to one time corresponding sensor data point to form a matched data pair. In another embodiment, a plurality of reference data points are averaged (e.g., equally or non-equally weighted average, mean-value, median, or the like) and matched to one time corresponding sensor data point to form a matched data pair. In another embodiment, one reference data point is matched to a plurality of time corresponding sensor data points averaged to form a matched data pair. In yet another embodiment, a plurality of reference data points are averaged and matched to a plurality of time corresponding sensor data points averaged to form a matched data pair. In yet another embodiment, a line is produced from the reference data points as a function of time. The line may be produced by connecting individual data points, from smoothed data points, or as a best-fit through the application of an appropriate algorithm. A line produced from a series of sensor data points may be matched to the line produced from the reference data points.


To properly associate the sensor data with reference data, a delay in the sensing process can be taken into account. In one embodiment, the reference data is provided by another substantially continuous source that has similar sensor characteristics so that the delay in the sensor data is similar to the delay in the reference data. If the delay is not similar, the data can be appropriately processed to associate the data taken at the same time. In one embodiment where the sensor data is being associated with data from a non-continuous source, time corresponding sensor data comprises one or more sensor data points that occur 5 min (e.g., +/−2% minutes) after the reference analyte data timestamp (e.g., the time that the reference analyte data is obtained). In this embodiment, the 15 minute time delay has been chosen to account for an approximately 10 minute delay introduced by the filter used in data smoothing and an approximately 5 minute physiological time-lag (e.g., the time necessary for the analyte to diffusion through a membrane(s) of an analyte sensor). In alternative embodiments, the time corresponding sensor value can be more or less than the above-described embodiment, for example t 60 minutes. Variability in time correspondence of sensor and reference data can be attributed to, for example a longer or shorter time delay introduced by the data smoothing filter, or if the configuration of the analyte sensor incurs a greater or lesser physiological time lag. In one exemplary embodiment, time delay information from a short term sensor can be used by a long term sensor as described above. In another exemplary embodiment, time delay information from a first short term sensor can be used by a second short term sensor as described above. In yet another exemplary embodiment, time delay information from a first long term sensor can be used by a second long term sensor as described above.


In some embodiments, tests are used to evaluate the best matched pair using a reference data point against individual sensor values over a predetermined time period (e.g., about 30 minutes). In one such exemplary embodiment, the reference data point is matched with sensor data points at 5-minute intervals and each matched pair is evaluated. The matched pair with the best correlation can be selected as the matched pair for data processing. In some alternative embodiments, matching a reference data point with an average of a plurality of sensor data points over a predetermined time period can be used to form a matched pair.


At block 264, a calibration set module, also referred to as the processor module, forms an initial calibration set from a set of one or more matched data pairs, which are used to determine the relationship between the reference analyte data and the sensor analyte data, such as will be described in more detail with reference to block 267, below.


The matched data pairs, which make up the initial calibration set, can be selected according to predetermined criteria. The criteria for the initial calibration set can be the same as, or different from, the criteria for the update calibration set, which is described in more detail with reference to FIG. 24. In some embodiments, the number (n) of data pair(s) selected for the initial calibration set is one. In other embodiments, n data pairs are selected for the initial calibration set wherein n is a function of the frequency of the received reference data points. For example, a substantially continuous analyte sensor can provide numerous data points for use as reference data (e.g., dozens or even hundreds). In one exemplary embodiment, a substantially continuous analyte sensor provides about 288 reference data points per day (about every five minutes for twenty-four hours). In one exemplary embodiment, six data pairs make up the initial calibration set.


In some embodiments, the data pairs are selected only within a certain analyte value threshold, for example wherein the reference analyte value is from about 40 and to about 400 mg/dL. In some embodiments, the data pairs that form the initial calibration set are selected according to their time stamp. In some embodiments, the calibration set is selected such as described with reference to FIG. 24.


At block 265, an optional stability determination module, also referred to as the start-up module, determines the stability of the analyte sensor over a period of time. Some analyte sensors can have an initial instability time period during which the analyte sensor is unstable for environmental, physiological, or other reasons. One example of initial sensor instability is an embodiment wherein the analyte sensor is implanted subcutaneously; in this example embodiment, stabilization of the analyte sensor can be dependent upon the maturity of the tissue ingrowth around and within the sensor. Another example of initial sensor instability is in an embodiment wherein the analyte sensor is inserted transdermally (e.g., transcutaneously); in this example embodiment, stabilization of the analyte sensor can be dependent upon electrode stabilization and/or sweat, for example.


Accordingly, in some embodiments, determination of sensor stability can include waiting a predetermined time period (e.g., an implantable sensor is known to require a time period for tissue ingrowth, and a transdermal (e.g., transcutaneous) sensor is known to require time to equilibrate the sensor with the user's tissue); in some embodiments, this waiting period is from about one minute to about six weeks. Although in some embodiments, the sensitivity (e.g., sensor signal strength with respect to analyte concentration) can be used to determine the stability of the sensor; for example, amplitude and/or variability of sensor sensitivity can be evaluated to determine the stability of the sensor. In alternative embodiments, detection of pH levels, oxygen, hypochlorite, interfering species (e.g., ascorbate, urea, and acetaminophen), correlation between sensor and reference values (e.g., R-value), baseline drift and/or offset, and the like can be used to determine the stability of the sensor. In one exemplary embodiment, wherein the sensor is a glucose sensor, it is known to provide a signal that is associated with interfering species (e.g., ascorbate, urea, acetaminophen), which can be used to evaluate sensor stability. In another exemplary embodiment, wherein the sensor is a glucose sensor such as described with reference to FIGS. 8 and 9, the counter electrode can be monitored for oxygen deprivation, which can be used to evaluate sensor stability or functionality. Numerous other systems and methods for evaluating sensor stability or functionality are described in U.S. Publication No. US-2005-0043598-A1. In one embodiment employing a long term implantable sensor that requires a waiting period, a short term sensor or a series of short term sensors employed for the same user provides sensor data to the user during the waiting period. In an embodiment employing a series of short term sensors, the sensors can be employed so that they provide sensor data in discrete or overlapping periods. In such embodiments, the sensor data from one short term sensor can be used to calibrate another short term sensor, or be used to confirm the validity of a subsequently employed short term sensor. The data can also be used for calibrating the implantable long term sensor so that data from the long term sensor can be used immediately upon completion of the waiting period.


At decision block 266, the system (e.g., microprocessor) determines whether the analyte sensor is sufficiently stable according to certain criteria, such as described above. In one embodiment wherein the sensor is an implantable glucose sensor, the system waits a predetermined time period believed necessary for sufficient tissue ingrowth and evaluates the sensor sensitivity (e.g., from about one minute to about six weeks). In another embodiment, the receiver determines sufficient stability based on oxygen concentration near the sensor head. In yet another embodiment, the sensor determines sufficient stability based on a reassessment of baseline drift and/or offset. A few examples of determining sufficient stability are given here, however a variety of known tests and parameters can be used to determine sensor stability without departing from the spirit and scope of the preferred embodiments.


If the receiver does not assess that the stability of the sensor is sufficient, then the processing returns to block 261, wherein the receiver receives sensor data such as described in more detail above. The above-described steps are repeated until sufficient stability is determined.


If the receiver does assess that the stability of the sensor is sufficient, then processing continues to block 267 and the calibration set is used to calibrate the sensor.


At block 267, the conversion function module uses the calibration set to create a conversion function. The conversion function substantially defines the relationship between the reference analyte data and the analyte sensor data.


A variety of known methods can be used with the preferred embodiments to create the conversion function from the calibration set. In one embodiment, wherein a plurality of matched data points form the initial calibration set, a linear least squares regression is performed on the initial calibration set such as described with reference to FIG. 14A.



FIG. 22A is a graph that illustrates a regression performed on a calibration set to create a conversion function in one exemplary embodiment. In this embodiment, a linear least squares regression is performed on the initial calibration set. The x-axis represents reference analyte data; the y-axis represents sensor data. The graph pictorially illustrates regression of the matched pairs 276 in the calibration set. Regression calculates a slope 272 and an offset 274 (y=mx+b), which defines the conversion function.


In alternative embodiments other algorithms could be used to determine the conversion function, for example forms of linear and non-linear regression, for example fuzzy logic, neural networks, piece-wise linear regression, polynomial fit, genetic algorithms, and other pattern recognition and signal estimation techniques.


In yet other alternative embodiments, the conversion function can comprise two or more different optimal conversions to account for optimal conversion variability due to dependence on parameters, such as time of day, calories consumed, exercise, or analyte concentration above or below a set threshold, for example. In one such exemplary embodiment, the conversion function is adapted for the estimated glucose concentration (e.g., high vs. low). For example, in an implantable glucose sensor, it has been observed that the cells surrounding the implant will consume at least a small amount of glucose as it diffuses toward the glucose sensor. Assuming the cells consume substantially the same amount of glucose whether the glucose concentration is low or high, this phenomenon will have a greater effect on the concentration of glucose during low blood sugar episodes than the effect on the concentration of glucose during relatively higher blood sugar episodes. Accordingly, the conversion function is adapted to compensate for the sensitivity differences in blood sugar level. In one implementation, the conversion function comprises two different regression lines wherein a first regression line is applied when the estimated blood glucose concentration is at or below a certain threshold (e.g., 150 mg/dL) and a second regression line is applied when the estimated blood glucose concentration is at or above a certain threshold (e.g., 150 mg/dL). In one alternative implementation, a predetermined pivot of the regression line that forms the conversion function can be applied when the estimated blood is above or below a set threshold (e.g., 150 mg/dL), wherein the pivot and threshold are determined from a retrospective analysis of the performance of a conversion function and its performance at a range of glucose concentrations. In another implementation, the regression line that forms the conversion function is pivoted about a point in order to comply with clinical acceptability standards (e.g., Clarke Error Grid, Consensus Grid, mean absolute relative difference, or other clinical cost function). Although only a few example implementations are described, the preferred embodiments contemplate numerous implementations where the conversion function is adaptively applied based on one or more parameters that can affect the sensitivity of the sensor data over time.


In some alternative embodiments, the sensor is calibrated with a single-point through the use of a dual-electrode system to simplify sensor calibration. In one such dual-electrode system, a first electrode functions as a hydrogen peroxide sensor including a membrane system containing glucose-oxidase disposed thereon, which operates as described herein. A second electrode is a hydrogen peroxide sensor that is configured similar to the first electrode, but with a modified membrane system (with the enzyme domain removed, for example). This second electrode provides a signal composed mostly of the baseline signal, b.


In some dual-electrode systems, the baseline signal is (electronically or digitally) subtracted from the glucose signal to obtain a glucose signal substantially without baseline. Accordingly, calibration of the resultant difference signal can be performed by solving the equation y=mx with a single paired measurement. Calibration of the implanted sensor in this alternative embodiment can be made less dependent on the values/range of the paired measurements, less sensitive to error in manual blood glucose measurements, and can facilitate the sensor's use as a primary source of glucose information for the user. U.S. Publication No. US-2005-0143635-A1 describes systems and methods for subtracting the baseline from a sensor signal.


In some alternative dual-electrode system embodiments, the analyte sensor is configured to transmit signals obtained from each electrode separately (e.g., without subtraction of the baseline signal). In this way, the receiver can process these signals to determine additional information about the sensor and/or analyte concentration. For example, by comparing the signals from the first and second electrodes, changes in baseline and/or sensitivity can be detected and/or measured and used to update calibration (e.g., without the use of a reference analyte value). In one such example, by monitoring the corresponding first and second signals over time, an amount of signal contributed by baseline can be measured. In another such example, by comparing fluctuations in the correlating signals over time, changes in sensitivity can be detected and/or measured.


In some alternative embodiments, a regression equation y=mx+b is used to calculate the conversion function; however, prior information can be provided for m and/or b, thereby enabling calibration to occur with fewer paired measurements. In one calibration technique, prior information (e.g., obtained from in vivo or in vitro tests) determines a sensitivity of the sensor and/or the baseline signal of the sensor by analyzing sensor data from measurements taken by the sensor (e.g., prior to inserting the sensor). For example, if there exists a predictive relationship between in vitro sensor parameters and in vivo parameters, then this information can be used by the calibration procedure. For example, if a predictive relationship exists between in vitro sensitivity and in vivo sensitivity, m≈f(minin vitro), then the predicted m can be used, along with a single matched pair, to solve for b (b=y−mx). If, in addition, b can be assumed to be 0, for example with a dual-electrode configuration that enables subtraction of the baseline from the signal such as described above, then both m and b are known a priori, matched pairs are not needed for calibration, and the sensor can be completely calibrated e.g. without the need for reference analyte values (e.g. values obtained after implantation in vivo.)


In another alternative embodiment, prior information can be provided to guide or validate the baseline (b) and/or sensitivity (m) determined from the regression analysis. In this embodiment, boundaries can be set for the regression line that defines the conversion function such that working sensors are calibrated accurately and easily (with two points), and non-working sensors are prevented from being calibrated. If the boundaries are drawn too tightly, a working sensor may not enter into calibration. Likewise, if the boundaries are drawn too loosely, the scheme can result in inaccurate calibration or can permit non-working sensors to enter into calibration. For example, subsequent to performing regression, the resulting slope and/or baseline are tested to determine whether they fall within a predetermined acceptable threshold (boundaries). These predetermined acceptable boundaries can be obtained from in vivo or in vitro tests (e.g., by a retrospective analysis of sensor sensitivities and/or baselines collected from a set of sensors/patients, assuming that the set is representative of future data).


If the slope and/or baseline fall within the predetermined acceptable boundaries, then the regression is considered acceptable. Alternatively, if the slope and/or baseline fall outside the predetermined acceptable boundaries, steps can be taken to either correct the regression or fail-safe such that a system will not process or display errant data. This can be useful in situations wherein regression results in errant slope or baseline values. For example, when points (matched pairs) used for regression are too close in value, the resulting regression statistically is less accurate than when the values are spread farther apart. As another example, a sensor that is not properly deployed or is damaged during deployment can yield a skewed or errant baseline signal.



FIG. 22B is a graph that illustrates one example of using prior information for slope and baseline. The x-axis represents reference glucose data (blood glucose) from a reference glucose source in mg/dL; the y-axis represents sensor data from a transcutaneous glucose sensor of the preferred embodiments in counts. An upper boundary line 215 is a regression line that represents an upper boundary of “acceptability” in this example; the lower boundary line 216 is a regression line that represents a lower boundary of “acceptability” in this example. The boundary lines 215, 216 were obtained from retrospective analysis of in vivo sensitivities and baselines of glucose sensors as described in the preferred embodiments.


A plurality of matched data pairs 217 represent data pairs in a calibration set obtained from a glucose sensor as described in the preferred embodiments. The matched data pairs are plotted according to their sensor data and time-corresponding reference glucose data. A regression line 218 represents the result of regressing the matched data pairs 217 using least squares regression. In this example, the regression line falls within the upper and lower boundaries 215, 216 indicating that the sensor calibration is acceptable.


However, if the slope and/or baseline had fallen outside the predetermined acceptable boundaries, which would be illustrated in this graph by a line that crosses the upper and/or lower boundaries 215, 216, then the system may be configured to assume a preset baseline value and re-run the regression (or a modified version of the regression) with the assumed baseline, where the assumed baseline value is derived from in vivo or in vitro testing. Subsequently, the newly derived slope and baseline are again tested to determine whether they fall within the predetermined acceptable boundaries. The processing continues in response to the results of the boundary test in a similar fashion. In general, for a set of matched pairs (e.g., a calibration set), regression lines with higher slope (sensitivity) have a lower baseline while regression lines with lower slope (sensitivity) have a higher baseline. Accordingly, the step of assuming a baseline and testing against boundaries can be repeated using a variety of different assumed baselines based on the baseline, sensitivity, in vitro testing, and/or in vivo testing. For example, if a boundary test fails due to high sensitivity, then a higher baseline is assumed and the regression re-run and boundary-tested. It is preferred that after about two iterations of assuming a baseline and/or sensitivity and running a modified regression, the system assumes an error has occurred (if the resulting regression lines fall outside the boundaries) and fail-safe. The term “fail-safe” includes modifying the system processing and/or display of data responsive to a detected error to avoid reporting of inaccurate or clinically irrelevant analyte values.


In yet another alternative embodiment, information obtained prior to sensor insertion can be provided for selecting the baseline (b) and/or slope (m) determined from the regression analysis. For example, a distribution of slopes and/or baselines typically obtained may be determined (or estimated) from retrospective analysis of a sample set of implanted sensors. This prior distribution information may be used to enable the sensor system to select a preferred combination of slope and/or baseline to be used in calibration.


In some embodiments, when one or more matched pairs are obtained from a sensor implanted in a host (as described elsewhere herein), a plurality of possible calibration lines can be drawn dependent upon the method of utilizing these matched pairs to draw a calibration line. For example, where only a single matched pair is obtained, numerous calibration lines having various baselines and slopes may be drawn through the single matched pair. The single matched pair alone does not provide enough information to determine the best calibration line. Similarly, where multiple matched pairs are obtained that are clustered closely together, numerous calibration lines may be drawn that pass close to all of the matched pairs in the cluster (e.g., numerous calibration lines are similarly correlated with the matched pairs). In some circumstances, some of these multiple calibration lines may not represent the best calibration (e.g., due to error in the reference glucose, small distribution of pairs, only one matched pair, and the like). Accordingly, in one embodiment, prior information regarding the typical distribution of slopes and/or baselines may be used to select one of the multiple calibration lines.


In one embodiment, a baseline can be selected, during calibration, based on the prior distribution information described above (e.g., by selecting the most probable baseline from the distribution of baselines). In another embodiment, a slope can be selected, during calibration, based on the prior distribution information described above (e.g., by selecting the most probable slope from the distribution of slopes). In a preferred embodiment, both a baseline and slope are selected, during calibration, based on the prior distribution information described above. For example, in one embodiment, of the possible multiple calibration lines, the calibration line is chosen that has a slope and baseline closest to the maximum joint probability of both the slope and baseline distributions. In some embodiments, preference may be given to either the slope or baseline such that having either a slope or baseline closer to its most probable value is weighted more heavily.


In one embodiment, depicted in FIG. 22C, the slope and baseline closest to the maximum joint probability may be determined geometrically (e.g., when both the slope and baseline have normal distributions). In FIG. 22C, each slope and baseline determined (or estimated) from retrospective analysis is plotted as a matched pair 230 in a slope-baseline plot. The set of matched pairs 230 form a cloud distribution, with the center of highest density corresponding to the highest probability of slope and baseline combination. The set of possible calibration lines for the sensor to be calibrated (e.g., from regression of a single matched pair or set of closely spaced matched pairs) make up a line 232 in the slope-baseline plot. In one embodiment, the point on this line 234 closest to the center of highest matched pair 230 density may be chosen as providing the slope and baseline of the selected calibration line. Either the slope or the baseline probabilities may be given preference by scaling the cloud distribution along either the baseline or slope axes.


The use of prior distribution information may be extended to more complex cases. For example, in some embodiments, the desired calibration curve is not linear (e.g., it has three or more parameters). In such cases, the most probable set of parameters (e.g., based on the prior distributions) the still correlates with the calibration data may be used to define the calibration curve.


In these various embodiments, utilizing an additional electrode, prior information (e.g., in vitro or in vivo testing), signal processing, or other information for assisting in the calibration process can be used alone or in combination to reduce or eliminate the dependency of the calibration on reference analyte values obtained by the host.


Referring again to FIG. 21, at block 268, a sensor data transformation module uses the conversion function to transform sensor data into substantially real-time analyte value estimates, also referred to as calibrated data, as sensor data is continuously (or intermittently) received from the sensor. For example, in the embodiment of FIG. 22A, the sensor data, which can be provided to the receiver in “counts,” is translated to estimate analyte value(s) in mg/dL. In other words, the offset value at any given point in time can be subtracted from the raw value (e.g., in counts) and divided by the slope to obtain the estimated analyte value:







mg
/
dL

=


(

rawvalue
-
offset

)

slope





In some alternative embodiments, the sensor and/or reference analyte values are stored in a database for retrospective analysis.


At block 269, an output module provides output to the user via the user interface. The output is representative of the estimated analyte value, which is determined by converting the sensor data into a meaningful analyte value such as described in more detail with reference to block 268, above. User output can be in the form of a numeric estimated analyte value, an indication of directional trend of analyte concentration, and/or a graphical representation of the estimated analyte data over a period of time, for example. Other representations of the estimated analyte values are also possible, for example audio and tactile. Accordingly, after initial calibration of the sensor, and possibly determination of stability of the sensor data, real-time continuous analyte information can be displayed on the user interface so that the user can regularly and proactively care for his/her diabetic condition within the bounds set by his/her physician.


In alternative embodiments, the conversion function is used to predict analyte values at future points in time. These predicted values can be used to alert the user of upcoming hypoglycemic or hyperglycemic events. Additionally, predicted values can be used to compensate for the time lag (e.g., 15 minute time lag such as described elsewhere herein), so that an estimate analyte value displayed to the user represents the instant time, rather than a time delayed estimated value.


In some embodiments, the substantially real time estimated analyte value, a predicted future estimate analyte value, a rate of change, and/or a directional trend of the analyte concentration is used to control the administration of a constituent to the user, including an appropriate amount and time, in order to control an aspect of the user's biological system. One such example is a closed loop glucose sensor and insulin pump, wherein the analyte data (e.g., estimated glucose value, rate of change, and/or directional trend) from the glucose sensor is used to determine the amount of insulin, and time of administration, that can be given to a diabetic user to evade hyper- and hypoglycemic conditions.


The conventional analyte meters (e.g., self-monitored blood analyte tests) are known to have a +−20% error in analyte values. For example, gross errors in analyte readings are known to occur due to patient error in self-administration of the blood analyte test. In one such example, if the user has traces of sugar on his/her finger while obtaining a blood sample for a glucose concentration test, then the measured glucose value will likely be much higher than the actual glucose value in the blood. Additionally, it is known that self-monitored analyte tests (e.g., test strips) are occasionally subject to manufacturing error.


Another cause for error includes infrequency and time delay that can occur if a user does not self-test regularly, or if a user self-tests regularly but does not enter the reference value at the appropriate time or with the appropriate time stamp. Providing reference data using a substantially continuous sensor overcomes those errors associated with irregular self-tests. To ensure the validity of the sensor data, the receiver can be configured to evaluate the clinical acceptability of received reference analyte data prior to their acceptance as a valid reference value.


In one embodiment, the reference analyte data (and/or sensor analyte data) is evaluated with respect to substantially time corresponding sensor data (and/or substantially time corresponding reference analyte data) to determine the clinical acceptability of the reference analyte and/or sensor analyte data. Clinical acceptability considers a deviation between time corresponding glucose measurements (e.g., data from a glucose sensor and data from a reference glucose monitor) and the risk (e.g., to the decision making of a diabetic patient) associated with that deviation based on the glucose value indicated by the sensor and/or reference data. Evaluating the clinical acceptability of reference and sensor analyte data, and controlling the user interface dependent thereon, can minimize clinical risk.


In one embodiment, the receiver evaluates clinical acceptability each time reference data is obtained. In another embodiment, the receiver evaluates clinical acceptability after the initial calibration and stabilization of the sensor, such as described with reference to FIG. 21, above. In some embodiments, the receiver evaluates clinical acceptability as an initial pre-screen of reference analyte data, for example after determining if the reference glucose measurement is from about 40 to about 400 mg/dL. In other embodiments, other methods of pre-screening data can be used, for example by determining if a reference analyte data value is physiologically feasible based on previous reference analyte data values (e.g., below a maximum rate of change).


After initial calibration such as described in more detail with reference to FIG. 21, the sensor data receiving module 261 receives substantially continuous sensor data (e.g., a data stream) via a receiver and converts that data into estimated analyte values. As used herein, “substantially continuous” is broad enough to include a data stream of individual measurements taken at time intervals (e.g., time-spaced) of from fractions of a second up to, e.g., 1, 2, or 5 minutes. As sensor data is continuously converted, it can be occasionally recalibrated such as described in more detail below with reference to FIG. 24. Initial calibration and re-calibration of the sensor requires a reference analyte value. Accordingly, the receiver can receive reference analyte data at any time for appropriate processing. These reference analyte values can be evaluated for clinical acceptability such as described below as a fail-safe against reference analyte test errors.


In some embodiments, the reference data is pre-screened according to environmental and physiological issues, such as time of day, oxygen concentration, postural effects, and patient-entered environmental data. In one example embodiment, wherein the sensor comprises an implantable glucose sensor, an oxygen sensor within the glucose sensor is used to determine if sufficient oxygen is being provided to successfully complete the necessary enzyme and electrochemical reactions for glucose sensing. In another example embodiment wherein the sensor comprises an implantable glucose sensor, the counter electrode could be monitored for a “rail-effect”, that is, when insufficient oxygen is provided at the counter electrode causing the counter electrode to reach operational (e.g., circuitry) limits.


In some embodiments, a clinical acceptability evaluation module in the receiver (not shown), also referred to as a clinical module, evaluates newly received reference data and/or time corresponding sensor data. In some embodiments of evaluating clinical acceptability, the rate of change of the reference data as compared to previous data is assessed for clinical acceptability. That is, the rate of change and acceleration (or deceleration) of many analytes has certain physiological limits within the body. Accordingly, a limit can be set to determine if the new matched pair is within a physiologically feasible range, indicated by a rate of change from the previous data that is within known physiological and/or statistical limits. Similarly, in some embodiments any algorithm that predicts a future value of an analyte can be used to predict and then compare an actual value to a time corresponding predicted value to determine if the actual value falls within a clinically acceptable range based on the predictive algorithm, for example.


In one exemplary embodiment, the clinical acceptability evaluation module matches the reference data with a substantially time corresponding converted sensor value such as described with reference to FIG. 21 above, and plots the matched data on a Clarke Error Grid such as described in more detail with reference to FIG. 23.



FIG. 23 is a graph of two data pairs on a Clarke Error Grid to illustrate the evaluation of clinical acceptability in one exemplary embodiment. The Clarke Error Grid can be used by the clinical acceptability evaluation module to evaluate the clinical acceptability of the disparity between a reference glucose value and a sensor glucose (e.g., estimated glucose) value, if any, in an embodiment wherein the sensor is a glucose sensor. The x-axis represents glucose reference glucose data and the y-axis represents estimated glucose sensor data. Matched data pairs are plotted accordingly to their reference and sensor values, respectively. In this embodiment, matched pairs that fall within the A and B regions of the Clarke Error Grid are considered clinically acceptable, while matched pairs that fall within the C, D, and E regions of the Clarke Error Grid are not considered clinically acceptable. Particularly, FIG. 23 shows a first matched pair 1992 is shown which falls within the A region of the Clarke Error Grid, therefore is it considered clinically acceptable. A second matched pair 94 is shown which falls within the C region of the Clarke Error Grid, therefore it is not considered clinically acceptable. Further description of evaluating reference data for its clinical acceptability is included in U.S. Publication No. US-2005-0027180-A1.


Reference is now made to FIG. 24, which is a flow chart that illustrates the process of evaluation of calibration data for best calibration based on inclusion criteria of matched data pairs in one embodiment.


Calibration of analyte sensors can be variable over time; that is, the conversion function suitable for one point in time may not be suitable for another point in time (e.g., hours, days, weeks, or months later). For example, in an embodiment wherein the analyte sensor is subcutaneously implantable, the maturation of tissue ingrowth over time can cause variability in the calibration of the analyte sensor. As another example, physiological changes in the user (e.g., metabolism, interfering blood constituents, lifestyle changes) can cause variability in the calibration of the sensor. Accordingly, a continuously updating calibration algorithm is disclosed that includes reforming the calibration set, and thus recalculating the conversion function, over time according to a set of inclusion criteria.


At block 101, the reference data receiving module, also referred to as the reference input module, receives one or more new reference analyte values (e.g., data point) from the reference analyte source. In some embodiments, the reference analyte value can be pre-screened according to criteria such as described in more detail with reference to FIG. 21, block 62. In some embodiments, the reference analyte values can be evaluated for clinical acceptability such as described in more detail with reference to FIG. 23.


At block 102, the data matching module, also referred to as the processor module, forms one or more updated matched data pairs by matching new reference data to substantially time corresponding sensor data, such as described in more detail with reference to FIG. 21, block 63.


At block 103, a calibration evaluation module evaluates the new matched pair(s) inclusion into the calibration set. In some embodiments, the receiver simply adds the updated matched data pair into the calibration set, displaces the oldest and/or least concordant matched pair from the calibration set, and proceeds to recalculate the conversion function accordingly (block 105).


In some embodiments, the calibration evaluation includes evaluating only the new matched data pair. In some embodiments, the calibration evaluation includes evaluating all of the matched data pairs in the existing calibration set and including the new matched data pair; in such embodiments not only is the new matched data pair evaluated for inclusion (or exclusion), but additionally each of the data pairs in the calibration set are individually evaluated for inclusion (or exclusion). In some alternative embodiments, the calibration evaluation includes evaluating all possible combinations of matched data pairs from the existing calibration set and including the new matched data pair to determine which combination best meets the inclusion criteria. In some additional alternative embodiments, the calibration evaluation includes a combination of at least two of the above-described embodiments.


Inclusion criteria comprise one or more criteria that define a set of matched data pairs that form a substantially optimal calibration set. One inclusion criterion comprises ensuring the time stamp of the matched data pairs (that make up the calibration set) span at least a set time period (e.g., three hours). Another inclusion criterion comprises ensuring that the time stamps of the matched data pairs are not more than a set age (e.g., one week old). Another inclusion criterion ensures that the matched pairs of the calibration set have a substantially distributed amount of high and low raw sensor data, estimated sensor analyte values, and/or reference analyte values. Another criterion comprises ensuring all raw sensor data, estimated sensor analyte values, and/or reference analyte values are within a predetermined range (e.g., 40 to 400 mg/dL for glucose values). Another criterion comprises evaluating the rate of change of the analyte concentration (e.g., from sensor data) during the time stamp of the matched pair(s). For example, sensor and reference data obtained during the time when the analyte concentration is undergoing a slow rate of change can be less susceptible inaccuracies caused by time lag and other physiological and non-physiological effects. Another criterion comprises evaluating the congruence of respective sensor and reference data in each matched data pair; the matched pairs with the most congruence can be chosen. Another criterion comprises evaluating physiological changes (e.g., low oxygen due to a user's posture that can effect the function of a subcutaneously implantable analyte sensor, or other effects such as described with reference to FIG. 21) to ascertain a likelihood of error in the sensor value. Valuation of calibration set criteria can comprise evaluating one, some, or all of the above described inclusion criteria. It is contemplated that additional embodiments can comprise additional inclusion criteria not explicitly described herein.


At block 104, the evaluation of the calibration set determines whether to maintain the previously established calibration set, or if the calibration set can be updated (e.g., modified) with the new matched data pair. In some embodiments, the oldest matched data pair is simply displaced when a new matched data pair is included. A new calibration set can include not only the determination to include the new matched data pair, but in some embodiments, can also determine which of the previously matched data pairs can be displaced from the calibration set.


At block 105, the conversion function module recreates the conversion function using the modified calibration set. The calculation of the conversion function is described in more detail with reference to FIG. 21.


At block 106, the sensor data transformation module converts sensor data to calibrated data using the updated conversion function. Conversion of raw sensor data into estimated analyte values is described in more detail with reference to FIG. 21.


Reference is now made to FIG. 25, which is a flow chart that illustrates the process of evaluating the quality of the calibration in one embodiment. The calibration quality can be evaluated by determining the statistical association of data that forms the calibration set, which determines the confidence associated with the conversion function used in calibration and conversion of raw sensor data into estimated analyte values.


In one embodiment calibration quality can be evaluated after initial or updated calculation of the conversion function such as described elsewhere herein. However, calibration quality can be performed at any time during the data processing.


At block 111, a sensor data receiving module, also referred to as the sensor data module, receives the sensor data from the sensor such as described in more detail with reference to FIG. 21.


At block 112, a reference data receiving module, also referred to as the reference input module, receives reference data from a reference analyte source, such as a substantially continuous analyte monitor, and as described in more detail with reference to FIG. 21.


At block 113, the data matching module, also referred to as the processor module, matches received reference data with substantially time corresponding sensor data to provide one or more matched data pairs, such as described in more detail with reference to FIG. 21.


At block 114, the calibration set module, also referred to as the processor module, forms a calibration set from one or more matched data pairs such as described in more detail with reference to FIGS. 21 and 24.


At block 115, the conversion function module calculates a conversion function using the calibration set, such as described in more detail with reference to FIGS. 21 and 16.


At block 116, the sensor data transformation module continuously (or intermittently) converts received sensor data into estimated analyte values, also referred to as calibrated data, such as described in more detail with reference to FIGS. 21 and 24.


At block 117, a quality evaluation module evaluates the quality of the calibration. In one embodiment, the quality of the calibration is based on the association of the calibration set data using statistical analysis. Statistical analysis can comprise any known cost function such as linear regression, non-linear mapping/regression, rank (e.g., non-parametric) correlation, least mean square fit, mean absolute deviation (MAD), mean absolute relative difference, and the like. The result of the statistical analysis provides a measure of the association of data used in calibrating the system. A threshold of data association can be set to determine if sufficient quality is exhibited in a calibration set.


In another embodiment, the quality of the calibration is determined by evaluating the calibration set for clinical acceptability, such as described with reference to blocks 82 and 83 (e.g., Clarke Error Grid. Consensus Grid, or clinical acceptability test). As an example, the matched data pairs that form the calibration set can be plotted on a Clarke Error Grid, such that when all matched data pairs fall within the A and B regions of the Clarke Error Grid, then the calibration is determined to be clinically acceptable.


In yet another alternative embodiment, the quality of the calibration is determined based initially on the association of the calibration set data using statistical analysis, and then by evaluating the calibration set for clinical acceptability. If the calibration set fails the statistical and/or the clinical test, the processing returns to block 115 to recalculate the conversion function with a new (e.g., optimized) set of matched data pairs. In this embodiment, the processing loop (block 115 to block 117) iterates until the quality evaluation module 1) determines clinical acceptability, 2) determines sufficient statistical data association, 3) determines both clinical acceptability and sufficient statistical data association, or 4) surpasses a threshold of iterations; after which the processing continues to block 118.



FIGS. 26A and 26B illustrate one exemplary embodiment wherein the accuracy of the conversion function is determined by evaluating the correlation coefficient from linear regression of the calibration set that formed the conversion function. In this exemplary embodiment, a threshold (e.g., 0.79) is set for the R-value obtained from the correlation coefficient.



FIGS. 26A and 26B are graphs that illustrate an evaluation of the quality of calibration based on data association in one exemplary embodiment using a correlation coefficient. Particularly, FIGS. 26A and 26B pictorially illustrate the results of the linear least squares regression performed on a first and a second calibration set (FIGS. 26A and 26B, respectively). The x-axis represents reference analyte data; the y-axis represents sensor data. The graph pictorially illustrates regression that determines the conversion function.


The regression line (and thus the conversion function) formed by the regression of the first calibration set of FIG. 26A is the same as the regression line (and thus the conversion function) formed by the regression of the second calibration set of FIG. 26B. However, the correlation of the data in the calibration set to the regression line in FIG. 26A is significantly different than the correlation of the data in the calibration set to the regression line in FIG. 26A. In other words, there is a noticeably greater deviation of the data from the regression line in FIG. 26B than the deviation of the data from the regression line in FIG. 26A.


In order to quantify this difference in correlation, an R-value can be used to summarize the residuals (e.g., root mean square deviations) of the data when fitted to a straight line via least squares method, in this exemplary embodiment. R-value can be calculated according to the following equation:






R
=




i




(


x
i

-

x
_


)



(


y
i

-

y
_


)








i




(


x
i

-
x

)

2











i



y
i


-
y

)

2









In the above equation: i is an index (1 to n), x is a reference analyte value, y is a sensor analyte value, x is an average of 1/n reference analyte values, and y is an average of 1/n sensor analyte values.


In the exemplary calibration set shown in FIG. 26A, the calculated R-value is about 0.99, which can also be expressed as the correlation coefficient of regression. Accordingly, the calibration exhibits sufficient data association (and thus insufficient quality) because it falls above the 0.79 threshold set in this exemplary embodiment.


In the exemplary calibration set shown in FIG. 26B, the calculated R-value is about 0.77, which can also be expressed as the correlation coefficient of regression. Accordingly, the calibration exhibits insufficient data association (and thus insufficient quality) because it falls below the 0.79 threshold set in this exemplary embodiment.


Reference is again made to FIG. 25, at block 118, the interface control module, also referred to as the fail-safe module, controls the user interface based upon the quality of the calibration. If the calibration is exhibits sufficient quality, then the then the first reference analyte value is discarded, and the repeated reference analyte value is accepted the process continues, and the user interface can function as normal; that is providing output for the user such as described in more detail with reference to FIG. 21. If however the calibration is not deemed sufficient in quality, then fail-safe module begins the initial stages of fail-safe mode, which are described in more detail in U.S. Publication No. US-2005-0027463-A1.


Example I

As described above, benchtop testing of a sensor prior to insertion can be used to calibrate sensor data after the sensor is inserted. FIG. 27 shows in-vivo sensitivity (as calculated using retrospective calibration) vs. in-vitro sensitivity (collected prior to implant), of 16 short term sensors implanted in humans. Least-squares regression was used to define the predictive relationship between in-vitro and in-vivo sensitivities (e.g., min vivo=2.99*min vitro+26.62), as shown in FIG. 27. This relationship was applied to a sensor used in the above-described experiment. The comparison of blood glucose values with the in-vitro calibrated sensor is shown in FIGS. 28 and 29. Predicted in-vivo sensitivity was assumed for calibration throughout the first day. The mean absolute relative difference found across 43 matched pairs over 3 days was 20.17%. In-vivo sensitivity is usually greater than in-vitro sensitivity (typically 2-3× higher). This may be due to enhanced transport of glucose when the membranes interact with molecules in the tissues, such as proteins or lipid in the interstitial fluid.


Example II

In this example, one substantially continuous glucose sensor was used to calibrate another substantially continuous glucose sensor, where both sensors were used in the same host. The data specifically illustrates the use of a short-term (e.g., transcutaneous) sensor to calibrate a long term (e.g., implantable) sensor, but the methods described are applicable to other combinations, including (1) use of a short-term sensor to calibrate another short term sensor; (2) use of a long-term sensor to calibrate another long-term sensor. (3) use of a long term sensor to calibrate a short term sensor.


As discussed herein, calibration of an enzyme-electrode based glucose sensor consists of solving the line

y=mx+b

for m and b, where y denotes the sensor signal (in units of A/D counts), x the estimated glucose concentration (mg/dl), m the sensor sensitivity to glucose (counts/mg/dl), and b the baseline signal unrelated to glucose (counts). If two glucose sensors are used concurrently in the same host, and one sensor is calibrated, the time-corresponding glucose values (x) from the calibrated sensor can be matched to the signal values (y) of the un-calibrated sensor. These matched pairs are then used to draw the calibration line for the second sensor using a regression relationship (e.g. ordinary least-squares).


In this example, a short term substantially continuous sensor was employed in a host in which a long term sensor was already implanted. The data from the substantially continuous short term sensor was used to run a prospective calibration on the substantially continuous long term sensor. Referring to FIG. 30, a plurality of data points (e.g., about 20) from the short term sensor (referred to in FIG. 30 as “STS” and depicted with a diamond symbol) were used as reference data to calibrate the sensor data from the long term sensor (referred to in FIG. 30 as “LTS” and depicted with a dot symbol). The top graph in FIG. 30 shows sensor data (counts (left y-axis)) from an un-calibrated long term sensor and sensor data (glucose measurements (right y-axis)) from a calibrated short term sensor. The top graph in FIG. 30 shows roughly 6 days of un-calibrated long term sensor data for a particular host. On day five, a calibrated short term sensor was employed on the same host. The lower graph in FIG. 30 shows a close-up of the overlay of the sensor data from the long term sensor and, beginning on day five, the sensor data from the short term sensor.


After matching time-corresponding sensor values from the short term sensor data and the long term sensor data, a regression analysis yielded a result for (m, b) of (134.24, 11922.53), with 5 min time-lag of the long term sensor relative to short term sensor. When this calibration was prospectively applied to the long term sensor on day 6, the (calibrated) long term sensor glucose values were compared to reference glucose measurements (e.g. meter readings) to demonstrate calibration accuracy, as shown in FIG. 23. In FIG. 31, the long term sensor data is referred to as “LTS” and depicted as small dots, and the reference glucose measurements (self-monitoring blood glucose) are referred to as “SMBG” and depicted with large ovals. The results show the accuracy of the short term sensor calibration. Further improvement in accuracy would likely result if more points were used.


Comparison of the proposed calibration scheme (long term sensor calibration based on short term sensor) vs. a conventional scheme, for example, a 6-pt moving window regression, using 2/day self-monitoring blood glucose (SMBG) is shown in the Table 1.









TABLE 1







Calibration long term sensor calibration schemes:


retrospective, with SMBG, and with short term sensor.










Calibration

With SMBG
With


Scheme
Retrospective
(conventional)
STS













m
127.12
197.38
134.24


b
12196.48
13508.15
11922.53









The results suggest that calibration of a long term sensor with a short term sensor can be more accurate than with 2/day SMBG. The m and b found with short term sensor based calibration are closer to the values found with retrospective calibration (‘gold standard’) than with 2/day SMBG.


Example III

Referring now to FIG. 32, in this example, sensor data from a short term analyte sensor was used to calibrate a subsequently employed short term sensor. Short term data was collected over a two and a half-day time period from a substantially continuous short term sensor employed on a human host. Finger stick glucose measurements (referred to in FIG. 32 as “Calpts” and depicted with large round dots) were used to calibrate Sensor No. 1. Glucose values (read off of the left y-axis) were derived from the Calibrated Sensor No. 1 sensor data. The Calibrated Sensor No. 1 data is referred to in FIG. 32 as “Calglucose 1” and depicted as small dots.


On Day 3, a second substantially continuous short term sensor (referred to in FIG. 32 as “Sensor2”) was employed on the same host as Sensor No. 1, and sensor data was collected about every 5 minutes for one day (e.g., 288 data points). Digital count data (read off of the right y-axis) from the Sensor No. 2 is depicted in FIG. 32 as diamonds.


Using the glucose values resulting from the data of Sensor No. 1, the sensor data from Sensor No. 2 was calibrated using a retrospective calibration analysis, i.e., least squares regression correlation coefficient, and evaluated using a mean absolute relative difference (MARD). The results of the regression are illustrated in FIG. 33, which shows 288 digital count data points from Sensor No. 2 matched to glucose values from Sensor No. 1 at corresponding times. The regression data was then prospectively applied to the data collected by Sensor No. 2 on Day 4. The Calibrated Sensor 2 data is depicted in FIG. 32 as medium-sized round dots and referred to in FIG. 32 as “Calglucose2.” After one day, a finger stick glucose measurement was taken at about 12:00:00. The sensor data from FIG. 32 closely corresponded to the glucose measurement from the finger stick glucose measurement.


Methods and devices that are suitable for use in conjunction with aspects of the preferred embodiments are disclosed in U.S. Pat. Nos. 4,994,167; 4,757,022; 6,001,067; 6,741,877; 6,702,857; 6,558,321; 6,931,327; and 6,862,465.


Methods and devices that are suitable for use in conjunction with aspects of the preferred embodiments are disclosed in U.S. Publication No. US-2005-0176136-A1; U.S. Publication No. US-2005-0251083-A1; U.S. Publication No. US-2005-0143635-A1; U.S. Publication No. US-2005-0181012-A1; U.S. Publication No. US-2005-0177036-A1; U.S. Publication No. US-2005-0124873-A1; U.S. Publication No. US-2005-0051440-A1; U.S. Publication No. US-2005-0115832-A1; U.S. Publication No. US-2005-0245799-A1; U.S. Publication No. US-2005-0245795-A1; U.S. Publication No. US-2005-0242479-A1; U.S. Publication No. US-2005-0182451-A1; U.S. Publication No. US-2005-0056552-A1; U.S. Publication No. US-2005-0192557-A1; U.S. Publication No. US-2005-0154271-A1; U.S. Publication No. US-2004-0199059-A1; U.S. Publication No. US-2005-0054909-A1; U.S. Publication No. US-2005-0112169-A1; U.S. Publication No. US-2005-0051427-A1; U.S. Publication No. US-2003-0032874-A1; U.S. Publication No. US-2005-0103625-A1; U.S. Publication No. US-2005-0203360-A1; U.S. Publication No. US-2005-0090607-A1; U.S. Publication No. US-2005-0187720-A1; U.S. Publication No. US-2005-0161346-A1; U.S. Publication No. US-2006-0015020-A1; U.S. Publication No. US-2005-0043598-A1; U.S. Publication No. US-2003-0217966-A1; U.S. Publication No. US-2005-0033132-A1; U.S. Publication No. US-2005-0031689-A1; U.S. Publication No. US-2004-0045879-A1; U.S. Publication No. US-2004-0186362-A1; U.S. Publication No. US-2005-0027463-A1; U.S. Publication No. US-2005-0027181-A1; U.S. Publication No. US-2005-0027180-A1; U.S. Publication No. US-2006-0020187-A1; U.S. Publication No. US-2006-0036142-A1; U.S. Publication No. US-2006-0020192-A1; U.S. Publication No. US-2006-0036143-A1; U.S. Publication No. US-2006-0036140-A1; U.S. Publication No. US-2006-0019327-A1; U.S. Publication No. US-2006-0020186-A1; U.S. Publication No. US-2006-0020189-A1; U.S. Publication No. US-2006-0036139-A1; U.S. Publication No. US-2006-0020191-A1; U.S. Publication No. US-2006-0020188-A1; U.S. Publication No. US-2006-0036141-A1; U.S. Publication No. US-2006-0020190-A1; U.S. Publication No. US-2006-0036145-A1; U.S. Publication No. US-2006-0036144-A1; and U.S. Publication No. US-2006-0016700-A1.


Methods and devices that are suitable for use in conjunction with aspects of the preferred embodiments are disclosed in U.S. application Ser. No. 09/447,227 filed Nov. 22, 1999 and entitled “DEVICE AND METHOD FOR DETERMINING ANALYTE LEVELS”; U.S. application Ser. No. 11/280,672 filed Nov. 16, 2005, and entitled “TECHNIQUES TO IMPROVE POLYURETHANE MEMBRANES FOR IMPLANTABLE GLUCOSE SENSORS”; U.S. application Ser. No. 11/280,102 filed Nov. 16, 2005, and entitled “TECHNIQUES TO IMPROVE POLYURETHANE MEMBRANES FOR IMPLANTABLE GLUCOSE SENSORS”; U.S. application Ser. No. 11/201,445 filed Aug. 10, 2005 and entitled “SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA”; U.S. application Ser. No. 11/335,879 filed Jan. 18, 2006 and entitled “CELLULOSIC-BASED INTERFERENCE DOMAIN FOR AN ANALYTE SENSOR”; U.S. application Ser. No. 11/334,876 filed Jan. 18, 2006 and entitled “TRANSCUTANEOUS ANALYTE SENSOR”; U.S. application Ser. No. 11/333,837 filed Jan. 17, 2006 and entitled “LOW OXYGEN IN VIVO ANALYTE SENSOR”.


All references cited herein, including but not limited to published and unpublished applications, patents, and literature references are incorporated herein by reference in their entirety and are hereby made a part of this specification. To the extent publications and patents or patent applications incorporated by reference contradict the disclosure contained in the specification, the specification is intended to supersede and/or take precedence over any such contradictory material.


The term “comprising” as used herein is synonymous with “including,” “containing,” or “characterized by,” and is inclusive or open-ended and does not exclude additional, unrecited elements or method steps.


All numbers expressing quantities of ingredients, reaction conditions, and so forth used in the specification are to be understood as being modified in all instances by the term “about.” Accordingly, unless indicated to the contrary, the numerical parameters set forth herein are approximations that may vary depending upon the desired properties sought to be obtained. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of any claims in any application claiming priority to the present application, each numerical parameter should be construed in light of the number of significant digits and ordinary rounding approaches.


The above description discloses several methods and materials of the present invention. This invention is susceptible to modifications in the methods and materials, as well as alterations in the fabrication methods and equipment. Such modifications will become apparent to those skilled in the art from a consideration of this disclosure or practice of the invention disclosed herein. Consequently, it is not intended that this invention be limited to the specific embodiments disclosed herein, but that it cover all modifications and alternatives coming within the true scope and spirit of the invention.

Claims
  • 1. A glucose monitoring system comprising: a transcutaneous electrochemical glucose sensor comprising: an in vivo portion configured to be inserted into a body of a human host, the in vivo portion having at least one electrode and a membrane containing glucose oxidase; andan ex vivo portion configured to remain outside of the body of the host; andat least one processor programmed to: calculate an in vivo sensitivity for the transcutaneous electrochemical glucose sensor by converting an in vitro sensitivity associated with the transcutaneous electrochemical glucose sensor, wherein the in vitro sensitivity is obtained prior to insertion of the transcutaneous electrochemical glucose sensor, wherein the in vitro sensitivity is different from the in vivo sensitivity; anddetermine an estimated glucose value based on an in vivo measurement from the in vivo portion of the transcutaneous electrochemical glucose sensor and the calculated in vivo sensitivity for the transcutaneous electrochemical glucose sensor,wherein the in vivo sensitivity for the transcutaneous electrochemical glucose sensor is calculated without a need for a reference analyte measurement obtained after insertion of the in vivo portion of the transcutaneous electrochemical glucose sensor into the body of the human host.
  • 2. The system of claim 1 wherein the in vitro sensitivity associated with the transcutaneous electrochemical glucose sensor is a sensitivity measured from a benchtop sensor.
  • 3. The system of claim 2 wherein the benchtop sensor is a second glucose sensor, such that the transcutaneous electrochemical glucose sensor may be calibrated using data from another sensor.
  • 4. The system of claim 1 wherein the determination of the estimated glucose value by the at least one processor comprises use of drift information.
  • 5. The system of claim 1 further comprising a temperature probe, wherein the at least one processor receives a measurement from the temperature probe for add temperature compensation to the estimated glucose value.
  • 6. The system of claim 5 further comprising a housing configured for mounting on the skin of the host, wherein the temperature probe is located in the housing.
  • 7. The system of claim 1 further comprising: a housing configured for mounting on the skin of the human host; anda receiver having a display,wherein the at least one processor comprises a first processor positioned within the housing and a second processor positioned within the receiver.
  • 8. The system of claim 1 wherein the in vivo sensitivity is greater than the in vitro sensitivity.
  • 9. The system of claim 1 wherein the converting the previously obtained in vitro sensitivity to the in vivo sensitivity comprises a linear relationship.
  • 10. The system of claim 1 wherein the reference analyte measurement obtained after insertion is a finger stick blood sample obtained from the human host.
  • 11. The system of claim 1 wherein the membrane comprises a plurality of domains.
  • 12. The system of claim 11 wherein the plurality of domains comprises at least a resistance domain.
  • 13. The system of claim 1 further comprising a housing configured for mounting on the skin of the human host, wherein at least one of the at least one processor is located in the housing.
  • 14. The system of claim 1 further comprising a receiver configured to wirelessly receive the in vivo measurement, wherein at least one of the at least one processor is located in the receiver.
  • 15. The system of claim 1 further comprising a receiver configured to wirelessly receive the estimated glucose value, wherein at least one of the at least one processor is located in the receiver.
  • 16. A glucose monitoring system comprising: a transcutaneous electrochemical glucose sensor comprising: an in vivo portion configured to be inserted into a body of a host, the in vivo portion having at least one electrode and a membrane containing glucose oxidase, andan ex vivo portion configured to remain outside of the body of the host;a memory storing calibration information for the transcutaneous electrochemical glucose sensor, the calibration information generated by applying a predictive relationship for converting sensitivity information obtained prior to insertion of the transcutaneous electrochemical glucose sensor in the host to a different in vivo sensitivity of the transcutaneous electrochemical glucose sensor; anda processor programmed to determine an estimated glucose value by applying the in vivo sensitivity of the transcutaneous electrochemical glucose sensor to an in vivo measurement from the in vivo portion of the transcutaneous electrochemical glucose sensor,wherein the estimated glucose value is determined without any reference glucose concentration measurements obtained after insertion of the in vivo portion of the transcutaneous electrochemical glucose sensor into the body of the host.
  • 17. The system of claim 16 further comprising a temperature probe, wherein the at least one processor is configured to use a measurement from the temperature probe to determine the estimated glucose value.
  • 18. The system of claim 17 wherein the at least one processor is configured to use drift information to determine the estimated glucose value.
  • 19. A glucose monitoring system comprising: a transcutaneous electrochemical glucose sensor comprising: an in vivo portion configured to be inserted into a body of a host, wherein the in vivo portion of the transcutaneous electrochemical glucose sensor comprises an electrode and a membrane comprising glucose oxidase; andan ex vivo portion configured to remain outside the body of the host;a memory storing calibration information for the transcutaneous electrochemical glucose sensor, wherein the stored calibration information is based at least in part on information generated prior to insertion of the in vivo portion of the transcutaneous electrochemical glucose sensor in the host, wherein the stored calibration information is based at least in part on applying a predictive relationship that converts an in vitro sensitivity to glucose to a in vivo sensitivity to glucose, wherein the in vitro sensitivity to glucose is different from the in vivo sensitivity to glucose; anda processor configured to calibrate data derived at least in part from in vivo measurements generated by the transcutaneous electrochemical glucose sensor after insertion of the in vivo portion of the transcutaneous electrochemical glucose sensor in the host, wherein the processor is configured to perform the calibrating based at least in part on the stored calibration information, and wherein the processor is configured to perform the calibrating without requiring calibration information obtained from a reference glucose measurement after insertion of the transcutaneous electrochemical glucose sensor.
  • 20. The system of claim 19, wherein the applying the predictive relationship comprises applying a linear transformation from in vitro sensitivities to glucose to in vivo sensitivities to glucose.
  • 21. The system of claim 19, wherein the calibrating is performed without requiring an in vivo glucose concentration obtained from a finger stick blood sample from the host.
  • 22. The system of claim 21, wherein the calibrating is performed without requiring a matched pair of an in vivo measurement with the transcutaneous electrochemical glucose sensor and an in vivo glucose concentration obtained from a finger stick blood sample from the host.
  • 23. The system of claim 19, wherein the in vitro sensitivity to glucose associated with the transcutaneous electrochemical glucose sensor is derived at least in part from benchtop in vitro testing of the transcutaneous electrochemical glucose sensor.
  • 24. The system of claim 19, wherein the in vitro sensitivity to glucose associated with the transcutaneous electrochemical glucose sensor is derived at least in part from benchtop in vitro testing of at least one other transcutaneous electrochemical glucose sensor.
  • 25. The system of claim 19, wherein the in vivo sensitivity to glucose of the transcutaneous glucose sensor is greater than the in vitro sensitivity to glucose associated with the transcutaneous electrochemical glucose sensor.
  • 26. The system of claim 19, wherein the predictive relationship is derived at least in part from in vivo and in vitro sensitivity experiments performed with other transcutaneous electrochemical glucose sensors.
  • 27. The system of claim 19, wherein the transcutaneous glucose sensor comprises a plurality of membrane layers.
  • 28. The system of claim 27, wherein the plurality of membrane layers comprises a resistance domain layer.
  • 29. The system of claim 19, further comprising a temperature probe.
  • 30. The system of claim 29, wherein the memory and the processor and the temperature probe are associated with an on-skin electronics assembly.
  • 31. The system of claim 29, wherein the temperature probe is on the transcutaneous electrochemical glucose sensor.
  • 32. The system of claim 29, wherein the processor is configured to add temperature compensation to the calibrating.
  • 33. The system of claim 19, comprising: an on-skin sensor electronics module; anda receiver comprising a display, wherein the display is configured to display sensor information.
  • 34. The system of claim 33, wherein the processor is incorporated in the receiver.
  • 35. The system of claim 33, wherein the receiver is configured to trigger a start-up mode for calibrating the sensor at the beginning of a sensor session.
  • 36. A method of making a glucose monitoring system comprising: providing a transcutaneous electrochemical glucose sensor comprising: an in vivo portion configured to be inserted into a body of a host; andan ex vivo portion configured to remain outside the body of the host, wherein the in vivo portion of the transcutaneous electrochemical glucose sensor comprises an electrode and a membrane comprising glucose oxidase, and wherein the transcutaneous electrochemical glucose sensor is associated with an in vitro sensitivity to glucose;applying a predictive relationship to the in vitro sensitivity to glucose to generate an in vivo sensitivity to glucose that is different from the in vitro sensitivity to glucose; andproviding a processor configured to calibrate data derived at least in part from in vivo measurements generated by the transcutaneous electrochemical glucose sensor after insertion of the in vivo portion of the transcutaneous electrochemical glucose sensor in the host, wherein the processor is configured to perform the calibrating based at least in part on the in vivo sensitivity to glucose generated by applying the predictive relationship, and wherein the processor is configured to perform the calibrating without requiring calibration information obtained from a reference glucose measurement after insertion of the transcutaneous electrochemical glucose sensor.
  • 37. The method of claim 36, wherein the in vivo sensitivity to glucose is greater than the in vitro sensitivity to glucose.
  • 38. The method of claim 36, comprising deriving the in vitro sensitivity to glucose associated with the transcutaneous electrochemical glucose sensor at least in part from benchtop in vitro testing of the transcutaneous electrochemical glucose sensor.
  • 39. The method of claim 36, comprising deriving the in vitro sensitivity to glucose associated with the transcutaneous electrochemical glucose sensor at least in part from benchtop in vitro testing of at least one other transcutaneous electrochemical glucose sensor.
INCORPORATED BY REFERENCE TO RELATED APPLICATIONS

Any and all priority claims identified in the Application Data Sheet, or any correction thereto, are hereby incorporated by reference under 37 CFR 1.57. This application is a continuation of U.S. application Ser. No. 17/076,714, filed Oct. 21, 2020, which is a continuation of U.S. application Ser. No. 16/983,885, filed on Aug. 3, 2020, now abandoned, which is a continuation of U.S. application Ser. No. 16/691,107, filed on Nov. 21, 2019, now U.S. Pat. No. 10,898,114, which is a continuation of U.S. application Ser. No. 16/457,628, filed on Jun. 28, 2019, now U.S. Pat. No. 10,610,136, which is a continuation of U.S. application Ser. No. 15/787,595, filed on Oct. 18, 2017, now abandoned, which is a continuation of U.S. application Ser. No. 15/065,623, filed Mar. 9, 2016, now U.S. Pat. No. 9,918,668, which is a continuation of U.S. application Ser. No. 13/607,162, filed on Sep. 7, 2012, now U.S. Pat. No. 9,314,196, which is a continuation of U.S. application Ser. No. 12/683,755, filed Jan. 7, 2010, now U.S. Pat. No. 8,611,978, which is a continuation of U.S. application Ser. No. 11/373,628, filed on Mar. 9, 2006, now U.S. Pat. No. 7,920,906, which claims the benefit of U.S. Provisional Application No. 60/660,743, filed on Mar. 10, 2005. Each of the aforementioned applications is incorporated by reference herein in its entirety, and each is hereby expressly made a part of this specification.

US Referenced Citations (2567)
Number Name Date Kind
52641 Gates Feb 1866 A
62334 Holmes Feb 1867 A
65604 Reynolds Jun 1867 A
1498738 Gustave et al. Jun 1924 A
1564641 St. James et al. Dec 1925 A
1726766 Rector Sep 1929 A
2057029 McC. Johnstone et al. Oct 1936 A
2402306 Henry et al. Jun 1946 A
2497894 Clare et al. Feb 1950 A
2719797 Rosenblatt Oct 1955 A
2882696 Herrmann et al. Apr 1959 A
2910256 Richard et al. Oct 1959 A
3022639 Brown et al. Feb 1962 A
3210578 Sherer Oct 1965 A
3218819 Crotser Nov 1965 A
3219533 Mullins Nov 1965 A
3381371 Russell May 1968 A
3506032 Eveleigh et al. Apr 1970 A
3539455 Clark, Jr. et al. Nov 1970 A
3556950 Dahms et al. Jan 1971 A
3562352 Nyilas et al. Feb 1971 A
3581062 Aston May 1971 A
3607329 Manji Sep 1971 A
3610226 Albisser Oct 1971 A
3652475 Wada et al. Mar 1972 A
3728678 Tong Apr 1973 A
3775182 Patton et al. Nov 1973 A
3780727 King Dec 1973 A
3791871 Rowley Feb 1974 A
3826244 Salcman et al. Jul 1974 A
3837339 Aisenberg et al. Sep 1974 A
3838033 Mindt et al. Sep 1974 A
3838682 Clark et al. Oct 1974 A
3872455 Fuller et al. Mar 1975 A
3874850 Sorensen et al. Apr 1975 A
3882011 Hines et al. May 1975 A
3898984 Mandel et al. Aug 1975 A
3910256 Clark et al. Oct 1975 A
3926760 Allen et al. Dec 1975 A
3929971 Roy Dec 1975 A
3930462 Day Jan 1976 A
3933593 Sternberg Jan 1976 A
3943918 Lewis Mar 1976 A
3949388 Fuller Apr 1976 A
3957613 Macur May 1976 A
3957651 Kesting May 1976 A
3964974 Banauch et al. Jun 1976 A
3966580 Janata et al. Jun 1976 A
3978684 Taylor Sep 1976 A
3979274 Newman Sep 1976 A
3982530 Storch Sep 1976 A
4003621 Lamp Jan 1977 A
4008717 Kowarski Feb 1977 A
4016866 Lawton Apr 1977 A
4024312 Korpman May 1977 A
4036749 Anderson Jul 1977 A
4037563 Pflueger et al. Jul 1977 A
4040908 Clark, Jr. Aug 1977 A
4052754 Homsy Oct 1977 A
4055175 Clemens et al. Oct 1977 A
4067322 Johnson Jan 1978 A
4068660 Beck Jan 1978 A
4073713 Newman Feb 1978 A
4076656 White et al. Feb 1978 A
4101395 Motani et al. Jul 1978 A
4109505 Clark et al. Aug 1978 A
4110997 Klotz et al. Sep 1978 A
4116920 Honma et al. Sep 1978 A
4119406 Clemens Oct 1978 A
4129128 McFarlane Dec 1978 A
4151845 Clemens May 1979 A
4172770 Semersky et al. Oct 1979 A
4176659 Rolfe Dec 1979 A
4187390 Gore Feb 1980 A
4197840 Beck et al. Apr 1980 A
4197852 Schindler et al. Apr 1980 A
4206755 Klein Jun 1980 A
4215703 Willson Aug 1980 A
4225410 Pace Sep 1980 A
4230118 Holman et al. Oct 1980 A
4240438 Updike et al. Dec 1980 A
4240889 Yoda et al. Dec 1980 A
4245634 Albisser et al. Jan 1981 A
4248246 Ikeda Feb 1981 A
4253469 Aslan Mar 1981 A
4255500 Hooke Mar 1981 A
4259540 Sabia Mar 1981 A
4260725 Keogh et al. Apr 1981 A
4260726 Deubzer et al. Apr 1981 A
4265249 Schindler et al. May 1981 A
4286039 Landa et al. Aug 1981 A
4319578 Enger Mar 1982 A
4324256 Vesterager Apr 1982 A
4324257 Albarda et al. Apr 1982 A
4327725 Cortese et al. May 1982 A
4344438 Schultz Aug 1982 A
4349728 Phillips et al. Sep 1982 A
4353368 Slovak et al. Oct 1982 A
4353888 Sefton Oct 1982 A
4366040 Marsoner et al. Dec 1982 A
4369785 Rehkopf et al. Jan 1983 A
4374013 Enfors Feb 1983 A
4378016 Loeb Mar 1983 A
4388166 Suzuki et al. Jun 1983 A
4402694 Ash et al. Sep 1983 A
4402847 Wilson et al. Sep 1983 A
4403847 Chrestensen Sep 1983 A
4403984 Ash et al. Sep 1983 A
4415666 D'Orazio et al. Nov 1983 A
4418148 Oberhardt Nov 1983 A
4419535 O'Hara Dec 1983 A
4425920 Bourland et al. Jan 1984 A
4431004 Bessman et al. Feb 1984 A
4431507 Nankai et al. Feb 1984 A
4432366 Margules Feb 1984 A
4436094 Cerami Mar 1984 A
4442841 Uehara et al. Apr 1984 A
4453537 Spitzer Jun 1984 A
4454295 Wittmann et al. Jun 1984 A
4457339 Juan et al. Jul 1984 A
4469110 Slama Sep 1984 A
4477314 Richter et al. Oct 1984 A
4478222 Koning et al. Oct 1984 A
4478976 Goertz et al. Oct 1984 A
4484987 Gough Nov 1984 A
4486290 Cahalan et al. Dec 1984 A
4492575 Mabille Jan 1985 A
4493714 Ueda et al. Jan 1985 A
4494950 Fischell Jan 1985 A
4506680 Stokes Mar 1985 A
4509531 Ward Apr 1985 A
4519973 Cahalan et al. May 1985 A
RE31916 Oswin et al. Jun 1985 E
4526569 Bernardi Jul 1985 A
4527240 Kvitash Jul 1985 A
4527999 Lee Jul 1985 A
4534355 Potter Aug 1985 A
4534825 Koning Aug 1985 A
4535786 Kater Aug 1985 A
4538616 Rogoff Sep 1985 A
4545382 Higgins et al. Oct 1985 A
4554927 Fussell Nov 1985 A
4561963 Owen et al. Dec 1985 A
4565665 Fogt Jan 1986 A
4565666 Cahalan et al. Jan 1986 A
4568444 Nakamura et al. Feb 1986 A
4571292 Liu et al. Feb 1986 A
4573968 Parker Mar 1986 A
4577642 Stokes Mar 1986 A
4578215 Bradley Mar 1986 A
4579120 Macgregor Apr 1986 A
4583976 Ferguson Apr 1986 A
4592824 Smith et al. Jun 1986 A
4600495 Fogt Jul 1986 A
4602922 Cabasso et al. Jul 1986 A
4603152 Laurin et al. Jul 1986 A
4614514 Carr et al. Sep 1986 A
4619793 Lee Oct 1986 A
4625730 Fountain et al. Dec 1986 A
4626104 Pointon et al. Dec 1986 A
RE32361 Duggan Feb 1987 E
4647643 Zdrahala et al. Mar 1987 A
4650547 Gough Mar 1987 A
4655880 Liu Apr 1987 A
4663824 Kenmochi May 1987 A
4671288 Gough Jun 1987 A
4672970 Uchida et al. Jun 1987 A
4675346 Lin et al. Jun 1987 A
4680268 Clark, Jr. Jul 1987 A
4684538 Klemarczyk Aug 1987 A
4684558 Keusch et al. Aug 1987 A
4685463 Williams Aug 1987 A
4685903 Cable et al. Aug 1987 A
4686137 Ward, Jr. et al. Aug 1987 A
4689149 Kanno et al. Aug 1987 A
4689309 Jones Aug 1987 A
4694861 Goodale et al. Sep 1987 A
4703756 Gough et al. Nov 1987 A
4703989 Price et al. Nov 1987 A
4705503 Dorman et al. Nov 1987 A
4711245 Higgins et al. Dec 1987 A
4711251 Stokes Dec 1987 A
4721677 Clark, Jr. Jan 1988 A
4726381 Jones Feb 1988 A
4731726 Allen, III Mar 1988 A
4734092 Millerd Mar 1988 A
4736748 Nakamura et al. Apr 1988 A
4739380 Lauks et al. Apr 1988 A
4747822 Peabody May 1988 A
4749985 Corsberg Jun 1988 A
4750496 Reinhart et al. Jun 1988 A
4752935 Beck Jun 1988 A
4753652 Langer et al. Jun 1988 A
4755168 Romanelli et al. Jul 1988 A
4757022 Shults et al. Jul 1988 A
4759828 Young et al. Jul 1988 A
4761748 Le Rat et al. Aug 1988 A
4763648 Wyatt Aug 1988 A
4763658 Jones Aug 1988 A
4776343 Hubbard et al. Oct 1988 A
4777953 Ash et al. Oct 1988 A
4779618 Mund et al. Oct 1988 A
4781680 Redmond et al. Nov 1988 A
4781798 Gough Nov 1988 A
4784157 Halls et al. Nov 1988 A
4786394 Enzer et al. Nov 1988 A
4787398 Garcia et al. Nov 1988 A
4789467 Lindsay et al. Dec 1988 A
4791932 Margules Dec 1988 A
4793555 Lee et al. Dec 1988 A
4795435 Steer Jan 1989 A
4795542 Ross et al. Jan 1989 A
4803243 Fujimoto et al. Feb 1989 A
4805624 Yao et al. Feb 1989 A
4805625 Wyler Feb 1989 A
4807632 Liess et al. Feb 1989 A
4808089 Buchholtz et al. Feb 1989 A
4808292 Kessler et al. Feb 1989 A
4809704 Sogawa et al. Mar 1989 A
4810243 Howson Mar 1989 A
4810470 Burkhardt et al. Mar 1989 A
4813424 Wilkins Mar 1989 A
4815471 Stobie Mar 1989 A
4820281 Lawler, Jr. Apr 1989 A
4822336 Ditraglia Apr 1989 A
4826706 Hilker et al. May 1989 A
4828544 Lane et al. May 1989 A
4830013 Maxwell May 1989 A
4831070 McInally et al. May 1989 A
4832005 Takamiya et al. May 1989 A
4832034 Pizziconi et al. May 1989 A
4834101 Collison et al. May 1989 A
4838281 Rogers et al. Jun 1989 A
4841974 Gumbrecht et al. Jun 1989 A
4849458 Reed et al. Jul 1989 A
4852025 Herpichbohm Jul 1989 A
4852573 Kennedy Aug 1989 A
4852604 Wales et al. Aug 1989 A
4854322 Ash et al. Aug 1989 A
4858615 Meinema Aug 1989 A
4861454 Ushizawa et al. Aug 1989 A
4867741 Portnoy Sep 1989 A
4871440 Nagata et al. Oct 1989 A
4874363 Abell Oct 1989 A
4883057 Broderick Nov 1989 A
4883467 Franetzki et al. Nov 1989 A
4886070 Demarest Dec 1989 A
4886562 Pinson Dec 1989 A
4889528 Nadai et al. Dec 1989 A
4889744 Quaid Dec 1989 A
4890620 Gough Jan 1990 A
4890621 Hakky Jan 1990 A
4894339 Hanazato et al. Jan 1990 A
4900305 Smith et al. Feb 1990 A
4902294 Gosserez Feb 1990 A
4907857 Giuliani et al. Mar 1990 A
4909786 Gijsfi et al. Mar 1990 A
4909908 Ross et al. Mar 1990 A
4919114 Miyazaki Apr 1990 A
4919141 Zier et al. Apr 1990 A
4919649 Timothy et al. Apr 1990 A
4921477 Davis May 1990 A
4921480 Sealfon May 1990 A
4925268 Iyer et al. May 1990 A
4925444 Orkin et al. May 1990 A
4927407 Dorman May 1990 A
4927516 Yamaguchi et al. May 1990 A
4928694 Maxwell May 1990 A
4934369 Maxwell Jun 1990 A
4934375 Cole et al. Jun 1990 A
4935345 Guilbeau et al. Jun 1990 A
4940065 Tanagho et al. Jul 1990 A
4944299 Silvian Jul 1990 A
4946439 Eggers Aug 1990 A
4951657 Pfister et al. Aug 1990 A
4951669 Maxwell et al. Aug 1990 A
4952618 Olsen Aug 1990 A
4953552 DeMarzo Sep 1990 A
4955861 Enegren et al. Sep 1990 A
4957483 Gonser et al. Sep 1990 A
4958148 Olson Sep 1990 A
4960594 Honeycutt Oct 1990 A
4961434 Stypulkowski Oct 1990 A
4963595 Ward et al. Oct 1990 A
4966579 Polaschegg Oct 1990 A
4967940 Blette et al. Nov 1990 A
4970145 Bennetto et al. Nov 1990 A
4974592 Branco Dec 1990 A
4974929 Curry Dec 1990 A
4975175 Karube et al. Dec 1990 A
4975636 Desautels Dec 1990 A
4976687 Martin Dec 1990 A
4979509 Hakky Dec 1990 A
4984929 Rock et al. Jan 1991 A
4986271 Wilkins Jan 1991 A
4986671 Sun et al. Jan 1991 A
4988341 Columbus et al. Jan 1991 A
4988758 Fukuda et al. Jan 1991 A
4989607 Keusch et al. Feb 1991 A
4990231 Stewart et al. Feb 1991 A
4992794 Brouwers Feb 1991 A
4994026 Fecondini Feb 1991 A
4994167 Shults et al. Feb 1991 A
4995402 Smith et al. Feb 1991 A
4997627 Bergkuist et al. Mar 1991 A
5000180 Kuypers et al. Mar 1991 A
5000194 Van Den Honert et al. Mar 1991 A
5002054 Ash et al. Mar 1991 A
5002055 Merki et al. Mar 1991 A
5002572 Picha Mar 1991 A
5002590 Friesen et al. Mar 1991 A
5006050 Cooke et al. Apr 1991 A
5006111 Inokuchi et al. Apr 1991 A
5007929 Quaid Apr 1991 A
5009251 Pike et al. Apr 1991 A
5019096 Fox, Jr. et al. May 1991 A
5019974 Beckers May 1991 A
5026348 Venegas Jun 1991 A
5030199 Barwick et al. Jul 1991 A
5030310 Wogoman Jul 1991 A
5030333 Clark, Jr. Jul 1991 A
5034112 Murase et al. Jul 1991 A
5035711 Aoki et al. Jul 1991 A
5037497 Stypulkowski Aug 1991 A
5041092 Barwick Aug 1991 A
5045057 Van Driessche et al. Sep 1991 A
5045601 Capelli et al. Sep 1991 A
5046496 Betts et al. Sep 1991 A
5048525 Maxwell Sep 1991 A
5050612 Matsumura Sep 1991 A
5055171 Peck Oct 1991 A
5055198 Shettigar Oct 1991 A
5059654 Hou et al. Oct 1991 A
5063081 Cozzette et al. Nov 1991 A
5067491 Taylor, II et al. Nov 1991 A
5068536 Rosenthal Nov 1991 A
5077476 Rosenthal Dec 1991 A
5082550 Rishpon et al. Jan 1992 A
5088981 Howson et al. Feb 1992 A
5089112 Skotheim et al. Feb 1992 A
5089421 Dieffenbach Feb 1992 A
5096669 Lauks et al. Mar 1992 A
5097834 Skrabal Mar 1992 A
5098377 Borsanyi et al. Mar 1992 A
5101814 Palti Apr 1992 A
5106365 Hernandez Apr 1992 A
5108819 Heller et al. Apr 1992 A
5109850 Blanco et al. May 1992 A
5112301 Fenton, Jr. et al. May 1992 A
5116313 McGregor May 1992 A
5120420 Nankai et al. Jun 1992 A
5120813 Ward, Jr. Jun 1992 A
5122925 Inpyn Jun 1992 A
5127405 Alcala et al. Jul 1992 A
5130009 Marsoner et al. Jul 1992 A
5130231 Kennedy et al. Jul 1992 A
5135297 Valint, Jr. Aug 1992 A
5137028 Nishimura Aug 1992 A
5140985 Schroeder et al. Aug 1992 A
5145565 Kater et al. Sep 1992 A
5147725 Pinchuk Sep 1992 A
5152746 Atkinson et al. Oct 1992 A
5160418 Mullen Nov 1992 A
5161532 Joseph Nov 1992 A
5162407 Turner Nov 1992 A
5165406 Wong Nov 1992 A
5165407 Wilson et al. Nov 1992 A
5171689 Kawaguri et al. Dec 1992 A
5174123 Erickson Dec 1992 A
5174291 Schoonen et al. Dec 1992 A
5176632 Bernardi Jan 1993 A
5176658 Ranford Jan 1993 A
5176662 Bartholomew et al. Jan 1993 A
5178142 Harjunmaa et al. Jan 1993 A
5178957 Kolpe et al. Jan 1993 A
5182004 Kohno Jan 1993 A
5183549 Joseph et al. Feb 1993 A
5188591 Dorsey, III Feb 1993 A
5190038 Polson et al. Mar 1993 A
5190041 Palti Mar 1993 A
5195963 Yafuso et al. Mar 1993 A
5198771 Fidler et al. Mar 1993 A
5200051 Cozzette et al. Apr 1993 A
5202261 Musho et al. Apr 1993 A
5207218 Carpentier et al. May 1993 A
5208147 Kagenow et al. May 1993 A
5208313 Krishnan May 1993 A
5212050 Mier et al. May 1993 A
5220917 Cammilli et al. Jun 1993 A
5220920 Gharib Jun 1993 A
5222980 Gealow Jun 1993 A
5224929 Remiszewski Jul 1993 A
5225063 Gumbrecht et al. Jul 1993 A
5232434 Inagaki et al. Aug 1993 A
5235003 Ward et al. Aug 1993 A
5243696 Carr et al. Sep 1993 A
5243982 Mostl et al. Sep 1993 A
5243983 Tarr et al. Sep 1993 A
5246867 Lakowicz et al. Sep 1993 A
5249576 Goldberger et al. Oct 1993 A
5250439 Musho et al. Oct 1993 A
5254102 Ogawa Oct 1993 A
5261892 Bertaud et al. Nov 1993 A
5262035 Gregg et al. Nov 1993 A
5262305 Heller et al. Nov 1993 A
5264104 Gregg et al. Nov 1993 A
5264105 Gregg et al. Nov 1993 A
5265594 Olsson et al. Nov 1993 A
5265999 Wenschhof et al. Nov 1993 A
5266179 Nankai et al. Nov 1993 A
5269891 Colin Dec 1993 A
5271736 Picha Dec 1993 A
5271815 Wong Dec 1993 A
5279294 Anderson et al. Jan 1994 A
5281319 Kaneko et al. Jan 1994 A
5282844 Stokes et al. Feb 1994 A
5282848 Schmitt Feb 1994 A
5284140 Allen et al. Feb 1994 A
5284570 Savage et al. Feb 1994 A
5285513 Kaufman et al. Feb 1994 A
5285792 Sjoquist et al. Feb 1994 A
5286364 Yacynych et al. Feb 1994 A
5287753 Routh et al. Feb 1994 A
5293877 O'Hara et al. Mar 1994 A
5296144 Sternina et al. Mar 1994 A
5298022 Bernardi Mar 1994 A
5298144 Spokane Mar 1994 A
5299571 Mastrototaro Apr 1994 A
5302093 Owens et al. Apr 1994 A
5302440 Davis Apr 1994 A
5304468 Phillips et al. Apr 1994 A
5307263 Brown Apr 1994 A
5310469 Cunningham et al. May 1994 A
5311908 Barone et al. May 1994 A
5312361 Zadini et al. May 1994 A
5314471 Brauker et al. May 1994 A
5316008 Suga et al. May 1994 A
5316452 Bogen et al. May 1994 A
5318511 Riquier et al. Jun 1994 A
5320725 Gregg et al. Jun 1994 A
5322063 Allen et al. Jun 1994 A
5324322 Grill, Jr. et al. Jun 1994 A
5326356 Della Valle et al. Jul 1994 A
5326449 Cunningham Jul 1994 A
5328451 Davis et al. Jul 1994 A
5330521 Cohen Jul 1994 A
5330634 Wong et al. Jul 1994 A
5331555 Hashimoto et al. Jul 1994 A
5335658 Bedingham Aug 1994 A
5336102 Cairns et al. Aug 1994 A
5337747 Neftel Aug 1994 A
5340352 Nakanishi et al. Aug 1994 A
5340722 Wolfbeis et al. Aug 1994 A
5342348 Kaplan Aug 1994 A
5342409 Mullett Aug 1994 A
5342789 Chick et al. Aug 1994 A
5343869 Pross et al. Sep 1994 A
5344451 Dayton Sep 1994 A
5344454 Clarke et al. Sep 1994 A
5345932 Yafuso et al. Sep 1994 A
5348788 White Sep 1994 A
5352348 Young et al. Oct 1994 A
5352351 White et al. Oct 1994 A
5354272 Swendson et al. Oct 1994 A
5354449 Band et al. Oct 1994 A
5356375 Higley Oct 1994 A
5356378 Doan Oct 1994 A
5356786 Heller et al. Oct 1994 A
5358409 Obara Oct 1994 A
5360404 Novacek et al. Nov 1994 A
5362761 Uragami et al. Nov 1994 A
5368028 Palti Nov 1994 A
5368224 Richardson et al. Nov 1994 A
5368562 Blomquist et al. Nov 1994 A
5372133 Hogen Esch Dec 1994 A
5372135 Mendelson et al. Dec 1994 A
5372427 Padovani et al. Dec 1994 A
5372709 Hood Dec 1994 A
5372719 Afeyan et al. Dec 1994 A
5376070 Purvis et al. Dec 1994 A
5378229 Layer et al. Jan 1995 A
5379238 Stark Jan 1995 A
5380268 Wheeler Jan 1995 A
5380422 Negishi et al. Jan 1995 A
5380491 Carver, Jr. et al. Jan 1995 A
5380536 Hubbell et al. Jan 1995 A
5380665 Cusack et al. Jan 1995 A
5382514 Passaniti et al. Jan 1995 A
5384028 Ito Jan 1995 A
5387327 Khan Feb 1995 A
5390671 Lord et al. Feb 1995 A
5391250 Cheney, II et al. Feb 1995 A
5393401 Knoll Feb 1995 A
5397848 Yang et al. Mar 1995 A
5400267 Denen et al. Mar 1995 A
5404877 Nolan et al. Apr 1995 A
5405510 Betts et al. Apr 1995 A
5408999 Singh et al. Apr 1995 A
5411052 Murray May 1995 A
5411647 Johnson et al. May 1995 A
5411866 Luong et al. May 1995 A
5417115 Burns May 1995 A
5417206 Kaneyoshi May 1995 A
5417395 Fowler et al. May 1995 A
5418142 Kiser et al. May 1995 A
5421328 Bedingham Jun 1995 A
5421923 Clarke et al. Jun 1995 A
5423738 Robinson et al. Jun 1995 A
5423749 Merte et al. Jun 1995 A
5425717 Mohiuddin Jun 1995 A
5426032 Phillips et al. Jun 1995 A
5428123 Ward et al. Jun 1995 A
5429129 Lovejoy et al. Jul 1995 A
5429485 Dodge Jul 1995 A
5429602 Hauser Jul 1995 A
5429735 Johnson et al. Jul 1995 A
5431160 Wilkins Jul 1995 A
5431174 Knute Jul 1995 A
5431921 Thombre Jul 1995 A
5434412 Sodickson et al. Jul 1995 A
5437635 Fields et al. Aug 1995 A
5437999 Diebold et al. Aug 1995 A
5438984 Schoendorfer Aug 1995 A
5445610 Evert Aug 1995 A
5448992 Kupershmidt Sep 1995 A
5451260 Versteeg et al. Sep 1995 A
5453199 Afeyan et al. Sep 1995 A
5453278 Chan et al. Sep 1995 A
5458631 Xavier Oct 1995 A
5462051 Oka et al. Oct 1995 A
5462064 D'Angelo et al. Oct 1995 A
5462645 Albery et al. Oct 1995 A
5466356 Schneider et al. Nov 1995 A
5466575 Cozzette et al. Nov 1995 A
5469846 Khan Nov 1995 A
5472317 Field et al. Dec 1995 A
5474552 Palti Dec 1995 A
5476094 Allen et al. Dec 1995 A
5476776 Wilkins Dec 1995 A
5480711 Ruefer Jan 1996 A
5482008 Stafford et al. Jan 1996 A
5482446 Williamson Jan 1996 A
5482473 Lord et al. Jan 1996 A
5484404 Schulman et al. Jan 1996 A
5486776 Chiang Jan 1996 A
5489414 Schreiber et al. Feb 1996 A
5490323 Thacker et al. Feb 1996 A
5491474 Suni et al. Feb 1996 A
5494562 Maley et al. Feb 1996 A
5496453 Uenoyama et al. Mar 1996 A
5497772 Schulman et al. Mar 1996 A
5502396 Desarzens et al. Mar 1996 A
5505828 Wong et al. Apr 1996 A
5507288 Bocker et al. Apr 1996 A
5508203 Fuller et al. Apr 1996 A
5508509 Yafuso et al. Apr 1996 A
5509410 Hill et al. Apr 1996 A
5509888 Miller Apr 1996 A
5512046 Pusinelli et al. Apr 1996 A
5512248 Van Apr 1996 A
5513636 Palti May 1996 A
5514253 Davis et al. May 1996 A
5514718 Lewis et al. May 1996 A
5515170 Matzinger et al. May 1996 A
5515851 Goldstein May 1996 A
5516832 Kennan et al. May 1996 A
5518601 Foos et al. May 1996 A
5526120 Jina et al. Jun 1996 A
5527288 Gross et al. Jun 1996 A
5529066 Palti Jun 1996 A
5529676 Maley et al. Jun 1996 A
5531679 Schulman et al. Jul 1996 A
5531878 Vadgama et al. Jul 1996 A
5540828 Yacynych Jul 1996 A
5545200 West et al. Aug 1996 A
5545220 Andrews et al. Aug 1996 A
5545223 Neuenfeldt et al. Aug 1996 A
5549547 Cohen et al. Aug 1996 A
5549548 Larsson Aug 1996 A
5549569 Lynn et al. Aug 1996 A
5549651 Lynn Aug 1996 A
5549675 Neuenfeldt et al. Aug 1996 A
5551850 Williamson et al. Sep 1996 A
5552112 Schiffmann et al. Sep 1996 A
5553616 Ham et al. Sep 1996 A
5554339 Cozzette et al. Sep 1996 A
5558957 Datta et al. Sep 1996 A
5562614 O'Donnell Oct 1996 A
5562615 Nassif Oct 1996 A
5564439 Picha Oct 1996 A
5568806 Cheney, II et al. Oct 1996 A
5569186 Lord et al. Oct 1996 A
5569188 Mackool Oct 1996 A
5569219 Hakki et al. Oct 1996 A
5569462 Martinson et al. Oct 1996 A
5571395 Park et al. Nov 1996 A
5575293 Miller et al. Nov 1996 A
5575930 Tietje-Girault et al. Nov 1996 A
5577499 Teves Nov 1996 A
5582184 Erickson et al. Dec 1996 A
5582497 Noguchi Dec 1996 A
5582593 Hultman Dec 1996 A
5582697 Ikeda et al. Dec 1996 A
5584813 Livingston et al. Dec 1996 A
5584876 Bruchman et al. Dec 1996 A
5586553 Halili et al. Dec 1996 A
5587273 Yan et al. Dec 1996 A
5588560 Benedict et al. Dec 1996 A
5589133 Suzuki Dec 1996 A
5589563 Ward et al. Dec 1996 A
5590651 Shaffer et al. Jan 1997 A
5593440 Brauker et al. Jan 1997 A
5593852 Heller et al. Jan 1997 A
5601435 Quy Feb 1997 A
5607565 Azarnia et al. Mar 1997 A
5609572 Lang Mar 1997 A
5609575 Larson et al. Mar 1997 A
5611900 Worden et al. Mar 1997 A
5624409 Seale Apr 1997 A
5624537 Turner et al. Apr 1997 A
5626561 Butler et al. May 1997 A
5626563 Dodge et al. May 1997 A
5628310 Rao et al. May 1997 A
5628619 Wilson May 1997 A
5628890 Carter et al. May 1997 A
5630978 Domb May 1997 A
5637083 Bertrand et al. Jun 1997 A
5637135 Ottenstein et al. Jun 1997 A
5640470 Iyer et al. Jun 1997 A
5640954 Pfeiffer et al. Jun 1997 A
5643195 Drevet et al. Jul 1997 A
5651767 Schulman et al. Jul 1997 A
5653239 Pompei et al. Aug 1997 A
5653756 Clarke et al. Aug 1997 A
5653863 Genshaw et al. Aug 1997 A
5658247 Henley Aug 1997 A
5658250 Blomquist et al. Aug 1997 A
5658330 Carlisle et al. Aug 1997 A
5658802 Hayes et al. Aug 1997 A
5660163 Schulman et al. Aug 1997 A
5660177 Faupel et al. Aug 1997 A
5662616 Bousquet Sep 1997 A
5665061 Antwiler Sep 1997 A
5665065 Colman et al. Sep 1997 A
5665215 Bussmann et al. Sep 1997 A
5665222 Heller et al. Sep 1997 A
5667504 Baumann et al. Sep 1997 A
5673694 Rivers Oct 1997 A
5676651 Larson, Jr. et al. Oct 1997 A
5676820 Wang et al. Oct 1997 A
5681572 Seare, Jr. Oct 1997 A
5682884 Hill et al. Nov 1997 A
5683562 Schaffar et al. Nov 1997 A
5686829 Girault Nov 1997 A
5688239 Walker Nov 1997 A
5688244 Lang Nov 1997 A
5690119 Rytky et al. Nov 1997 A
5695623 Michel et al. Dec 1997 A
5696314 McCaffrey et al. Dec 1997 A
5697366 Kimball et al. Dec 1997 A
5697899 Hillman et al. Dec 1997 A
5697976 Chesterfield et al. Dec 1997 A
5703359 Wampler, III Dec 1997 A
5704354 Preidel et al. Jan 1998 A
5706807 Picha Jan 1998 A
5707502 McCaffrey et al. Jan 1998 A
5711001 Bussan et al. Jan 1998 A
5711302 Lampropoulos et al. Jan 1998 A
5711685 Wood Jan 1998 A
5711861 Ward et al. Jan 1998 A
5713842 Kay Feb 1998 A
5713888 Neuenfeldt et al. Feb 1998 A
5714123 Sohrab Feb 1998 A
5714391 Omura et al. Feb 1998 A
5720293 Quinn et al. Feb 1998 A
5730654 Brown Mar 1998 A
5733336 Neuenfeldt et al. Mar 1998 A
5735273 Kurnik et al. Apr 1998 A
5735285 Albert et al. Apr 1998 A
5741319 Woloszko et al. Apr 1998 A
5741330 Brauker et al. Apr 1998 A
5741634 Nozoe et al. Apr 1998 A
5743262 Lepper, Jr. et al. Apr 1998 A
5746898 Preidel May 1998 A
5749832 Vadgama et al. May 1998 A
5749907 Mann May 1998 A
5755692 Manicom May 1998 A
5756632 Ward et al. May 1998 A
5758643 Wong et al. Jun 1998 A
5763760 Gumbrecht et al. Jun 1998 A
5763787 Gravel et al. Jun 1998 A
5766151 Valley et al. Jun 1998 A
5770028 Maley et al. Jun 1998 A
5770208 Fattom et al. Jun 1998 A
5771890 Tamada Jun 1998 A
5772586 Heinonen et al. Jun 1998 A
5773270 D'Orazio et al. Jun 1998 A
5773286 Dionne et al. Jun 1998 A
5776324 Usala Jul 1998 A
5777060 Van Antwerp Jul 1998 A
5779665 Mastrototaro et al. Jul 1998 A
5781455 Hyodo Jul 1998 A
5782880 Lahtinen et al. Jul 1998 A
5782912 Brauker et al. Jul 1998 A
5783054 Raguse et al. Jul 1998 A
5786439 Van Antwerp et al. Jul 1998 A
5787900 Butler et al. Aug 1998 A
5791344 Schulman et al. Aug 1998 A
5791880 Wilson Aug 1998 A
5795453 Gilmartin Aug 1998 A
5795774 Matsumoto et al. Aug 1998 A
5798065 Picha Aug 1998 A
5798085 Seaton et al. Aug 1998 A
5800383 Chandler et al. Sep 1998 A
5800420 Gross et al. Sep 1998 A
5800529 Brauker et al. Sep 1998 A
5804048 Wong et al. Sep 1998 A
5806517 Gerhardt et al. Sep 1998 A
5807274 Henning et al. Sep 1998 A
5807312 Dzwonkiewicz Sep 1998 A
5807375 Gross et al. Sep 1998 A
5807406 Brauker et al. Sep 1998 A
5810736 Pail Sep 1998 A
5810770 Chin et al. Sep 1998 A
5811487 Schulz, Jr. et al. Sep 1998 A
5814599 Mitragotri et al. Sep 1998 A
5820570 Erickson et al. Oct 1998 A
5820589 Torgerson et al. Oct 1998 A
5820622 Gross et al. Oct 1998 A
5822715 Worthington et al. Oct 1998 A
5823802 Bartley Oct 1998 A
5824651 Nanci et al. Oct 1998 A
5827183 Kurnik et al. Oct 1998 A
5833603 Kovacs et al. Nov 1998 A
5836886 Itoigawa et al. Nov 1998 A
5836887 Oka et al. Nov 1998 A
5836989 Shelton Nov 1998 A
5837454 Cozzette et al. Nov 1998 A
5837728 Purcell Nov 1998 A
5840026 Uber, III et al. Nov 1998 A
5840148 Campbell et al. Nov 1998 A
5840240 Stenoien et al. Nov 1998 A
5843069 Butler et al. Dec 1998 A
5848991 Gross et al. Dec 1998 A
5851197 Marano et al. Dec 1998 A
5856195 Charlton et al. Jan 1999 A
5857983 Douglas et al. Jan 1999 A
5858296 Domb Jan 1999 A
5858365 Faller Jan 1999 A
5858747 Schinstine et al. Jan 1999 A
5861019 Sun et al. Jan 1999 A
5863400 Drummond et al. Jan 1999 A
5863460 Slovacek et al. Jan 1999 A
5871499 Hahn et al. Feb 1999 A
5871514 Wiklund et al. Feb 1999 A
5872198 Mosbach et al. Feb 1999 A
5872499 Poulsen Feb 1999 A
5873862 Lopez Feb 1999 A
5874500 Rhee et al. Feb 1999 A
5879294 Anderson et al. Mar 1999 A
5879373 Roper et al. Mar 1999 A
5879713 Roth et al. Mar 1999 A
5879828 Debe et al. Mar 1999 A
5882354 Brauker et al. Mar 1999 A
5882494 Van Antwerp Mar 1999 A
5895235 Droz Apr 1999 A
5897525 Dey et al. Apr 1999 A
5897578 Wiklund et al. Apr 1999 A
5897955 Drumheller Apr 1999 A
5899855 Brown May 1999 A
5904666 DeDecker et al. May 1999 A
5904708 Goedeke May 1999 A
5910554 Kempe et al. Jun 1999 A
5911219 Aylsworth et al. Jun 1999 A
5913998 Butler et al. Jun 1999 A
5914026 Blubaugh, Jr. et al. Jun 1999 A
5914182 Drumheller Jun 1999 A
5916445 Hjerten et al. Jun 1999 A
5917346 Gord Jun 1999 A
5919215 Wiklund et al. Jul 1999 A
5921951 Morris Jul 1999 A
5922530 Yu Jul 1999 A
5925021 Castellano et al. Jul 1999 A
5928130 Schmidt Jul 1999 A
5928155 Eggers et al. Jul 1999 A
5928182 Kraus et al. Jul 1999 A
5928189 Phillips et al. Jul 1999 A
5928195 Malamud et al. Jul 1999 A
5931814 Alex et al. Aug 1999 A
5932175 Knute et al. Aug 1999 A
5933136 Brown Aug 1999 A
5935785 Reber et al. Aug 1999 A
5938636 Kramer et al. Aug 1999 A
5938679 Freeman et al. Aug 1999 A
5942979 Luppino Aug 1999 A
5944661 Swette et al. Aug 1999 A
5945498 Hopken et al. Aug 1999 A
5947911 Wong et al. Sep 1999 A
5951521 Mastrototaro et al. Sep 1999 A
5954643 VanAntwerp et al. Sep 1999 A
5954685 Tierney Sep 1999 A
5954954 Houck et al. Sep 1999 A
5957854 Besson et al. Sep 1999 A
5957903 Mirzaee et al. Sep 1999 A
5959050 Mosbach et al. Sep 1999 A
5961451 Reber et al. Oct 1999 A
5963132 Yoakum Oct 1999 A
5964261 Neuenfeldt et al. Oct 1999 A
5964745 Lyles et al. Oct 1999 A
5964804 Brauker et al. Oct 1999 A
5964993 Blubaugh, Jr. et al. Oct 1999 A
5965125 Mineau-Hanschke Oct 1999 A
5965380 Heller et al. Oct 1999 A
5967986 Cimochowski et al. Oct 1999 A
5968836 Matzinger et al. Oct 1999 A
5971922 Arita et al. Oct 1999 A
5972199 Heller et al. Oct 1999 A
5976085 Kimball et al. Nov 1999 A
5977241 Koloski et al. Nov 1999 A
5985129 Gough et al. Nov 1999 A
5985693 Leedy Nov 1999 A
5987352 Klein et al. Nov 1999 A
5989409 Kurnik et al. Nov 1999 A
5995208 Sarge et al. Nov 1999 A
5995860 Sun et al. Nov 1999 A
5997501 Gross et al. Dec 1999 A
5998247 Wu Dec 1999 A
5999848 Gord et al. Dec 1999 A
5999849 Gord et al. Dec 1999 A
6001067 Shults et al. Dec 1999 A
6001471 Bries et al. Dec 1999 A
6007845 Domb et al. Dec 1999 A
6011984 Van Antwerp et al. Jan 2000 A
6013113 Mika Jan 2000 A
6014577 Henning et al. Jan 2000 A
6015392 Douglas et al. Jan 2000 A
6015572 Lin et al. Jan 2000 A
6016448 Busacker et al. Jan 2000 A
6017435 Hassard et al. Jan 2000 A
6018033 Chen et al. Jan 2000 A
6023629 Tamada Feb 2000 A
6024699 Surwit et al. Feb 2000 A
6024720 Chandler et al. Feb 2000 A
6027445 Von Bahr Feb 2000 A
6027479 Alei et al. Feb 2000 A
6032059 Henning et al. Feb 2000 A
6032667 Heinonen Mar 2000 A
6036924 Simons et al. Mar 2000 A
6043328 Domschke et al. Mar 2000 A
6045567 Taylor et al. Apr 2000 A
6045671 Wu et al. Apr 2000 A
6048691 Maracas Apr 2000 A
6049727 Crothall Apr 2000 A
6051372 Bayerl et al. Apr 2000 A
6051389 Ahl et al. Apr 2000 A
6057377 Sasaki et al. May 2000 A
6059946 Yukawa et al. May 2000 A
6060640 Pauley et al. May 2000 A
6063637 Arnold et al. May 2000 A
6065154 Hulings et al. May 2000 A
6066083 Slater et al. May 2000 A
6066088 Davis May 2000 A
6066448 Wohlstadter et al. May 2000 A
6068668 Mastroianni May 2000 A
6071391 Gotoh et al. Jun 2000 A
6071406 Tsou Jun 2000 A
6074775 Gartstein et al. Jun 2000 A
6077299 Adelberg et al. Jun 2000 A
6080583 Von Bahr Jun 2000 A
6081735 Diab et al. Jun 2000 A
6081736 Colvin et al. Jun 2000 A
6082289 Cavallaro Jul 2000 A
6083523 Dionne et al. Jul 2000 A
6083710 Heller et al. Jul 2000 A
6088608 Schulman et al. Jul 2000 A
6090087 Tsukada et al. Jul 2000 A
6091975 Daddona et al. Jul 2000 A
6091976 Pfeiffer et al. Jul 2000 A
6093156 Cunningham et al. Jul 2000 A
6093172 Funderburk et al. Jul 2000 A
6099511 Devos et al. Aug 2000 A
6101404 Yoon et al. Aug 2000 A
6103033 Say et al. Aug 2000 A
6103533 Hassard et al. Aug 2000 A
6106486 Tenerz et al. Aug 2000 A
6107083 Collins et al. Aug 2000 A
6115622 Minoz Sep 2000 A
6115634 Donders et al. Sep 2000 A
6117290 Say et al. Sep 2000 A
6119028 Schulman et al. Sep 2000 A
6120676 Heller et al. Sep 2000 A
6121009 Heller et al. Sep 2000 A
6121611 Lindsay et al. Sep 2000 A
6122351 Schlueter, Jr. et al. Sep 2000 A
6122536 Sun et al. Sep 2000 A
6123827 Wong et al. Sep 2000 A
6127154 Mosbach et al. Oct 2000 A
6128519 Say Oct 2000 A
6134461 Say et al. Oct 2000 A
6135978 Houben et al. Oct 2000 A
6139718 Kurnik et al. Oct 2000 A
6141573 Kurnik et al. Oct 2000 A
D433755 Mastrototaro et al. Nov 2000 S
6142939 Eppstein et al. Nov 2000 A
6144869 Berner et al. Nov 2000 A
6144871 Saito et al. Nov 2000 A
RE36991 Yamamoto et al. Dec 2000 E
6156051 Schraga Dec 2000 A
6157860 Hauser et al. Dec 2000 A
6159147 Lichter et al. Dec 2000 A
6159186 Wickham et al. Dec 2000 A
6159497 LaPrade et al. Dec 2000 A
6162201 Cohen et al. Dec 2000 A
6162611 Heller et al. Dec 2000 A
6164921 Moubayed et al. Dec 2000 A
6165154 Gray et al. Dec 2000 A
6165156 Cesarczyk et al. Dec 2000 A
6167614 Tuttle et al. Jan 2001 B1
6168568 Gavriely Jan 2001 B1
6168957 Matzinger et al. Jan 2001 B1
6169155 Alvarez et al. Jan 2001 B1
6171276 Lippe et al. Jan 2001 B1
6175752 Say et al. Jan 2001 B1
6175767 Doyle, Sr. Jan 2001 B1
6180221 Crotzer et al. Jan 2001 B1
6180416 Kurnik et al. Jan 2001 B1
6183437 Walker Feb 2001 B1
6187062 Oweis et al. Feb 2001 B1
6189536 Martinez et al. Feb 2001 B1
6191860 Klinger et al. Feb 2001 B1
6192891 Gravel et al. Feb 2001 B1
6197040 LeVaughn et al. Mar 2001 B1
6198969 Kuzma Mar 2001 B1
6200265 Walsh et al. Mar 2001 B1
6200772 Vadgama et al. Mar 2001 B1
6201979 Kurnik et al. Mar 2001 B1
6201980 Darrow et al. Mar 2001 B1
6201993 Kruse et al. Mar 2001 B1
6206856 Mahurkar Mar 2001 B1
6208894 Schulman et al. Mar 2001 B1
6212416 Ward et al. Apr 2001 B1
6212424 Robinson Apr 2001 B1
6213739 Phallen et al. Apr 2001 B1
6214185 Offenbacher et al. Apr 2001 B1
6214901 Chudzik et al. Apr 2001 B1
6219574 Cormier et al. Apr 2001 B1
6223080 Thompson Apr 2001 B1
6223083 Rosar Apr 2001 B1
6230059 Duffin May 2001 B1
6231879 Li et al. May 2001 B1
6232783 Merrill May 2001 B1
6233080 Brenner et al. May 2001 B1
6233471 Berner et al. May 2001 B1
6241663 Wu et al. Jun 2001 B1
6241863 Monbouquette Jun 2001 B1
6248067 Causey, III Jun 2001 B1
6248077 Elson et al. Jun 2001 B1
6248093 Moberg Jun 2001 B1
6251280 Dai et al. Jun 2001 B1
6254586 Mann et al. Jul 2001 B1
6255592 Pennington et al. Jul 2001 B1
6256522 Schultz Jul 2001 B1
6259937 Schulman et al. Jul 2001 B1
6261280 Houben et al. Jul 2001 B1
6263222 Diab et al. Jul 2001 B1
6264825 Blackburn et al. Jul 2001 B1
6266551 Osadchy et al. Jul 2001 B1
6268161 Han et al. Jul 2001 B1
6270478 Mernoee Aug 2001 B1
6271332 Lohmann et al. Aug 2001 B1
6272364 Kurnik Aug 2001 B1
6272382 Faltys et al. Aug 2001 B1
6272480 Tresp et al. Aug 2001 B1
6274285 Gries et al. Aug 2001 B1
6274686 Mosbach et al. Aug 2001 B1
6275717 Gross et al. Aug 2001 B1
6280408 Sipin Aug 2001 B1
6283761 Joao Sep 2001 B1
6284125 Hodges et al. Sep 2001 B1
6284126 Kurnik et al. Sep 2001 B1
6284478 Heller et al. Sep 2001 B1
6285897 Kilcoyne et al. Sep 2001 B1
6293925 Safabash et al. Sep 2001 B1
6294281 Heller Sep 2001 B1
6295506 Heinonen et al. Sep 2001 B1
6296615 Brockway et al. Oct 2001 B1
6298254 Tamada Oct 2001 B2
6298255 Cordero et al. Oct 2001 B1
6299578 Kurnik et al. Oct 2001 B1
6299583 Eggers et al. Oct 2001 B1
6300002 Webb et al. Oct 2001 B1
6300884 Wilson Oct 2001 B1
6302855 Lav et al. Oct 2001 B1
6306104 Cunningham et al. Oct 2001 B1
6306424 Vyakarnam et al. Oct 2001 B1
6306594 Cozzette et al. Oct 2001 B1
6308089 Von Der Ruhr et al. Oct 2001 B1
6309351 Kurnik et al. Oct 2001 B1
6309384 Harrington et al. Oct 2001 B1
6309526 Fujiwara et al. Oct 2001 B1
6309884 Cooper et al. Oct 2001 B1
6310110 Markowitz et al. Oct 2001 B1
6315738 Nishikawa et al. Nov 2001 B1
6319566 Polanyi et al. Nov 2001 B1
6325978 Labuda et al. Dec 2001 B1
6325979 Hahn et al. Dec 2001 B1
6326160 Dunn et al. Dec 2001 B1
6329161 Heller et al. Dec 2001 B1
6329488 Terry et al. Dec 2001 B1
6329929 Weijand et al. Dec 2001 B1
6330464 Colvin, Jr. et al. Dec 2001 B1
6335203 Patel et al. Jan 2002 B1
6336269 Eldridge et al. Jan 2002 B1
6340588 Nova et al. Jan 2002 B1
6341232 Conn et al. Jan 2002 B1
6343225 Clark, Jr. Jan 2002 B1
6344021 Juster et al. Feb 2002 B1
6346114 Schraga Feb 2002 B1
6348640 Navot et al. Feb 2002 B1
6355000 Ogura Mar 2002 B1
6356776 Berner et al. Mar 2002 B1
6358225 Butterfield Mar 2002 B1
6359444 Grimes Mar 2002 B1
6360888 McIvor et al. Mar 2002 B1
6365670 Fry Apr 2002 B1
6366794 Moussy et al. Apr 2002 B1
6368141 Vanantwerp et al. Apr 2002 B1
6368274 Van Antwerp et al. Apr 2002 B1
6368658 Schwarz et al. Apr 2002 B1
6370410 Kurnik et al. Apr 2002 B2
6370941 Nakamura et al. Apr 2002 B2
6371963 Nishtala et al. Apr 2002 B1
6372244 Antanavich et al. Apr 2002 B1
6377828 Chaiken et al. Apr 2002 B1
6379201 Biggs et al. Apr 2002 B1
6379301 Worthington et al. Apr 2002 B1
6379317 Kintzig et al. Apr 2002 B1
6379883 Davis et al. Apr 2002 B2
6387709 Mason et al. May 2002 B1
6391019 Ito May 2002 B1
6393318 Conn et al. May 2002 B1
6398562 Butler et al. Jun 2002 B1
6400974 Lesho Jun 2002 B1
6402703 Kensey et al. Jun 2002 B1
6403944 MacKenzie et al. Jun 2002 B1
6405066 Essenpreis et al. Jun 2002 B1
6406066 Uegane Jun 2002 B1
6406426 Reuss et al. Jun 2002 B1
6407195 Sherman et al. Jun 2002 B2
6409674 Brockway et al. Jun 2002 B1
6413393 Van Antwerp et al. Jul 2002 B1
6413410 Hodges et al. Jul 2002 B1
6416651 Millar Jul 2002 B1
6418332 Mastrototaro et al. Jul 2002 B1
6418346 Nelson et al. Jul 2002 B1
6424847 Mastrototaro et al. Jul 2002 B1
6427088 Bowman, IV et al. Jul 2002 B1
6430437 Marro Aug 2002 B1
6432050 Porat et al. Aug 2002 B1
6435708 Huang Aug 2002 B1
6438414 Conn et al. Aug 2002 B1
6440068 Brown Aug 2002 B1
6442413 Silver Aug 2002 B1
6447448 Ishikawa et al. Sep 2002 B1
6447542 Weadock Sep 2002 B1
6454710 Ballerstadt et al. Sep 2002 B1
6459917 Gowda et al. Oct 2002 B1
6461496 Feldman et al. Oct 2002 B1
6464849 Say et al. Oct 2002 B1
6465066 Rule et al. Oct 2002 B1
6466810 Ward et al. Oct 2002 B1
6467480 Meier et al. Oct 2002 B1
6468287 Baugh Oct 2002 B1
6471689 Joseph et al. Oct 2002 B1
6471993 Shastri et al. Oct 2002 B1
6474360 Ito Nov 2002 B1
6475372 Ohara et al. Nov 2002 B1
6475750 Han et al. Nov 2002 B1
6477392 Honigs et al. Nov 2002 B1
6477395 Schulman et al. Nov 2002 B2
6478736 Mault Nov 2002 B1
6481440 Gielen et al. Nov 2002 B2
6484045 Holker et al. Nov 2002 B1
6484046 Say et al. Nov 2002 B1
6484132 Hively et al. Nov 2002 B1
6485449 Ito Nov 2002 B2
6487429 Hockersmith et al. Nov 2002 B2
6488652 Weijand et al. Dec 2002 B1
6494830 Wessel Dec 2002 B1
6494879 Lennox et al. Dec 2002 B2
6497655 Linberg et al. Dec 2002 B1
6497729 Moussy et al. Dec 2002 B1
6498043 Schulman et al. Dec 2002 B1
6498941 Jackson Dec 2002 B1
6501976 Sohrab Dec 2002 B1
6510239 Wieres et al. Jan 2003 B1
6510329 Heckel Jan 2003 B2
6512939 Colvin et al. Jan 2003 B1
6514689 Han et al. Feb 2003 B2
6514718 Heller et al. Feb 2003 B2
6517508 Utterberg et al. Feb 2003 B1
6520326 McIvor et al. Feb 2003 B2
6520477 Trimmer Feb 2003 B2
6520937 Hart et al. Feb 2003 B2
6520938 Funderburk et al. Feb 2003 B1
6520997 Pekkarinen et al. Feb 2003 B1
6522903 Berman et al. Feb 2003 B1
6522927 Bishay et al. Feb 2003 B1
6524861 Anderson Feb 2003 B1
6526298 Khalil et al. Feb 2003 B1
6527729 Turcott Mar 2003 B1
6528584 Kennedy et al. Mar 2003 B2
6529755 Kurnik et al. Mar 2003 B2
6534711 Pollack Mar 2003 B1
6536433 Cewers Mar 2003 B1
6537318 Ita et al. Mar 2003 B1
6541107 Zhong et al. Apr 2003 B1
6541266 Modzelewski et al. Apr 2003 B2
6542765 Guy et al. Apr 2003 B1
6544212 Galley et al. Apr 2003 B2
6545085 Kilgour et al. Apr 2003 B2
6546268 Ishikawa et al. Apr 2003 B1
6546269 Kurnik Apr 2003 B1
6547839 Zhang et al. Apr 2003 B2
6549796 Sohrab Apr 2003 B2
6551494 Heller et al. Apr 2003 B1
6551496 Moles et al. Apr 2003 B1
6553241 Mannheimer et al. Apr 2003 B2
6553244 Lesho et al. Apr 2003 B2
6554805 Hiejima Apr 2003 B2
6554822 Holschneider et al. Apr 2003 B1
6558312 Latour, Jr. May 2003 B2
6558320 Causey, III et al. May 2003 B1
6558321 Burd et al. May 2003 B1
6558347 Jhuboo et al. May 2003 B1
6558351 Steil et al. May 2003 B1
6560471 Heller et al. May 2003 B1
6561978 Conn et al. May 2003 B1
6562001 Lebel et al. May 2003 B2
6564105 Starkweather et al. May 2003 B2
6565509 Say et al. May 2003 B1
6565535 Zaias et al. May 2003 B2
6565807 Patterson et al. May 2003 B1
6569309 Otsuka et al. May 2003 B2
6569521 Sheridan et al. May 2003 B1
6571128 Lebel et al. May 2003 B2
6572542 Houben et al. Jun 2003 B1
6572545 Knobbe et al. Jun 2003 B2
6572579 Raghavan et al. Jun 2003 B1
6572745 Rappin et al. Jun 2003 B2
6574490 Abbink et al. Jun 2003 B2
6575905 Knobbe et al. Jun 2003 B2
6576101 Heller et al. Jun 2003 B1
6577899 Lebel et al. Jun 2003 B2
6579257 Elgas et al. Jun 2003 B1
6579498 Eglise Jun 2003 B1
6579690 Bonnecaze et al. Jun 2003 B1
6584335 Haar et al. Jun 2003 B1
6585644 Lebel et al. Jul 2003 B2
6585675 O'Mahony et al. Jul 2003 B1
6585763 Keilman et al. Jul 2003 B1
6587704 Fine et al. Jul 2003 B1
6587705 Kim et al. Jul 2003 B1
6589229 Connelly et al. Jul 2003 B1
6591123 Fein et al. Jul 2003 B2
6591125 Buse et al. Jul 2003 B1
6592745 Feldman et al. Jul 2003 B1
6594514 Berner et al. Jul 2003 B2
6595756 Gray et al. Jul 2003 B2
6595919 Berner et al. Jul 2003 B2
6602221 Saravia et al. Aug 2003 B1
6603995 Carter Aug 2003 B1
6605072 Struys et al. Aug 2003 B2
6605200 Mao et al. Aug 2003 B1
6605201 Mao et al. Aug 2003 B1
6607509 Bobroff et al. Aug 2003 B2
6607658 Heller et al. Aug 2003 B1
6609071 Shapiro Aug 2003 B2
6610012 Mault Aug 2003 B2
6612984 Kerr, II Sep 2003 B1
6613379 Ward et al. Sep 2003 B2
6615061 Khalil et al. Sep 2003 B1
6615078 Burson et al. Sep 2003 B1
6618603 Varalli et al. Sep 2003 B2
6618934 Feldman et al. Sep 2003 B1
6628975 Fein et al. Sep 2003 B1
6633772 Ford et al. Oct 2003 B2
6635014 Starkweather et al. Oct 2003 B2
6641533 Causey, III et al. Nov 2003 B2
6642015 Vachon et al. Nov 2003 B2
6645181 Lavi et al. Nov 2003 B1
6645219 Roe Nov 2003 B2
6645359 Bhullar et al. Nov 2003 B1
6648821 Lebel et al. Nov 2003 B2
6653091 Dunn et al. Nov 2003 B1
6654625 Say et al. Nov 2003 B1
6656157 Duchon et al. Dec 2003 B1
6659948 Lebel et al. Dec 2003 B2
6662439 Bhullar Dec 2003 B1
6663615 Madou et al. Dec 2003 B1
6666821 Keimel Dec 2003 B2
6668196 Villegas et al. Dec 2003 B1
6673022 Bobo et al. Jan 2004 B1
6673596 Sayler et al. Jan 2004 B1
6679865 Shekalim Jan 2004 B2
6683535 Utke Jan 2004 B1
6684904 Ito Feb 2004 B2
6685668 Cho et al. Feb 2004 B1
6687522 Tamada Feb 2004 B2
6687546 Lebel et al. Feb 2004 B2
6689056 Kilcoyne et al. Feb 2004 B1
6689089 Tiedtke et al. Feb 2004 B1
6689265 Heller et al. Feb 2004 B2
6692456 Eppstein et al. Feb 2004 B1
6694191 Starkweather et al. Feb 2004 B2
6695860 Ward et al. Feb 2004 B1
6699188 Wessel Mar 2004 B2
6699218 Flaherty et al. Mar 2004 B2
6699383 Lemire et al. Mar 2004 B2
6702249 Ito Mar 2004 B2
6702857 Brauker et al. Mar 2004 B2
6702972 Markle Mar 2004 B1
6705833 Tam et al. Mar 2004 B2
6711424 Fine et al. Mar 2004 B1
6712796 Fentis et al. Mar 2004 B2
6713773 Lyons et al. Mar 2004 B1
6721586 Kiser et al. Apr 2004 B2
6721587 Gough Apr 2004 B2
6723077 Pickup et al. Apr 2004 B2
6723086 Bassuk et al. Apr 2004 B2
6730072 Shawgo et al. May 2004 B2
6730200 Stewart May 2004 B1
6731976 Penn et al. May 2004 B2
6733446 Lebel et al. May 2004 B2
6733655 Davies et al. May 2004 B1
6736777 Kim et al. May 2004 B2
6736783 Blake et al. May 2004 B2
6737158 Thompson May 2004 B1
6740059 Flaherty May 2004 B2
6740075 Lebel et al. May 2004 B2
6741871 Silverbrook et al. May 2004 B1
6741877 Shults et al. May 2004 B1
6742635 Hirshberg Jun 2004 B2
6743635 Neel et al. Jun 2004 B2
6746582 Heller et al. Jun 2004 B2
6749587 Flaherty Jun 2004 B2
6758810 Lebel et al. Jul 2004 B2
6767440 Bhullar et al. Jul 2004 B1
6767632 Axelgaard et al. Jul 2004 B2
6770030 Schaupp et al. Aug 2004 B1
6770067 Lorenzen et al. Aug 2004 B2
6773565 Kunimoto et al. Aug 2004 B2
6780297 Matsumoto et al. Aug 2004 B2
6782343 Hasper Aug 2004 B2
6784274 Van Antwerp et al. Aug 2004 B2
6789634 Denton Sep 2004 B1
6790178 Mault et al. Sep 2004 B1
6793632 Sohrab Sep 2004 B2
6793802 Lee et al. Sep 2004 B2
6801041 Karinka et al. Oct 2004 B2
6802957 Jung et al. Oct 2004 B2
6804002 Fine et al. Oct 2004 B2
6804544 Van Antwerp et al. Oct 2004 B2
6804558 Haller et al. Oct 2004 B2
6805693 Gray et al. Oct 2004 B2
6809507 Morgan et al. Oct 2004 B2
6809653 Mann et al. Oct 2004 B1
6810290 Lebel et al. Oct 2004 B2
6810736 Ikezawa et al. Nov 2004 B2
6811533 Lebel et al. Nov 2004 B2
6811534 Bowman, IV et al. Nov 2004 B2
6811548 Jeffrey Nov 2004 B2
6813519 Lebel et al. Nov 2004 B2
6814845 Wilson et al. Nov 2004 B2
6815186 Clark, Jr. Nov 2004 B2
6830551 Uchigaki et al. Dec 2004 B1
6835553 Han et al. Dec 2004 B2
6843899 Ufer Jan 2005 B2
6849052 Uchigaki et al. Feb 2005 B2
6849463 Santini, Jr. et al. Feb 2005 B2
6850790 Berner et al. Feb 2005 B2
6858020 Rusnak Feb 2005 B2
6862465 Shults et al. Mar 2005 B2
6863800 Karinka et al. Mar 2005 B2
6867262 Angel et al. Mar 2005 B1
6869413 Langley et al. Mar 2005 B2
6873268 Lebel et al. Mar 2005 B2
6875386 Ward et al. Apr 2005 B1
6878112 Linberg et al. Apr 2005 B2
6881551 Heller et al. Apr 2005 B2
6882940 Potts Apr 2005 B2
6885883 Parris et al. Apr 2005 B2
6887228 Mckay May 2005 B2
6891317 Pei et al. May 2005 B2
6892085 McIvor et al. May 2005 B2
6893552 Wang et al. May 2005 B1
6895263 Shin et al. May 2005 B2
6895265 Silver May 2005 B2
6902544 Ludin et al. Jun 2005 B2
6908681 Terry et al. Jun 2005 B2
6919566 Cadell Jul 2005 B1
6923763 Kovatchev et al. Aug 2005 B1
6925393 Kalatz et al. Aug 2005 B1
6926691 Miethke Aug 2005 B2
6931327 Goode, Jr Aug 2005 B2
6932584 Gray et al. Aug 2005 B2
6932894 Mao Aug 2005 B2
6936006 Sabra Aug 2005 B2
6942518 Liamos et al. Sep 2005 B2
6945965 Whiting Sep 2005 B2
6948492 Wermeling et al. Sep 2005 B2
6950708 Bowman, IV et al. Sep 2005 B2
6952604 Denuzzio et al. Oct 2005 B2
6954662 Freger et al. Oct 2005 B2
6958705 Lebel et al. Oct 2005 B2
6960192 Flaherty et al. Nov 2005 B1
6965791 Hitchcock et al. Nov 2005 B1
6966325 Erickson Nov 2005 B2
6968294 Gutta et al. Nov 2005 B2
6971274 Olin Dec 2005 B2
6972080 Tomioka et al. Dec 2005 B1
6973706 Say et al. Dec 2005 B2
6974437 Lebel et al. Dec 2005 B2
6975893 Say et al. Dec 2005 B2
6979315 Rogers et al. Dec 2005 B2
6983867 Fugere Jan 2006 B1
6989891 Braig et al. Jan 2006 B2
6990366 Say et al. Jan 2006 B2
6991643 Saadat Jan 2006 B2
6997907 Safabash et al. Feb 2006 B2
6997921 Gray et al. Feb 2006 B2
6998247 Monfre et al. Feb 2006 B2
7003336 Holker et al. Feb 2006 B2
7003340 Say et al. Feb 2006 B2
7003341 Say et al. Feb 2006 B2
7008979 Schottman et al. Mar 2006 B2
7011630 Desai et al. Mar 2006 B2
7016713 Gardner et al. Mar 2006 B2
7022072 Fox et al. Apr 2006 B2
7022219 Mansouri et al. Apr 2006 B2
7024245 Lebel et al. Apr 2006 B2
7025425 Kovatchev et al. Apr 2006 B2
7025727 Brockway et al. Apr 2006 B2
7025743 Mann et al. Apr 2006 B2
7027848 Robinson et al. Apr 2006 B2
7029444 Shin et al. Apr 2006 B2
7033322 Silver Apr 2006 B2
7039446 Ruchti et al. May 2006 B2
7041068 Freeman et al. May 2006 B2
7041468 Drucker et al. May 2006 B2
7048687 Reuss et al. May 2006 B1
7048727 Moss May 2006 B1
7052483 Wojcik May 2006 B2
7056302 Douglas Jun 2006 B2
7058437 Buse et al. Jun 2006 B2
7058453 Nelson et al. Jun 2006 B2
7060031 Webb et al. Jun 2006 B2
7060059 Keith et al. Jun 2006 B2
7061593 Braig et al. Jun 2006 B2
7063086 Shahbazpour et al. Jun 2006 B2
7066884 Custer et al. Jun 2006 B2
7061195 Simpson et al. Jul 2006 B2
7070577 Haller et al. Jul 2006 B1
7070580 Nielsen Jul 2006 B2
7073246 Bhullar et al. Jul 2006 B2
7074307 Simpson et al. Jul 2006 B2
7078582 Stebbings et al. Jul 2006 B2
7097775 Greenberg et al. Aug 2006 B2
7098803 Mann et al. Aug 2006 B2
7100628 Izenson et al. Sep 2006 B1
7108778 Simpson et al. Sep 2006 B2
7110803 Shults et al. Sep 2006 B2
7113821 Sun et al. Sep 2006 B1
7114502 Schulman et al. Oct 2006 B2
7115884 Walt et al. Oct 2006 B1
7118667 Lee Oct 2006 B2
7120483 Russell et al. Oct 2006 B2
7125382 Zhou et al. Oct 2006 B2
7131967 Gray et al. Nov 2006 B2
7134999 Brauker et al. Nov 2006 B2
7136689 Shults et al. Nov 2006 B2
7141034 Eppstein et al. Nov 2006 B2
7144496 Meserol et al. Dec 2006 B2
7146202 Ward et al. Dec 2006 B2
7150741 Erickson et al. Dec 2006 B2
7153265 Vachon Dec 2006 B2
7162290 Levin Jan 2007 B1
7163511 Conn et al. Jan 2007 B2
7166074 Reghabi et al. Jan 2007 B2
7168597 Jones et al. Jan 2007 B1
7169289 Schuelein et al. Jan 2007 B2
7171274 Starkweather et al. Jan 2007 B2
7172075 Ji Feb 2007 B1
7183102 Monfre Feb 2007 B2
7184810 Caduff et al. Feb 2007 B2
7190988 Say et al. Mar 2007 B2
7192450 Brauker et al. Mar 2007 B2
7198606 Boecker et al. Apr 2007 B2
7207968 Harcinske Apr 2007 B1
7207974 Safabash et al. Apr 2007 B2
7211074 Sansoucy May 2007 B2
7220387 Flaherty et al. May 2007 B2
7221970 Parker May 2007 B2
7223253 Hogendijk May 2007 B2
7225535 Feldman et al. Jun 2007 B2
7226978 Tapsak et al. Jun 2007 B2
7228162 Ward et al. Jun 2007 B2
7229288 Stuart et al. Jun 2007 B2
7238165 Vincent et al. Jul 2007 B2
7241266 Zhou et al. Jul 2007 B2
7241586 Gulati et al. Jul 2007 B2
7247138 Reghabi et al. Jul 2007 B2
7248906 Dirac et al. Jul 2007 B2
7254450 Christopherson et al. Aug 2007 B2
7255690 Gray et al. Aug 2007 B2
7258681 Houde Aug 2007 B2
7261690 Teller et al. Aug 2007 B2
7266400 Fine et al. Sep 2007 B2
7267665 Steil et al. Sep 2007 B2
7276029 Goode, Jr. et al. Oct 2007 B2
7276146 Wilsey Oct 2007 B2
7276147 Wilsey Oct 2007 B2
7278983 Ireland et al. Oct 2007 B2
7287318 Bhullar et al. Oct 2007 B2
7288085 Olsen Oct 2007 B2
7291497 Holmes et al. Nov 2007 B2
7295867 Berner et al. Nov 2007 B2
7299082 Feldman et al. Nov 2007 B2
7310544 Brister et al. Dec 2007 B2
7311690 Burnett Dec 2007 B2
7313425 Finarov et al. Dec 2007 B2
7314452 Madonia Jan 2008 B2
7315767 Caduff et al. Jan 2008 B2
7316662 Delnevo et al. Jan 2008 B2
7317939 Fine et al. Jan 2008 B2
7318814 Levine et al. Jan 2008 B2
7324012 Mann et al. Jan 2008 B2
7327273 Hung et al. Feb 2008 B2
7329234 Sansoucy Feb 2008 B2
7329239 Safabash et al. Feb 2008 B2
7334594 Ludin Feb 2008 B2
7335179 Burnett Feb 2008 B2
7335195 Mehier Feb 2008 B2
7335286 Abel et al. Feb 2008 B2
7335294 Heller et al. Feb 2008 B2
7338464 Blischak et al. Mar 2008 B2
7344499 Prausnitz et al. Mar 2008 B1
7344500 Talbot et al. Mar 2008 B2
7354420 Steil et al. Apr 2008 B2
7359723 Jones Apr 2008 B2
7361155 Sage, Jr. et al. Apr 2008 B2
7364562 Braig et al. Apr 2008 B2
7364592 Carr-Brendel et al. Apr 2008 B2
7366556 Brister et al. Apr 2008 B2
7366566 Henry et al. Apr 2008 B2
7367942 Grage et al. May 2008 B2
7379765 Petisce et al. May 2008 B2
7381184 Funderburk et al. Jun 2008 B2
7384397 Zhang et al. Jun 2008 B2
7386937 Bhullar et al. Jun 2008 B2
7392080 Eppstein et al. Jun 2008 B2
7395158 Monfre et al. Jul 2008 B2
7396353 Lorenzen et al. Jul 2008 B2
7399277 Saidara et al. Jul 2008 B2
7402153 Steil et al. Jul 2008 B2
7404819 Darios et al. Jul 2008 B1
7405055 Dunn et al. Jul 2008 B2
7417164 Suri Aug 2008 B2
7424318 Brister et al. Sep 2008 B2
7426408 Denuzzio et al. Sep 2008 B2
7433727 Ward et al. Oct 2008 B2
7460898 Brister et al. Dec 2008 B2
7467003 Brister et al. Dec 2008 B2
7471972 Rhodes et al. Dec 2008 B2
7494465 Brister et al. Feb 2009 B2
7497827 Brister et al. Mar 2009 B2
7519408 Rasdal et al. Apr 2009 B2
7519478 Bartkowiak et al. Apr 2009 B2
7523004 Bartkowiak et al. Apr 2009 B2
7525298 Morgan et al. Apr 2009 B2
7565197 Haubrich et al. Jul 2009 B2
7574266 Dudding et al. Aug 2009 B2
7582059 Funderburk et al. Sep 2009 B2
7583990 Goode, Jr. et al. Sep 2009 B2
7587287 Connolly et al. Sep 2009 B2
7591801 Brauker et al. Sep 2009 B2
7599726 Goode, Jr. et al. Oct 2009 B2
7602310 Mann et al. Oct 2009 B2
7604593 Parris et al. Oct 2009 B2
7613491 Boock et al. Nov 2009 B2
7615007 Shults et al. Nov 2009 B2
7618368 Brown Nov 2009 B2
7618369 Hayter et al. Nov 2009 B2
7624028 Brown Nov 2009 B1
7632228 Brauker et al. Dec 2009 B2
7636602 Baru Fassio et al. Dec 2009 B2
7637868 Saint et al. Dec 2009 B2
7640032 Jones Dec 2009 B2
7640048 Dobbles et al. Dec 2009 B2
7647237 Malave et al. Jan 2010 B2
7651596 Petisce et al. Jan 2010 B2
7654956 Brister et al. Feb 2010 B2
7657297 Simpson et al. Feb 2010 B2
7676437 Satkunanathan et al. Mar 2010 B2
7687586 Ward et al. Mar 2010 B2
7695434 Malecha Apr 2010 B2
7697967 Stafford Apr 2010 B2
7699775 Desai et al. Apr 2010 B2
7711402 Shults et al. May 2010 B2
7711493 Bartkowiak et al. May 2010 B2
7713574 Brister et al. May 2010 B2
7715893 Kamath et al. May 2010 B2
7725148 Shah et al. May 2010 B2
7727148 Talbot et al. Jun 2010 B2
7731659 Malecha Jun 2010 B2
7736322 Roe et al. Jun 2010 B2
7761126 Gardner et al. Jul 2010 B2
7766830 Fox et al. Aug 2010 B2
7771352 Shults et al. Aug 2010 B2
7774145 Brauker et al. Aug 2010 B2
7778680 Goode, Jr. et al. Aug 2010 B2
7792562 Shults et al. Sep 2010 B2
7811231 Jin et al. Oct 2010 B2
7826981 Goode, Jr. et al. Nov 2010 B2
7857760 Brister et al. Dec 2010 B2
7860545 Shults et al. Dec 2010 B2
7862622 Dunlap et al. Jan 2011 B2
7874985 Kovatchev et al. Jan 2011 B2
7875293 Shults et al. Jan 2011 B2
7879010 Hunn et al. Feb 2011 B2
7881763 Brauker et al. Feb 2011 B2
7885697 Brister et al. Feb 2011 B2
7885698 Feldman Feb 2011 B2
7890295 Shin et al. Feb 2011 B2
7896809 Simpson et al. Mar 2011 B2
7899511 Shults et al. Mar 2011 B2
7901354 Shults et al. Mar 2011 B2
7905833 Brister et al. Mar 2011 B2
7917186 Kamath et al. Mar 2011 B2
7920906 Goode, Jr. et al. Apr 2011 B2
7925321 Goode, Jr. et al. Apr 2011 B2
7927274 Rasdal et al. Apr 2011 B2
7935499 Dunn et al. May 2011 B2
7946984 Brister et al. May 2011 B2
7946985 Mastrototaro et al. May 2011 B2
7949381 Brister et al. May 2011 B2
7986986 Goode et al. Jul 2011 B2
7998071 Goode, Jr. et al. Aug 2011 B2
8000901 Brauker et al. Aug 2011 B2
8005524 Brauker et al. Aug 2011 B2
8005525 Goode, Jr. et al. Aug 2011 B2
8010174 Goode, Jr. et al. Aug 2011 B2
8019421 Darvish Sep 2011 B2
8060173 Goode, Jr. et al. Nov 2011 B2
RE43039 Brister et al. Dec 2011 E
8073520 Kamath et al. Dec 2011 B2
8095197 Santini, Jr. et al. Jan 2012 B2
8112240 Fennell Feb 2012 B2
8118877 Brauker et al. Feb 2012 B2
8133178 Brauker et al. Mar 2012 B2
8147426 Neel et al. Apr 2012 B2
8152789 Starkweather et al. Apr 2012 B2
8160669 Brauker et al. Apr 2012 B2
8160671 Kamath et al. Apr 2012 B2
8167801 Goode, Jr. et al. May 2012 B2
8170803 Kamath et al. May 2012 B2
8192395 Estes et al. Jun 2012 B2
8216139 Brauker et al. Jul 2012 B2
8229534 Brister et al. Jul 2012 B2
8231531 Brister et al. Jul 2012 B2
8233958 Brauker et al. Jul 2012 B2
8251906 Brauker et al. Aug 2012 B2
8257259 Brauker et al. Sep 2012 B2
8265725 Brauker et al. Sep 2012 B2
8275438 Simpson et al. Sep 2012 B2
8277713 Petisce et al. Oct 2012 B2
8280475 Brister et al. Oct 2012 B2
8282549 Brauker et al. Oct 2012 B2
8290559 Shariati et al. Oct 2012 B2
8290560 Kamath et al. Oct 2012 B2
8290561 Brauker et al. Oct 2012 B2
8298142 Simpson et al. Oct 2012 B2
8311749 Brauker et al. Nov 2012 B2
8313434 Brister et al. Nov 2012 B2
8321149 Brauker et al. Nov 2012 B2
8353881 Jennewine Jan 2013 B2
8355753 Bochenko et al. Jan 2013 B2
8364229 Simpson et al. Jan 2013 B2
8366614 Say et al. Feb 2013 B2
8374667 Brauker et al. Feb 2013 B2
8407097 Sperduti et al. Mar 2013 B2
8441338 Naressi et al. May 2013 B2
8452368 Brister et al. May 2013 B2
8457708 Brister et al. Jun 2013 B2
8463350 Kamath et al. Jun 2013 B2
8469886 Brauker et al. Jun 2013 B2
8474397 Brister et al. Jul 2013 B2
8475373 Brister et al. Jul 2013 B2
8483791 Brister et al. Jul 2013 B2
8506482 Feldman Aug 2013 B2
8512276 Talbot et al. Aug 2013 B2
8515516 Kamath et al. Aug 2013 B2
8515519 Brister et al. Aug 2013 B2
8548551 Kamath et al. Oct 2013 B2
8560037 Goode, Jr. et al. Oct 2013 B2
8565848 Brister et al. Oct 2013 B2
8565849 Kamath et al. Oct 2013 B2
8571625 Kamath et al. Oct 2013 B2
8579816 Kamath et al. Nov 2013 B2
8606684 Bi et al. Dec 2013 B2
8611978 Kamath et al. Dec 2013 B2
8615282 Brister et al. Dec 2013 B2
8663109 Brister et al. Mar 2014 B2
8668645 Drucker et al. Mar 2014 B2
8690775 Brister et al. Apr 2014 B2
8731630 Kamath et al. May 2014 B2
8750955 Brister et al. Jun 2014 B2
8788007 Brauker et al. Jul 2014 B2
8792953 Brister et al. Jul 2014 B2
8792954 Brister et al. Jul 2014 B2
8792955 Brister et al. Jul 2014 B2
8825127 Kamath et al. Sep 2014 B2
8858434 Kamath et al. Oct 2014 B2
8886272 Brister et al. Nov 2014 B2
8915849 Brauker et al. Dec 2014 B2
8968198 Brauker et al. Mar 2015 B2
8986209 Brauker et al. Mar 2015 B2
8989833 Brauker et al. Mar 2015 B2
9044199 Brister et al. Jun 2015 B2
9055901 Brister et al. Jun 2015 B2
9060742 Brister et al. Jun 2015 B2
9078608 Kamath et al. Jul 2015 B2
9078626 Brister et al. Jul 2015 B2
9155496 Shults et al. Oct 2015 B2
9220449 Pryor et al. Dec 2015 B2
9247900 Brister et al. Feb 2016 B2
9314196 Pryor et al. Apr 2016 B2
9414777 Brister et al. Aug 2016 B2
9603557 Brister et al. Mar 2017 B2
9610031 Brister et al. Apr 2017 B2
9610034 Heller et al. Apr 2017 B2
9668677 Brister et al. Jun 2017 B2
9669156 Jennewine Jun 2017 B2
9724028 Brauker et al. Aug 2017 B2
9775543 Brister et al. Oct 2017 B2
9801572 Brister et al. Oct 2017 B2
9814414 Brister et al. Nov 2017 B2
9833176 Brister et al. Dec 2017 B2
9918668 Pryor et al. Mar 2018 B2
10022078 Brauker et al. Jul 2018 B2
10314525 Simpson et al. Jun 2019 B2
10376188 Simpson et al. Aug 2019 B2
10524703 Brister et al. Jan 2020 B2
10610135 Kamath et al. Apr 2020 B2
10610136 Kamath et al. Apr 2020 B2
10610137 Kamath et al. Apr 2020 B2
10617336 Kamath et al. Apr 2020 B2
10709362 Simpson et al. Jul 2020 B2
10709363 Brister et al. Jul 2020 B2
10709364 Kamath et al. Jul 2020 B2
10716498 Kamath et al. Jul 2020 B2
10722152 Brister et al. Jul 2020 B2
10743801 Kamath et al. Aug 2020 B2
10799158 Brister et al. Oct 2020 B2
10813577 Brister et al. Oct 2020 B2
10827956 Brister et al. Nov 2020 B2
10918313 Brister et al. Feb 2021 B2
10918314 Brister et al. Feb 2021 B2
10918315 Brister et al. Feb 2021 B2
10932700 Simpson et al. Mar 2021 B2
10980452 Simpson et al. Apr 2021 B2
10993642 Simpson et al. May 2021 B2
11000213 Kamath et al. May 2021 B2
20010008187 Hanssen et al. Jul 2001 A1
20010016682 Berner et al. Aug 2001 A1
20010020546 Eldridge et al. Sep 2001 A1
20010021817 Brugger et al. Sep 2001 A1
20010027327 Schraga Oct 2001 A1
20010039053 Liseo et al. Nov 2001 A1
20010039387 Rutynowski et al. Nov 2001 A1
20010041830 Varalli et al. Nov 2001 A1
20010044413 Pierce et al. Nov 2001 A1
20010044588 Mault Nov 2001 A1
20010051766 Gazdzinski Dec 2001 A1
20010051768 Schulman et al. Dec 2001 A1
20010053933 Phaneuf et al. Dec 2001 A1
20010056328 Trippel et al. Dec 2001 A1
20020009810 O'Connor et al. Jan 2002 A1
20020010390 Guice et al. Jan 2002 A1
20020016535 Martin et al. Feb 2002 A1
20020019330 Murray et al. Feb 2002 A1
20020019922 Dunn et al. Feb 2002 A1
20020022883 Burg Feb 2002 A1
20020022884 Mansmann Feb 2002 A1
20020023852 McIvor et al. Feb 2002 A1
20020026110 Parris Feb 2002 A1
20020026111 Ackerman Feb 2002 A1
20020032531 Mansky et al. Mar 2002 A1
20020038081 Fein et al. Mar 2002 A1
20020042090 Heller et al. Apr 2002 A1
20020042561 Schulman et al. Apr 2002 A1
20020043471 Ikeda et al. Apr 2002 A1
20020043651 Darrow et al. Apr 2002 A1
20020045808 Ford et al. Apr 2002 A1
20020050250 Peterson et al. May 2002 A1
20020055673 Van Antwerp et al. May 2002 A1
20020065453 Lesho et al. May 2002 A1
20020068860 Clark Jun 2002 A1
20020071776 Bandis et al. Jun 2002 A1
20020072720 Hague et al. Jun 2002 A1
20020077599 Wojcik Jun 2002 A1
20020084196 Liamos et al. Jul 2002 A1
20020099282 Knobbe et al. Jul 2002 A1
20020099997 Piret Jul 2002 A1
20020100474 Kellner et al. Aug 2002 A1
20020100725 Lee et al. Aug 2002 A1
20020103499 Perez et al. Aug 2002 A1
20020111547 Knobbe et al. Aug 2002 A1
20020119711 VanAntwerp et al. Aug 2002 A1
20020196709 Potts et al. Aug 2002 A1
20020123048 Gau Sep 2002 A1
20020128419 Terry et al. Sep 2002 A1
20020128546 Silver et al. Sep 2002 A1
20020128594 Das et al. Sep 2002 A1
20020132279 Hockersmith Sep 2002 A1
20020133063 Hockersmith et al. Sep 2002 A1
20020133224 Bajgar et al. Sep 2002 A1
20020137991 Scarantino et al. Sep 2002 A1
20020151796 Koulik Oct 2002 A1
20020151816 Rich et al. Oct 2002 A1
20020155615 Novikov et al. Oct 2002 A1
20020160722 Terranova et al. Oct 2002 A1
20020161288 Shin et al. Oct 2002 A1
20020164836 Ho Nov 2002 A1
20020169369 Ward et al. Nov 2002 A1
20020169405 Roberts Nov 2002 A1
20020177763 Burns et al. Nov 2002 A1
20020177764 Sohrab Nov 2002 A1
20020182241 Borenstein et al. Dec 2002 A1
20020185384 Leong et al. Dec 2002 A1
20020186185 Ide et al. Dec 2002 A1
20020188185 Sohrab Dec 2002 A1
20020188216 Kayyali et al. Dec 2002 A1
20020188252 Bardy Dec 2002 A1
20020192885 Miyasaka Dec 2002 A1
20020193679 Malave et al. Dec 2002 A1
20020193885 Legeay et al. Dec 2002 A1
20020198513 Lebel et al. Dec 2002 A1
20030003524 Taniike et al. Jan 2003 A1
20030004432 Assenheimer Jan 2003 A1
20030004457 Andersson Jan 2003 A1
20030006669 Pei et al. Jan 2003 A1
20030009993 Silver Jan 2003 A1
20030021729 Moller et al. Jan 2003 A1
20030023171 Sato et al. Jan 2003 A1
20030023317 Brauker et al. Jan 2003 A1
20030023461 Quintanilla et al. Jan 2003 A1
20030024811 Davies et al. Feb 2003 A1
20030028089 Galley et al. Feb 2003 A1
20030032867 Crothall et al. Feb 2003 A1
20030032874 Rhodes et al. Feb 2003 A1
20030036773 Whitehurst et al. Feb 2003 A1
20030042137 Mao et al. Mar 2003 A1
20030049166 Pendo et al. Mar 2003 A1
20030050537 Wessel Mar 2003 A1
20030050546 Desai et al. Mar 2003 A1
20030054428 Monfre et al. Mar 2003 A1
20030055464 Darvish et al. Mar 2003 A1
20030059631 Al-Lamee Mar 2003 A1
20030060765 Campbell et al. Mar 2003 A1
20030065254 Schulman et al. Apr 2003 A1
20030065308 Lebel et al. Apr 2003 A1
20030070548 Clausen Apr 2003 A1
20030072741 Berglund et al. Apr 2003 A1
20030076082 Morgan et al. Apr 2003 A1
20030078481 McIvor et al. Apr 2003 A1
20030078560 Miller et al. Apr 2003 A1
20030088166 Say et al. May 2003 A1
20030091433 Tam et al. May 2003 A1
20030096424 Mao et al. May 2003 A1
20030097082 Purdy et al. May 2003 A1
20030099682 Moussy et al. May 2003 A1
20030100040 Bonnecaze et al. May 2003 A1
20030100821 Heller et al. May 2003 A1
20030104119 Wilson et al. Jun 2003 A1
20030114735 Silver et al. Jun 2003 A1
20030117296 Seely Jun 2003 A1
20030119208 Yoon et al. Jun 2003 A1
20030120152 Omiya Jun 2003 A1
20030125612 Fox et al. Jul 2003 A1
20030125613 Enegren et al. Jul 2003 A1
20030130616 Steil et al. Jul 2003 A1
20030132227 Geisler et al. Jul 2003 A1
20030134100 Mao et al. Jul 2003 A1
20030134347 Heller et al. Jul 2003 A1
20030138674 Zeikus et al. Jul 2003 A1
20030143746 Sage Jul 2003 A1
20030144581 Conn et al. Jul 2003 A1
20030146110 Karinka et al. Aug 2003 A1
20030153821 Berner et al. Aug 2003 A1
20030153900 Aceti et al. Aug 2003 A1
20030157409 Huang Aug 2003 A1
20030158520 Safabash et al. Aug 2003 A1
20030168338 Gao et al. Sep 2003 A1
20030176183 Drucker et al. Sep 2003 A1
20030176933 Lebel et al. Sep 2003 A1
20030181794 Rini et al. Sep 2003 A1
20030186457 Iwaki et al. Oct 2003 A1
20030187338 Say et al. Oct 2003 A1
20030188427 Say et al. Oct 2003 A1
20030190383 Kim Oct 2003 A1
20030191377 Robinson et al. Oct 2003 A1
20030199744 Buse et al. Oct 2003 A1
20030199745 Burson et al. Oct 2003 A1
20030199790 Boecker et al. Oct 2003 A1
20030199878 Pohjonen et al. Oct 2003 A1
20030203498 Neel et al. Oct 2003 A1
20030203991 Schottman et al. Oct 2003 A1
20030209940 Trygg et al. Oct 2003 A1
20030208113 Mault et al. Nov 2003 A1
20030211625 Cohan et al. Nov 2003 A1
20030212317 Kovatchev et al. Nov 2003 A1
20030212346 Yuzhakov et al. Nov 2003 A1
20030212347 Sohrab Nov 2003 A1
20030212379 Bylund et al. Nov 2003 A1
20030217966 Tapsak et al. Nov 2003 A1
20030225324 Anderson et al. Dec 2003 A1
20030225360 Eppstein et al. Dec 2003 A1
20030225361 Sabra Dec 2003 A1
20030225437 Ferguson Dec 2003 A1
20030228681 Ritts et al. Dec 2003 A1
20030231550 Macfarlane Dec 2003 A1
20030235817 Bartkowiak et al. Dec 2003 A1
20040002682 Kovelman et al. Jan 2004 A1
20040006263 Anderson et al. Jan 2004 A1
20040010207 Flaherty et al. Jan 2004 A1
20040011671 Shults et al. Jan 2004 A1
20040015063 Denuzzio et al. Jan 2004 A1
20040015134 Lavi et al. Jan 2004 A1
20040017570 Parikh et al. Jan 2004 A1
20040018486 Dunn et al. Jan 2004 A1
29040008761 Kelliher et al. Jan 2004
20040023253 Kunwar et al. Feb 2004 A1
20040023317 Motamedi et al. Feb 2004 A1
20040024327 Brodnick Feb 2004 A1
20040024553 Monfre et al. Feb 2004 A1
20040030285 Lavi et al. Feb 2004 A1
20040030294 Mahurkar Feb 2004 A1
20040039298 Abreu Feb 2004 A1
20040039342 Eppstein et al. Feb 2004 A1
20040039343 Eppstein et al. Feb 2004 A1
20040039406 Jessen Feb 2004 A1
20040040840 Mao et al. Mar 2004 A1
20040045879 Shults et al. Mar 2004 A1
20040047764 Purcell Mar 2004 A1
20040052689 Yao Mar 2004 A1
20040054263 Moerman et al. Mar 2004 A1
20040054352 Adams et al. Mar 2004 A1
20040064068 DeNuzzio et al. Apr 2004 A1
20040064156 Shah et al. Apr 2004 A1
20040068230 Estes et al. Apr 2004 A1
20040074785 Holker et al. Apr 2004 A1
20040078219 Kaylor et al. Apr 2004 A1
20040087671 Tamada et al. May 2004 A1
20040088023 Imran et al. May 2004 A1
20040106741 Kriesel et al. Jun 2004 A1
20040106857 Gough Jun 2004 A1
20040106858 Say et al. Jun 2004 A1
20040106859 Say et al. Jun 2004 A1
20040106860 Say et al. Jun 2004 A1
20040111017 Say et al. Jun 2004 A1
20040120848 Teodorczyk Jun 2004 A1
20040122353 Shahmirian et al. Jun 2004 A1
20040124988 Leonard et al. Jul 2004 A1
20040127777 Ruchti et al. Jul 2004 A1
20040127818 Roe et al. Jul 2004 A1
20040133131 Kuhn et al. Jul 2004 A1
20040133164 Funderburk et al. Jul 2004 A1
20040135684 Steinthal et al. Jul 2004 A1
20040138543 Russell et al. Jul 2004 A1
20040138588 Saikley et al. Jul 2004 A1
20040142483 Genshaw Jul 2004 A1
20040143173 Reghabi et al. Jul 2004 A1
20040146909 Duong et al. Jul 2004 A1
20040147872 Thompson Jul 2004 A1
20040152187 Haight et al. Aug 2004 A1
20040152622 Keith et al. Aug 2004 A1
20040158138 Kilcoyne et al. Aug 2004 A1
20040158207 Hunn et al. Aug 2004 A1
20040167382 Gardner et al. Aug 2004 A1
20040167801 Say et al. Aug 2004 A1
20040171921 Say et al. Sep 2004 A1
20040173472 Jung et al. Sep 2004 A1
20040176672 Silver et al. Sep 2004 A1
20040180391 Gratzl et al. Sep 2004 A1
20040186362 Brauker et al. Sep 2004 A1
20040186365 Jin et al. Sep 2004 A1
20040193025 Steil et al. Sep 2004 A1
20040193090 Lebel et al. Sep 2004 A1
20040197846 Hockersmith et al. Oct 2004 A1
20040199059 Brauker et al. Oct 2004 A1
20040204687 Mogensen et al. Oct 2004 A1
20040204744 Penner et al. Oct 2004 A1
20040206625 Bhullar et al. Oct 2004 A1
20040206916 Colvin, Jr. et al. Oct 2004 A1
20040207054 Brown et al. Oct 2004 A1
20040219664 Heller et al. Nov 2004 A1
20040220517 Starkweather et al. Nov 2004 A1
20040225199 Evanyk et al. Nov 2004 A1
20040225338 Lebel et al. Nov 2004 A1
20040228902 Benz Nov 2004 A1
20040231772 Leonard et al. Nov 2004 A1
20040234575 Horres et al. Nov 2004 A1
20040236200 Say et al. Nov 2004 A1
20040236251 Roe et al. Nov 2004 A1
20040242982 Sakata et al. Dec 2004 A1
20040244151 Sakata et al. Dec 2004 A1
20040249421 Harel et al. Dec 2004 A1
20040253365 Warren et al. Dec 2004 A1
20040254433 Bandis et al. Dec 2004 A1
20040254434 Goodnow et al. Dec 2004 A1
20040260164 Kilcoyne et al. Dec 2004 A1
20040260234 Srinivasan et al. Dec 2004 A1
20040263354 Mann et al. Dec 2004 A1
20040265940 Slater et al. Dec 2004 A1
20040267300 Mace Dec 2004 A1
20050000829 Morita et al. Jan 2005 A1
20050003399 Blackburn et al. Jan 2005 A1
20050003470 Nelson et al. Jan 2005 A1
20050004438 Ward et al. Jan 2005 A1
20050004439 Shin et al. Jan 2005 A1
20050004494 Perez et al. Jan 2005 A1
20050006122 Burnette Jan 2005 A1
20050008671 Van Antwerp Jan 2005 A1
20050010265 Baru et al. Jan 2005 A1
20050010269 Lebel et al. Jan 2005 A1
20050011883 Clothier et al. Jan 2005 A1
20050013842 Qiu et al. Jan 2005 A1
20050016325 Enokido Jan 2005 A1
20050023137 Bhullar et al. Feb 2005 A1
20050026689 Marks Feb 2005 A1
20050027177 Shin Feb 2005 A1
20050027181 Goode, Jr. et al. Feb 2005 A1
20050027182 Siddiqui et al. Feb 2005 A1
20050027462 Goode, Jr. et al. Feb 2005 A1
20050027463 Goode, Jr. et al. Feb 2005 A1
20050031689 Shults et al. Feb 2005 A1
20050033132 Shults et al. Feb 2005 A1
20050038332 Saidara et al. Feb 2005 A1
20050043598 Goode, Jr. et al. Feb 2005 A1
29050027180 Goode, Jr. et al. Feb 2005
20050049472 Manda et al. Mar 2005 A1
20050051427 Brauker et al. Mar 2005 A1
20050051440 Simpson et al. Mar 2005 A1
20050054909 Petisce et al. Mar 2005 A1
20050056551 White et al. Mar 2005 A1
20050056552 Simpson et al. Mar 2005 A1
20050059871 Gough et al. Mar 2005 A1
20050065464 Talbot et al. Mar 2005 A1
20050070770 Dirac et al. Mar 2005 A1
20050077584 Uhland et al. Apr 2005 A1
20050079200 Rathenow et al. Apr 2005 A1
20050080345 Finburgh et al. Apr 2005 A1
20050083527 Flaherty et al. Apr 2005 A1
20050085839 Allen et al. Apr 2005 A1
20050090607 Tapsak et al. Apr 2005 A1
20050096512 Fox et al. May 2005 A1
20050096519 Denuzzio et al. May 2005 A1
20050101847 Routt et al. May 2005 A1
20050103624 Bhullar et al. May 2005 A1
20050103625 Rhodes et al. May 2005 A1
20050106713 Phan et al. May 2005 A1
20050107677 Ward et al. May 2005 A1
20050112169 Brauker et al. May 2005 A1
20050113653 Fox et al. May 2005 A1
20050114068 Chey et al. May 2005 A1
20050115832 Simpson et al. Jun 2005 A1
20050118344 Pacetti Jun 2005 A1
20050119720 Gale et al. Jun 2005 A1
20050121322 Say et al. Jun 2005 A1
20050124873 Shults et al. Jun 2005 A1
20050131305 Danielson et al. Jun 2005 A1
20050131346 Douglas Jun 2005 A1
20050133368 Davies et al. Jun 2005 A1
20050139489 Davies et al. Jun 2005 A1
20050143635 Kamath et al. Jun 2005 A1
20050143636 Zhang et al. Jun 2005 A1
20050143675 Neel et al. Jun 2005 A1
20050151976 Toma Jul 2005 A1
20050154264 Lecompte et al. Jul 2005 A1
20050154271 Rasdal et al. Jul 2005 A1
20050154272 Dirac et al. Jul 2005 A1
20050161346 Simpson et al. Jul 2005 A1
20050173245 Feldman et al. Aug 2005 A1
20050176136 Burd et al. Aug 2005 A1
20050176678 Horres et al. Aug 2005 A1
20050177036 Shults et al. Aug 2005 A1
20050177398 Watanabe et al. Aug 2005 A1
20050181012 Saint et al. Aug 2005 A1
20050182306 Sloan Aug 2005 A1
20050182451 Griffin et al. Aug 2005 A1
20050183954 Hitchcock et al. Aug 2005 A1
20050187720 Goode, Jr. et al. Aug 2005 A1
20050192557 Brauker et al. Sep 2005 A1
20050195930 Spital et al. Sep 2005 A1
20050196747 Stiene Sep 2005 A1
20050197554 Polcha Sep 2005 A1
20050199494 Say et al. Sep 2005 A1
20050203360 Brauker et al. Sep 2005 A1
20050203364 Monfre et al. Sep 2005 A1
20050209665 Hunter et al. Sep 2005 A1
20050211571 Schulein et al. Sep 2005 A1
20050215871 Feldman et al. Sep 2005 A1
20050215872 Berner et al. Sep 2005 A1
20050215979 Kornerup et al. Sep 2005 A1
20050225361 Rhee Oct 2005 A1
20050228238 Monitzer Oct 2005 A1
20050233407 Pamidi et al. Oct 2005 A1
20050236361 Ufer et al. Oct 2005 A1
20050239154 Feldman et al. Oct 2005 A1
20050239156 Drucker et al. Oct 2005 A1
20050241957 Mao et al. Nov 2005 A1
20050242479 Petisce et al. Nov 2005 A1
20050245795 Goode, Jr. et al. Nov 2005 A1
20050245799 Brauker et al. Nov 2005 A1
20050251083 Carr-Brendel et al. Nov 2005 A1
20050258037 Hajizadeh et al. Nov 2005 A1
20050261563 Zhou et al. Nov 2005 A1
20050267325 Bouchier et al. Dec 2005 A1
20050267440 Herman et al. Dec 2005 A1
20050271546 Gerber et al. Dec 2005 A1
20050272989 Shah et al. Dec 2005 A1
20050277164 Drucker et al. Dec 2005 A1
20050282997 Ward et al. Dec 2005 A1
20050284758 Funke et al. Dec 2005 A1
20050287620 Heller et al. Dec 2005 A1
20050288596 Eigler et al. Dec 2005 A1
20060001538 Kraft et al. Jan 2006 A1
20060001550 Mann et al. Jan 2006 A1
20060003398 Heller et al. Jan 2006 A1
20060007017 Mann et al. Jan 2006 A1
20060008370 Massaro et al. Jan 2006 A1
20060010098 Goodnow et al. Jan 2006 A1
20060015020 Neale et al. Jan 2006 A1
20060015024 Brister et al. Jan 2006 A1
20060016700 Brister et al. Jan 2006 A1
20060019327 Brister et al. Jan 2006 A1
20060020186 Brister et al. Jan 2006 A1
20060020187 Brister et al. Jan 2006 A1
20060020188 Kamath et al. Jan 2006 A1
20060020189 Brister et al. Jan 2006 A1
20060020190 Kamath et al. Jan 2006 A1
20060020191 Brister et al. Jan 2006 A1
20060020192 Brister et al. Jan 2006 A1
20060025663 Talbot et al. Feb 2006 A1
20060036139 Brister et al. Feb 2006 A1
20060036140 Brister et al. Feb 2006 A1
20060036141 Kamath et al. Feb 2006 A1
20060036142 Brister et al. Feb 2006 A1
20060036143 Brister et al. Feb 2006 A1
20060036144 Brister et al. Feb 2006 A1
20060036145 Brister et al. Feb 2006 A1
20060040402 Brauker et al. Feb 2006 A1
20060042080 Say et al. Mar 2006 A1
20060047215 Newman et al. Mar 2006 A1
20060049359 Busta et al. Mar 2006 A1
20060052745 Van Antwerp et al. Mar 2006 A1
20060065527 Samproni et al. Mar 2006 A1
20060068208 Tapsak et al. Mar 2006 A1
20060074564 Bartkowiak et al. Apr 2006 A1
20060079740 Silver et al. Apr 2006 A1
20060079809 Goldberger et al. Apr 2006 A1
20060086624 Tapsak et al. Apr 2006 A1
20060094946 Kellogg et al. May 2006 A1
20060100588 Brunnberg et al. May 2006 A1
20060118415 Say et al. Jun 2006 A1
20060142651 Brister et al. Jun 2006 A1
20060155180 Brister et al. Jul 2006 A1
20060159718 Rathenow et al. Jul 2006 A1
20060159981 Heller Jul 2006 A1
20060166629 Reggiardo Jul 2006 A1
20060169599 Feldman et al. Aug 2006 A1
20060171980 Helmus et al. Aug 2006 A1
20060173444 Choy et al. Aug 2006 A1
20060183178 Gulati et al. Aug 2006 A1
20060183871 Ward et al. Aug 2006 A1
20060183984 Dobbles et al. Aug 2006 A1
20060183985 Brister et al. Aug 2006 A1
20060189856 Petisce et al. Aug 2006 A1
20060189863 Peyser et al. Aug 2006 A1
20060195029 Shults et al. Aug 2006 A1
20060198864 Shults et al. Sep 2006 A1
20060200019 Petisce et al. Sep 2006 A1
20060200020 Brister et al. Sep 2006 A1
20060200022 Brauker et al. Sep 2006 A1
20060200981 Bhullar et al. Sep 2006 A1
20060200982 Bhullar et al. Sep 2006 A1
20060204536 Shults et al. Sep 2006 A1
20060211921 Brauker et al. Sep 2006 A1
26060200970 Brister et al. Sep 2006
20060222566 Brauker et al. Oct 2006 A1
20060224108 Brauker et al. Oct 2006 A1
20060224109 Steil et al. Oct 2006 A1
20060224141 Rush et al. Oct 2006 A1
20060226985 Goodnow et al. Oct 2006 A1
20060229512 Petisce et al. Oct 2006 A1
20060235285 Brister et al. Oct 2006 A1
20060247508 Fennell Nov 2006 A1
20060247710 Goetz et al. Nov 2006 A1
20060253085 Geismar et al. Nov 2006 A1
20060253086 Moberg et al. Nov 2006 A1
20060257995 Simpson et al. Nov 2006 A1
20060257996 Simpson et al. Nov 2006 A1
20060258761 Boock et al. Nov 2006 A1
20060258929 Goode et al. Nov 2006 A1
20060263673 Kim et al. Nov 2006 A1
20060263763 Simpson et al. Nov 2006 A1
20060263839 Ward et al. Nov 2006 A1
20060264888 Moberg et al. Nov 2006 A1
20060270922 Brauker et al. Nov 2006 A1
20060270923 Brauker et al. Nov 2006 A1
20060275859 Kjaer Dec 2006 A1
20060281985 Ward et al. Dec 2006 A1
20060287691 Drew Dec 2006 A1
20060289307 Yu et al. Dec 2006 A1
20060290496 Peeters Dec 2006 A1
20060293576 Van Antwerp et al. Dec 2006 A1
20070003588 Chinn et al. Jan 2007 A1
20070007133 Mang et al. Jan 2007 A1
20070016381 Kamath et al. Jan 2007 A1
20070017805 Hodges et al. Jan 2007 A1
20070027370 Brauker et al. Feb 2007 A1
20070027381 Stafford Feb 2007 A1
20070027384 Brister et al. Feb 2007 A1
20070027385 Brister et al. Feb 2007 A1
20070032706 Kamath et al. Feb 2007 A1
20070032717 Brister et al. Feb 2007 A1
20070032718 Shults et al. Feb 2007 A1
20070038044 Dobbles et al. Feb 2007 A1
20070045902 Brauker et al. Mar 2007 A1
20070049865 Radmer et al. Mar 2007 A1
20070049873 Hansen et al. Mar 2007 A1
20070059196 Brister et al. Mar 2007 A1
20070060814 Stafford et al. Mar 2007 A1
20070066873 Kamath et al. Mar 2007 A1
20070073129 Shah et al. Mar 2007 A1
20070078320 Stafford Apr 2007 A1
20070078321 Mazza et al. Apr 2007 A1
20070078322 Stafford Apr 2007 A1
20070085995 Pesach et al. Apr 2007 A1
20070093704 Brister et al. Apr 2007 A1
20070100222 Mastrototaro et al. May 2007 A1
20070106135 Sloan et al. May 2007 A1
20070111196 Alarcon et al. May 2007 A1
20070116600 Kochar et al. May 2007 A1
20070129524 Sunkara Jun 2007 A1
20070129619 Ward et al. Jun 2007 A1
20070129621 Kellogg et al. Jun 2007 A1
20070135698 Shah et al. Jun 2007 A1
20070135699 Ward et al. Jun 2007 A1
20070142584 Schorzman et al. Jun 2007 A1
20070149875 Ouyang et al. Jun 2007 A1
20070151869 Heller et al. Jul 2007 A1
20070156033 Causey, III et al. Jul 2007 A1
20070161070 Wilsey Jul 2007 A1
20070161880 Say et al. Jul 2007 A1
20070163880 Woo et al. Jul 2007 A1
20070173706 Neinast et al. Jul 2007 A1
20070173709 Petisce et al. Jul 2007 A1
20070173710 Petisce et al. Jul 2007 A1
20070173711 Shah et al. Jul 2007 A1
20070173761 Kanderian, Jr. et al. Jul 2007 A1
20070179436 Braig et al. Aug 2007 A1
20070191701 Feldman et al. Aug 2007 A1
20070197889 Brister et al. Aug 2007 A1
20070197890 Boock et al. Aug 2007 A1
20070200254 Curry Aug 2007 A1
20070200267 Tsai Aug 2007 A1
20070202562 Curry Aug 2007 A1
20070202672 Curry Aug 2007 A1
20070203407 Hoss et al. Aug 2007 A1
20070203966 Brauker et al. Aug 2007 A1
29070203410 Say et al. Aug 2007
20070206193 Pesach Sep 2007 A1
20070208244 Brauker et al. Sep 2007 A1
20070208245 Brauker et al. Sep 2007 A1
20070208246 Brauker et al. Sep 2007 A1
20070213610 Say et al. Sep 2007 A1
20070213611 Simpson et al. Sep 2007 A1
20070215491 Heller et al. Sep 2007 A1
20070218097 Heller et al. Sep 2007 A1
20070219441 Carlin et al. Sep 2007 A1
20070219496 Kamen et al. Sep 2007 A1
20070222609 Duron et al. Sep 2007 A1
20070225579 Lucassen et al. Sep 2007 A1
20070225675 Robinson et al. Sep 2007 A1
20070227907 Shah et al. Oct 2007 A1
20070232876 Otto et al. Oct 2007 A1
20070232879 Brister et al. Oct 2007 A1
20070233013 Schoenberg Oct 2007 A1
20070235331 Simpson et al. Oct 2007 A1
20070240497 Robinson et al. Oct 2007 A1
20070244381 Robinson et al. Oct 2007 A1
20070244382 Robinson et al. Oct 2007 A1
20070244383 Talbot et al. Oct 2007 A1
20070249916 Pesach et al. Oct 2007 A1
20070249922 Peyser et al. Oct 2007 A1
20070255114 Ackermann et al. Nov 2007 A1
20070255126 Moberg et al. Nov 2007 A1
20070255531 Drew Nov 2007 A1
20070258395 Jollota et al. Nov 2007 A1
20070259217 Logan Nov 2007 A1
20070275193 DeSimone et al. Nov 2007 A1
20070276211 Mir et al. Nov 2007 A1
20070282180 Caduff et al. Dec 2007 A1
20070299385 Santini, Jr. et al. Dec 2007 A1
20070299409 Whitbourne et al. Dec 2007 A1
20080001318 Schorzman et al. Jan 2008 A1
20080009692 Stafford Jan 2008 A1
20080017522 Heller et al. Jan 2008 A1
20080021666 Goode, Jr. et al. Jan 2008 A1
20080027245 Suri Jan 2008 A1
20080029390 Roche et al. Feb 2008 A1
20080029391 Mao et al. Feb 2008 A1
20080030369 Mann et al. Feb 2008 A1
20080033254 Kamath et al. Feb 2008 A1
20080033268 Stafford Feb 2008 A1
20080033269 Zhang Feb 2008 A1
20080034972 Gough et al. Feb 2008 A1
20080039702 Hayter et al. Feb 2008 A1
20080045824 Tapsak et al. Feb 2008 A1
20080064941 Funderburk et al. Mar 2008 A1
20080064943 Talbot et al. Mar 2008 A1
20080064944 VanAntwerp et al. Mar 2008 A1
20080070231 Franciskovich et al. Mar 2008 A1
20080071156 Brister et al. Mar 2008 A1
20080071157 McGarraugh et al. Mar 2008 A1
20080071158 McGarraugh et al. Mar 2008 A1
20080071328 Haubrich et al. Mar 2008 A1
20080072663 Keenan et al. Mar 2008 A1
20080081969 Feldman et al. Apr 2008 A1
20080083617 Simpson et al. Apr 2008 A1
20080086040 Heller et al. Apr 2008 A1
20080086041 Heller et al. Apr 2008 A1
20080086042 Brister et al. Apr 2008 A1
20080086043 Heller et al. Apr 2008 A1
20080086044 Brister et al. Apr 2008 A1
20080086273 Shults et al. Apr 2008 A1
20080091094 Heller et al. Apr 2008 A1
20080091095 Heller et al. Apr 2008 A1
20080108942 Brister et al. May 2008 A1
20080119703 Brister et al. May 2008 A1
20080119704 Brister et al. May 2008 A1
20080119705 Patel et al. May 2008 A1
20080119706 Brister et al. May 2008 A1
20080119707 Stafford May 2008 A1
20080125751 Fjield et al. May 2008 A1
20080139910 Mastrototaro et al. Jun 2008 A1
20080154101 Jain et al. Jun 2008 A1
20080159913 Jung et al. Jul 2008 A1
20080161666 Feldman et al. Jul 2008 A1
20080183060 Steil et al. Jul 2008 A1
20080183061 Goode et al. Jul 2008 A1
20080183399 Goode et al. Jul 2008 A1
20080187655 Markle et al. Aug 2008 A1
20080188722 Markle et al. Aug 2008 A1
20080188725 Markle et al. Aug 2008 A1
20080188731 Brister et al. Aug 2008 A1
20080188796 Steil et al. Aug 2008 A1
20080189051 Goode et al. Aug 2008 A1
20080193936 Squirrell Aug 2008 A1
20080194837 Kim et al. Aug 2008 A1
20080194935 Brister et al. Aug 2008 A1
20080194936 Goode et al. Aug 2008 A1
20080194937 Goode et al. Aug 2008 A1
20080194938 Brister et al. Aug 2008 A1
20080195232 Carr-Brendel et al. Aug 2008 A1
20080195967 Goode et al. Aug 2008 A1
20080197024 Simpson et al. Aug 2008 A1
20080200788 Brister et al. Aug 2008 A1
20080200789 Brister et al. Aug 2008 A1
20080200791 Simpson et al. Aug 2008 A1
20080208025 Shults et al. Aug 2008 A1
20080210557 Heller et al. Sep 2008 A1
20080214915 Brister et al. Sep 2008 A1
20080214918 Brister et al. Sep 2008 A1
20080228051 Shults et al. Sep 2008 A1
20080228054 Shults et al. Sep 2008 A1
20080235469 Drew Sep 2008 A1
20080242961 Brister et al. Oct 2008 A1
20080255438 Saidara et al. Oct 2008 A1
20080255440 Eilersen et al. Oct 2008 A1
20080262334 Dunn et al. Oct 2008 A1
20080262469 Brister et al. Oct 2008 A1
20080275313 Brister et al. Nov 2008 A1
20080275326 Kasielke et al. Nov 2008 A1
20080287764 Rasdal et al. Nov 2008 A1
20080287765 Rasdal et al. Nov 2008 A1
20080287766 Rasdal et al. Nov 2008 A1
20080296155 Shults et al. Dec 2008 A1
20080305009 Gamsey et al. Dec 2008 A1
20080305506 Suri Dec 2008 A1
20080306368 Goode, Jr. et al. Dec 2008 A1
20080306433 Cesaroni Dec 2008 A1
20080306434 Dobbles et al. Dec 2008 A1
20080306435 Kamath et al. Dec 2008 A1
20080306444 Brister et al. Dec 2008 A1
20080312397 Lai et al. Dec 2008 A1
20080312518 Jina et al. Dec 2008 A1
20080312859 Skyggebjerg et al. Dec 2008 A1
20080313896 Shah et al. Dec 2008 A1
20090005666 Shin et al. Jan 2009 A1
20090012379 Goode, Jr. et al. Jan 2009 A1
20090018418 Markle et al. Jan 2009 A1
20090018424 Kamath et al. Jan 2009 A1
20090018425 Ouyang et al. Jan 2009 A1
20090018426 Markle et al. Jan 2009 A1
20090020502 Bhullar et al. Jan 2009 A1
20090030294 Petisce et al. Jan 2009 A1
20090036758 Brauker et al. Feb 2009 A1
20090036763 Brauker et al. Feb 2009 A1
20090043181 Brauker et al. Feb 2009 A1
20090043182 Brauker et al. Feb 2009 A1
20090043525 Brauker et al. Feb 2009 A1
20090043541 Brauker et al. Feb 2009 A1
20090043542 Brauker et al. Feb 2009 A1
20090045055 Rhodes et al. Feb 2009 A1
20090054748 Feldman Feb 2009 A1
20090054812 Mace Feb 2009 A1
20090061528 Suri Mar 2009 A1
20090062633 Brauker et al. Mar 2009 A1
20090062635 Brauker et al. Mar 2009 A1
20090062645 Fehre et al. Mar 2009 A1
20090076356 Simpson et al. Mar 2009 A1
20090076360 Brister et al. Mar 2009 A1
20090076361 Kamath et al. Mar 2009 A1
20090081803 Gamsey et al. Mar 2009 A1
20090085768 Patel et al. Apr 2009 A1
20090099434 Liu et al. Apr 2009 A1
20090099436 Brister et al. Apr 2009 A1
20090112478 Mueller, Jr. et al. Apr 2009 A1
20090124877 Goode, Jr. et al. May 2009 A1
20090124878 Goode, Jr. et al. May 2009 A1
20090124879 Brister et al. May 2009 A1
20090124964 Leach et al. May 2009 A1
20090131768 Simpson et al. May 2009 A1
20090131769 Leach et al. May 2009 A1
20090131776 Simpson et al. May 2009 A1
20090131777 Simpson et al. May 2009 A1
20090137886 Shariati et al. May 2009 A1
20090137887 Shariati et al. May 2009 A1
20090143659 Li et al. Jun 2009 A1
20090143660 Brister et al. Jun 2009 A1
20090150186 Cohen et al. Jun 2009 A1
20090156919 Brister et al. Jun 2009 A1
20090156924 Shariati et al. Jun 2009 A1
20090163790 Brister et al. Jun 2009 A1
20090163791 Brister et al. Jun 2009 A1
20090177059 Say et al. Jul 2009 A1
20090177060 Say et al. Jul 2009 A1
20090177143 Markle et al. Jul 2009 A1
20090178459 Li et al. Jul 2009 A1
20090182217 Li et al. Jul 2009 A1
20090187090 Say et al. Jul 2009 A1
20090187091 Say et al. Jul 2009 A1
20090192366 Mensinger et al. Jul 2009 A1
20090192380 Shariati et al. Jul 2009 A1
20090192722 Shariati et al. Jul 2009 A1
20090192724 Brauker et al. Jul 2009 A1
20090192745 Kamath et al. Jul 2009 A1
20090192751 Kamath et al. Jul 2009 A1
20090203981 Brauker et al. Aug 2009 A1
20090204340 Feldman et al. Aug 2009 A1
20090204341 Brauker et al. Aug 2009 A1
20090216103 Brister et al. Aug 2009 A1
20090240120 Mensinger et al. Sep 2009 A1
20090240128 Mensinger et al. Sep 2009 A1
20090240193 Mensinger et al. Sep 2009 A1
20090242399 Kamath et al. Oct 2009 A1
20090242425 Kamath et al. Oct 2009 A1
20090247855 Boock et al. Oct 2009 A1
20090247856 Boock et al. Oct 2009 A1
20090247857 Harper et al. Oct 2009 A1
20090264719 Markle et al. Oct 2009 A1
20090264856 Lebel et al. Oct 2009 A1
20090287073 Boock et al. Nov 2009 A1
20090287074 Shults et al. Nov 2009 A1
20090299155 Yang et al. Dec 2009 A1
20090299156 Simpson et al. Dec 2009 A1
20090299162 Brauker et al. Dec 2009 A1
20090299276 Brauker et al. Dec 2009 A1
20090310743 Carpenter et al. Dec 2009 A1
20100010324 Brauker et al. Jan 2010 A1
20100010330 Rankers et al. Jan 2010 A1
20100010331 Brauker et al. Jan 2010 A1
20100010332 Brauker et al. Jan 2010 A1
20100016687 Brauker et al. Jan 2010 A1
20100016698 Rasdal et al. Jan 2010 A1
20100022855 Brauker et al. Jan 2010 A1
20100030038 Brauker et al. Feb 2010 A1
20100030053 Goode, Jr. et al. Feb 2010 A1
20100030484 Brauker et al. Feb 2010 A1
20100030485 Brauker et al. Feb 2010 A1
20100036215 Goode, Jr. et al. Feb 2010 A1
20100036216 Goode, Jr. et al. Feb 2010 A1
20100036222 Goode, Jr. et al. Feb 2010 A1
20100036223 Goode, Jr. et al. Feb 2010 A1
20100036224 Goode, Jr. et al. Feb 2010 A1
20100036225 Goode, Jr. et al. Feb 2010 A1
20100041971 Goode, Jr. et al. Feb 2010 A1
20100045465 Brauker et al. Feb 2010 A1
20100049024 Saint et al. Feb 2010 A1
20100063373 Kamath et al. Mar 2010 A1
20100069728 Funderburk et al. Mar 2010 A1
20100076283 Simpson et al. Mar 2010 A1
20100081908 Dobbles et al. Apr 2010 A1
20100081910 Brister et al. Apr 2010 A1
20100087721 Stafford Apr 2010 A1
20100087724 Brauker et al. Apr 2010 A1
20100096259 Zhang et al. Apr 2010 A1
20100099970 Shults et al. Apr 2010 A1
20100099971 Shults et al. Apr 2010 A1
20100113897 Brenneman et al. May 2010 A1
20100119693 Tapsak et al. May 2010 A1
20100121169 Petisce et al. May 2010 A1
20100161269 Kamath et al. Jun 2010 A1
20100168543 Kamath et al. Jul 2010 A1
20100168545 Kamath et al. Jul 2010 A1
20100168546 Kamath et al. Jul 2010 A1
20100174157 Brister et al. Jul 2010 A1
20100174158 Kamath et al. Jul 2010 A1
20100174163 Brister et al. Jul 2010 A1
20100174164 Brister et al. Jul 2010 A1
20100174165 Brister et al. Jul 2010 A1
20100174166 Brister et al. Jul 2010 A1
20100174167 Kamath et al. Jul 2010 A1
20100174168 Goode, Jr. et al. Jul 2010 A1
20100179399 Goode, Jr. et al. Jul 2010 A1
20100179400 Brauker et al. Jul 2010 A1
20100179401 Rasdal et al. Jul 2010 A1
20100179402 Goode, Jr. et al. Jul 2010 A1
20100179404 Kamath et al. Jul 2010 A1
20100179405 Goode, Jr. et al. Jul 2010 A1
20100179406 Goode, Jr. et al. Jul 2010 A1
20100179407 Goode, Jr. et al. Jul 2010 A1
20100179408 Kamath et al. Jul 2010 A1
20100185065 Goode, Jr. et al. Jul 2010 A1
20100185069 Brister et al. Jul 2010 A1
20100185070 Brister et al. Jul 2010 A1
20100185071 Simpson et al. Jul 2010 A1
20100185072 Goode, Jr. et al. Jul 2010 A1
20100185073 Goode, Jr. et al. Jul 2010 A1
20100185074 Goode, Jr. et al. Jul 2010 A1
20100185075 Brister et al. Jul 2010 A1
20100191082 Brister et al. Jul 2010 A1
29100179409 Kamath et al. Jul 2010
20100198035 Kamath et al. Aug 2010 A1
20100204555 Shults et al. Aug 2010 A1
20100212583 Brister et al. Aug 2010 A1
20100214104 Goode, Jr. et al. Aug 2010 A1
20100217106 Goode, Jr. et al. Aug 2010 A1
20100217555 Kamath et al. Aug 2010 A1
20100234707 Goode, Jr. et al. Sep 2010 A1
20100234796 Kamath et al. Sep 2010 A1
20100235106 Kamath et al. Sep 2010 A1
20100240975 Goode, Jr. et al. Sep 2010 A1
20100240976 Goode, Jr. et al. Sep 2010 A1
20100256779 Brauker et al. Oct 2010 A1
20100286496 Simpson et al. Nov 2010 A1
20100305869 Brauker et al. Dec 2010 A1
20100331648 Kamath et al. Dec 2010 A1
20100331655 Kamath et al. Dec 2010 A1
20100331656 Mensinger et al. Dec 2010 A1
20100331657 Mensinger et al. Dec 2010 A1
20110009727 Mensinger et al. Jan 2011 A1
20110027127 Simpson et al. Feb 2011 A1
20110028815 Simpson et al. Feb 2011 A1
20110028816 Simpson et al. Feb 2011 A1
20110046467 Simpson et al. Feb 2011 A1
20110087196 Hunn et al. Apr 2011 A1
20110118579 Goode, Jr. et al. May 2011 A1
20110124992 Brauker et al. May 2011 A1
20110124997 Goode, Jr. et al. May 2011 A1
20110128052 Fujibe et al. Jun 2011 A1
20110130639 Feldman Jun 2011 A1
20110130970 Goode, Jr. et al. Jun 2011 A1
20110136249 Stiene Jun 2011 A1
20110137601 Goode, Jr. et al. Jun 2011 A1
20110144465 Shults et al. Jun 2011 A1
20110178378 Brister et al. Jul 2011 A1
20110190614 Brister et al. Aug 2011 A1
20110201910 Rasdal et al. Aug 2011 A1
20110218414 Kamath et al. Sep 2011 A1
20110231107 Brauker et al. Sep 2011 A1
20110231140 Goode, Jr. et al. Sep 2011 A1
20110231141 Goode, Jr. et al. Sep 2011 A1
20110231142 Goode, Jr. et al. Sep 2011 A1
20110253533 Shults et al. Oct 2011 A1
20110257895 Brauker et al. Oct 2011 A1
20110263958 Brauker et al. Oct 2011 A1
20110270158 Brauker et al. Nov 2011 A1
20110290645 Brister et al. Dec 2011 A1
20110313543 Brauker et al. Dec 2011 A1
20110319739 Kamath et al. Dec 2011 A1
20120130214 Brister et al. May 2012 A1
20120172691 Brauker et al. Jul 2012 A1
20120265042 Neinast et al. Oct 2012 A1
20120277562 Brister et al. Nov 2012 A1
20120277566 Kamath et al. Nov 2012 A1
20130012798 Brister et al. Jan 2013 A1
20130060112 Pryor et al. Mar 2013 A1
20130131478 Simpson et al. May 2013 A1
20130255570 Brister et al. Oct 2013 A1
20130267808 Brister et al. Oct 2013 A1
20130281931 Hunn et al. Oct 2013 A1
20130296677 Pryor et al. Nov 2013 A1
20140128704 Simpson et al. May 2014 A1
20140142405 Brister et al. May 2014 A1
20140257065 Brister et al. Sep 2014 A1
20140288402 Brister et al. Sep 2014 A1
20160008029 Brister et al. Jan 2016 A1
20160051173 Brister et al. Feb 2016 A1
20160183856 Pryor et al. Jun 2016 A1
20160310051 Brister et al. Oct 2016 A1
20170196491 Brister et al. Jul 2017 A1
20170367627 Brister et al. Dec 2017 A1
20180014762 Brister et al. Jan 2018 A1
20180049682 Brister et al. Feb 2018 A1
20180055423 Pryor et al. Mar 2018 A1
20180140236 Brister et al. May 2018 A1
20180160949 Brister et al. Jun 2018 A1
20180242894 Brauker et al. Aug 2018 A1
20180303394 Brauker et al. Oct 2018 A1
20190015020 Brister et al. Jan 2019 A1
20190069817 Brister et al. Mar 2019 A1
20190076071 Brister et al. Mar 2019 A1
20190246965 Simpson et al. Aug 2019 A1
20190320951 Pryor et al. Oct 2019 A1
20190320952 Pryor et al. Oct 2019 A1
20190320953 Pryor et al. Oct 2019 A1
20190320954 Pryor et al. Oct 2019 A1
20190320955 Pryor et al. Oct 2019 A1
20190320956 Pryor et al. Oct 2019 A1
20190320957 Pryor et al. Oct 2019 A1
20190343436 Pryor et al. Nov 2019 A1
20190350503 Pryor et al. Nov 2019 A1
20190350504 Pryor et al. Nov 2019 A1
20190357821 Brister et al. Nov 2019 A1
20190357822 Pryor et al. Nov 2019 A1
20200077928 Brister et al. Mar 2020 A1
20200077932 Simpson et al. Mar 2020 A1
20200085350 Simpson et al. Mar 2020 A1
20200085351 Simpson et al. Mar 2020 A1
20200085354 Pryor et al. Mar 2020 A1
20200085355 Pryor et al. Mar 2020 A1
20200085356 Pryor et al. Mar 2020 A1
20200100713 Simpson et al. Apr 2020 A1
20200100714 Simpson et al. Apr 2020 A1
20200100715 Pryor et al. Apr 2020 A1
20200138346 Brister et al. May 2020 A1
20200155049 Pryor et al. May 2020 A1
20200155050 Pryor et al. May 2020 A1
20200178861 Brister Jun 2020 A1
20200178862 Brister Jun 2020 A1
20200178863 Brister Jun 2020 A1
20200196924 Brister Jun 2020 A1
20200405203 Brister et al. Dec 2020 A1
Foreign Referenced Citations (610)
Number Date Country
2127172 Jul 1998 CA
101026994 Aug 2007 CN
2658734 Jun 1978 DE
3144459 Oct 1982 DE
3933373 Apr 1991 DE
4105222 Aug 1992 DE
3933373 Sep 1992 DE
4401400 Jul 1995 DE
20110059 Aug 2002 DE
10117285 Nov 2002 DE
0098592 Jan 1984 EP
0107634 May 1984 EP
0127958 Dec 1984 EP
0143517 Jun 1985 EP
0139277 Jun 1988 EP
0282349 Sep 1988 EP
0284518 Sep 1988 EP
0286039 Oct 1988 EP
0286118 Oct 1988 EP
0288793 Nov 1988 EP
0143517 Apr 1989 EP
0314027 May 1989 EP
0319277 Jun 1989 EP
0320109 Jun 1989 EP
0351892 Jan 1990 EP
0352138 Jan 1990 EP
0352610 Jan 1990 EP
0352631 Jan 1990 EP
0352708 Jan 1990 EP
0353328 Feb 1990 EP
0390390 Oct 1990 EP
0396788 Nov 1990 EP
0406473 Jan 1991 EP
0420021 Apr 1991 EP
0440044 Aug 1991 EP
0441252 Aug 1991 EP
0441394 Aug 1991 EP
0457292 Nov 1991 EP
0467078 Jan 1992 EP
0471391 Feb 1992 EP
0473065 Mar 1992 EP
0476980 Mar 1992 EP
0275139 Apr 1992 EP
0477501 Apr 1992 EP
0494704 Sep 1992 EP
0494705 Sep 1992 EP
0508388 Oct 1992 EP
0512122 Nov 1992 EP
0520430 Dec 1992 EP
0520443 Dec 1992 EP
0262328 Jan 1993 EP
0319277 Mar 1993 EP
0534074 Mar 1993 EP
0535898 Apr 1993 EP
0539625 May 1993 EP
0264036 Jun 1993 EP
0351891 Sep 1993 EP
0563795 Oct 1993 EP
0567725 Nov 1993 EP
0323605 Jan 1994 EP
0279069 Jul 1994 EP
0595474 Jul 1994 EP
0561966 Oct 1994 EP
0286118 Jan 1995 EP
0478550 Jan 1995 EP
0647849 Apr 1995 EP
0424634 Jun 1995 EP
0677743 Oct 1995 EP
0191640 Nov 1995 EP
0424633 Jan 1996 EP
0690134 Jan 1996 EP
0534074 Mar 1996 EP
0709677 May 1996 EP
0532187 Oct 1996 EP
0470652-81 Dec 1996 EP
0476715 Dec 1996 EP
0747069 Dec 1996 EP
0776628 Jun 1997 EP
0387696 Aug 1997 EP
0593096 Dec 1997 EP
0817809 Jan 1998 EP
0838230 Apr 1998 EP
0880936 Dec 1998 EP
0885932 Dec 1998 EP
0587008 Feb 1999 EP
0967788 Dec 1999 EP
0995805 Apr 2000 EP
0678308 May 2000 EP
1048264 Nov 2000 EP
1077634 Feb 2001 EP
1078258 Feb 2001 EP
1028320 Mar 2001 EP
1111378 Jun 2001 EP
1112717 Jul 2001 EP
1112718 Jul 2001 EP
1120084 Aug 2001 EP
1120085 Aug 2001 EP
1120650 Aug 2001 EP
1130386 Sep 2001 EP
1153571 Nov 2001 EP
0777122 Apr 2002 EP
0817809 Jul 2002 EP
1251137 Oct 2002 EP
0958495 Nov 2002 EP
1258728 Nov 2002 EP
1266607 Dec 2002 EP
1281351 Feb 2003 EP
0824900 Apr 2003 EP
1340980 Sep 2003 EP
1340981 Sep 2003 EP
1077636 Jan 2004 EP
0674176 Feb 2004 EP
1391728 Feb 2004 EP
0846776 Mar 2004 EP
1413245 Apr 2004 EP
1430831 Jun 2004 EP
1498067 Jan 2005 EP
1498428 Jan 2005 EP
1614464 Jan 2006 EP
0922959 Oct 2006 EP
1717924 Nov 2006 EP
0877252 Jan 2007 EP
1234053 Apr 2007 EP
1798542 Jun 2007 EP
1286164 Jul 2007 EP
1804650 Jul 2007 EP
1612560 Oct 2007 EP
1905514 Apr 2008 EP
1582874 Jul 2008 EP
1977829 Oct 2008 EP
1982644 Oct 2008 EP
1457913 Dec 2008 EP
2223710 Sep 2010 EP
2226086 Sep 2010 EP
2228642 Sep 2010 EP
2236077 Oct 2010 EP
2327362 Jun 2011 EP
1413879 Jan 2012 EP
2407094 Jan 2012 EP
2329770 Sep 2014 EP
2407094 Oct 2014 EP
2335584 Jun 2015 EP
3797682 Mar 2021 EP
3797682 Mar 2021 EP
3821803 May 2021 EP
2656423 Jun 1991 FR
2760962 Sep 1998 FR
1442303 Jul 1976 GB
1556969 Dec 1979 GB
2149918 Jun 1985 GB
2230865 Oct 1990 GB
S5441190 Apr 1979 JP
S57156004 Sep 1982 JP
S58124912 Jul 1983 JP
S59211459 Nov 1984 JP
S61271418 Dec 1986 JP
S6283649 Apr 1987 JP
S6283849 Apr 1987 JP
H022913 Jan 1990 JP
H03293556 Dec 1991 JP
H06288853 Oct 1994 JP
H06307898 Nov 1994 JP
H0783871 Mar 1995 JP
H11258381 Sep 1999 JP
2000060826 Feb 2000 JP
2000149072 May 2000 JP
2002513602 May 2002 JP
2002189015 Jul 2002 JP
2003108679 Apr 2003 JP
2003297163 Oct 2003 JP
WO-8103614 Dec 1981 WO
WO-8706342 Oct 1987 WO
WO-8706706 Nov 1987 WO
WO-8808137 Oct 1988 WO
WO-8902720 Apr 1989 WO
WO-8904302 May 1989 WO
WO-8907263 Aug 1989 WO
WO-9000738 Jan 1990 WO
WO-9002938 Mar 1990 WO
WO-9005296 May 1990 WO
WO-9005301 May 1990 WO
WO-9005302 May 1990 WO
WO-9005910 May 1990 WO
WO-9007525 Jul 1990 WO
WO-9007575 Jul 1990 WO
WO-9010716 Sep 1990 WO
WO-9010861 Sep 1990 WO
WO-9013021 Nov 1990 WO
WO-9109302 Jun 1991 WO
WO-9115993 Oct 1991 WO
WO-9116416 Oct 1991 WO
WO-9117259 Nov 1991 WO
WO-9201315 Jan 1992 WO
WO-9201928 Feb 1992 WO
WO-9207525 May 1992 WO
WO-9208985 May 1992 WO
WO-9210584 Jun 1992 WO
WO-9212255 Jul 1992 WO
WO-921327 Aug 1992 WO
WO-9214138 Aug 1992 WO
WO-9214139 Aug 1992 WO
WO-9218887 Oct 1992 WO
WO-9221772 Dec 1992 WO
WO-9301308 Jan 1993 WO
WO-9302703 Feb 1993 WO
WO-9303362 Feb 1993 WO
WO-9305701 Apr 1993 WO
WO-9312256 Jun 1993 WO
WO-9313048 Jul 1993 WO
WO-9313408 Jul 1993 WO
WO-9314185 Jul 1993 WO
WO-9314693 Aug 1993 WO
WO-9319370 Sep 1993 WO
WO-9319701 Oct 1993 WO
WO-9320240 Oct 1993 WO
WO-9320440 Oct 1993 WO
WO-9320441 Oct 1993 WO
WO-9320443 Oct 1993 WO
WO-9320444 Oct 1993 WO
WO-9320450 Oct 1993 WO
WO-9323744 Nov 1993 WO
WO-9406011 Mar 1994 WO
WO-9406012 Mar 1994 WO
WO-9408236 Apr 1994 WO
WO-9409506 Apr 1994 WO
WO-9409507 Apr 1994 WO
WO-9419695 Sep 1994 WO
WO-9421642 Sep 1994 WO
WO-9421643 Sep 1994 WO
WO-9421644 Sep 1994 WO
WO-9422367 Oct 1994 WO
WO-9426414 Nov 1994 WO
WO-9502357 Jan 1995 WO
WO-9507109 Mar 1995 WO
WO-9508774 Mar 1995 WO
WO-9510044 Apr 1995 WO
WO-9511454 Apr 1995 WO
WO-9513838 May 1995 WO
WO-9517966 Jul 1995 WO
WO-9522597 Aug 1995 WO
WO-9528878 Nov 1995 WO
WO-9534814 Dec 1995 WO
WO-9601611 Jan 1996 WO
WO-9603117 Feb 1996 WO
WO-9605501 Feb 1996 WO
WO-9606947 Mar 1996 WO
WO-9614026 May 1996 WO
WO-9622991 Aug 1996 WO
WO-9622992 Aug 1996 WO
WO-9624690 Aug 1996 WO
WO-9625088 Aug 1996 WO
WO-9625089 Aug 1996 WO
WO-9630431 Oct 1996 WO
WO-9632076 Oct 1996 WO
WO-9635370 Nov 1996 WO
WO-9636296 Nov 1996 WO
WO-9636870 Nov 1996 WO
WO-9641179 Dec 1996 WO
WO-9701986 Jan 1997 WO
WO-9702811 Jan 1997 WO
WO-9706727 Feb 1997 WO
WO-9711080 Mar 1997 WO
WO-9713874 Apr 1997 WO
WO-9717884 May 1997 WO
WO-9719188 May 1997 WO
WO-9719344 May 1997 WO
WO-9728737 Aug 1997 WO
WO-9730628 Aug 1997 WO
WO-9733176 Sep 1997 WO
WO-9738625 Oct 1997 WO
WO-9743633 Nov 1997 WO
WO-9801071 Jan 1998 WO
WO-9804902 Feb 1998 WO
WO-9806423 Feb 1998 WO
WO-9819159 May 1998 WO
WO-9824358 Jun 1998 WO
WO-9824366 Jun 1998 WO
WO-9833549 Aug 1998 WO
WO-9834541 Aug 1998 WO
WO-9835053 Aug 1998 WO
WO-9838904 Sep 1998 WO
WO-9838906 Sep 1998 WO
WO-9841854 Sep 1998 WO
WO-9842249 Oct 1998 WO
WO-9844347 Oct 1998 WO
WO-9844348 Oct 1998 WO
WO-9845331 Oct 1998 WO
WO-9845427 Oct 1998 WO
WO-9852043 Nov 1998 WO
WO-9856293 Dec 1998 WO
WO-9856923 Dec 1998 WO
WO-9858250 Dec 1998 WO
WO-9904043 Jan 1999 WO
WO-9912607 Mar 1999 WO
WO-9913101 Mar 1999 WO
WO-9913574 Mar 1999 WO
WO-9927848 Jun 1999 WO
WO-9927852 Jun 1999 WO
WO-9929230 Jun 1999 WO
WO-9929429 Jun 1999 WO
WO-9929892 Jun 1999 WO
WO-9931504 Jun 1999 WO
WO-9933504 Jul 1999 WO
WO-9940848 Aug 1999 WO
WO-9948419 Sep 1999 WO
WO-9949856 Oct 1999 WO
WO-9956613 Nov 1999 WO
WO-9958051 Nov 1999 WO
WO-9958709 Nov 1999 WO
WO-9958973 Nov 1999 WO
WO-9959657 Nov 1999 WO
WO-9964620 Dec 1999 WO
WO-0007013 Feb 2000 WO
WO-0012720 Mar 2000 WO
WO-0013002 Mar 2000 WO
WO-0013003 Mar 2000 WO
WO-0018449 Apr 2000 WO
WO-0019887 Apr 2000 WO
WO-0020626 Apr 2000 WO
WO-0030530 Jun 2000 WO
WO-0032098 Jun 2000 WO
WO-0033065 Jun 2000 WO
WO-0035530 Jun 2000 WO
WO-0045696 Aug 2000 WO
WO-0049940 Aug 2000 WO
WO-0049941 Aug 2000 WO
WO-0049942 Aug 2000 WO
WO-0059370 Oct 2000 WO
WO-0059373 Oct 2000 WO
WO-0074753 Dec 2000 WO
WO-0078210 Dec 2000 WO
WO-0078992 Dec 2000 WO
WO-0079258 Dec 2000 WO
WO-0100865 Jan 2001 WO
WO-0109096 Feb 2001 WO
WO-0112158 Feb 2001 WO
WO-0116579 Mar 2001 WO
WO-0120019 Mar 2001 WO
WO-0120334 Mar 2001 WO
WO-0121827 Mar 2001 WO
WO-0134243 May 2001 WO
WO-0136666 May 2001 WO
WO-0143660 Jun 2001 WO
WO-0152727 Jul 2001 WO
WO-0152935 Jul 2001 WO
WO-019425 Aug 2001 WO
WO-0154753 Aug 2001 WO
WO-0158347 Aug 2001 WO
WO-0158348 Aug 2001 WO
WO-0164105 Sep 2001 WO
WO-0168901 Sep 2001 WO
WO-0169222 Sep 2001 WO
WO-0173109 Oct 2001 WO
WO-0188524 Nov 2001 WO
WO-0188534 Nov 2001 WO
WO-0191634 Dec 2001 WO
WO-0202755 Jan 2002 WO
WO-0205702 Jan 2002 WO
WO-0207596 Jan 2002 WO
WO-0207617 Jan 2002 WO
WO-0215778 Feb 2002 WO
WO-0216535 Feb 2002 WO
WO-0216905 Feb 2002 WO
WO-0217780 Mar 2002 WO
WO-0224065 Mar 2002 WO
WO-0233407 Apr 2002 WO
WO-0078210 May 2002 WO
WO-0243585 Jun 2002 WO
WO-02056751 Jul 2002 WO
WO-02058537 Aug 2002 WO
WO-02062210 Aug 2002 WO
WO-02066509 Aug 2002 WO
WO-02066986 Aug 2002 WO
WO-02074161 Sep 2002 WO
WO-02082989 Oct 2002 WO
WO-02087681 Nov 2002 WO
WO-02089666 Nov 2002 WO
WO-02097414 Dec 2002 WO
WO-02099097 Dec 2002 WO
WO-02099428 Dec 2002 WO
WO-02100266 Dec 2002 WO
WO-02100457 Dec 2002 WO
WO-02100474 Dec 2002 WO
WO-03000127 Jan 2003 WO
WO-03008013 Jan 2003 WO
WO-03008014 Jan 2003 WO
WO-03009207 Jan 2003 WO
WO-03009208 Jan 2003 WO
WO-03011131 Feb 2003 WO
WO-03012422 Feb 2003 WO
WO-03022327 Mar 2003 WO
WO-03028797 Apr 2003 WO
WO-03032411 Apr 2003 WO
WO-03033726 Apr 2003 WO
WO-03035117 May 2003 WO
WO-03036310 May 2003 WO
WO-03044511 May 2003 WO
WO-03053498 Jul 2003 WO
WO-03057028 Jul 2003 WO
WO-03063700 Aug 2003 WO
WO-03072164 Sep 2003 WO
WO-03072269 Sep 2003 WO
WO-03076893 Sep 2003 WO
WO-03076937 Sep 2003 WO
WO-03082091 Oct 2003 WO
WO-03085372 Oct 2003 WO
WO-03088832 Oct 2003 WO
WO-03094714 Nov 2003 WO
WO-03097866 Nov 2003 WO
WO-03101862 Dec 2003 WO
WO-03106031 Dec 2003 WO
WO-03106966 Dec 2003 WO
WO-2004004905 Jan 2004 WO
WO-2004010844 Feb 2004 WO
WO-03076937 Apr 2004 WO
WO-2004030726 Apr 2004 WO
WO-2004036183 Apr 2004 WO
WO-2004039265 May 2004 WO
WO-2004052190 Jun 2004 WO
WO-2004060455 Jul 2004 WO
WO-2004061420 Jul 2004 WO
WO-2004063718 Jul 2004 WO
WO-2004071291 Aug 2004 WO
WO-2004073138 Aug 2004 WO
WO-2004086970 Oct 2004 WO
WO-2004098685 Nov 2004 WO
WO-2004105641 Dec 2004 WO
WO-2004110256 Dec 2004 WO
WO-2004113901 Dec 2004 WO
WO-2005011489 Feb 2005 WO
WO-2005012873 Feb 2005 WO
WO-2005013824 Feb 2005 WO
WO-2005018443 Mar 2005 WO
WO-2005018450 Mar 2005 WO
WO-2005026178 Mar 2005 WO
WO-2005026689 Mar 2005 WO
WO-2005026690 Mar 2005 WO
WO-2005032362 Apr 2005 WO
WO-2005032400 Apr 2005 WO
WO-2005041766 May 2005 WO
WO-2005048834 Jun 2005 WO
WO-2005051440 Jun 2005 WO
WO-2005057168 Jun 2005 WO
WO-2005057173 Jun 2005 WO
WO-2005057175 Jun 2005 WO
WO-2005063115 Jul 2005 WO
WO-2005065542 Jul 2005 WO
WO-2005067797 Jul 2005 WO
WO-2005070287 Aug 2005 WO
WO-2005074811 Aug 2005 WO
WO-2005078424 Aug 2005 WO
WO-2005084530 Sep 2005 WO
WO-2005084545 Sep 2005 WO
WO-2005084546 Sep 2005 WO
WO-2005089103 Sep 2005 WO
WO-2005026689 Oct 2005 WO
WO-2005094714 Oct 2005 WO
WO-2005098431 Oct 2005 WO
WO-2005107594 Nov 2005 WO
WO-2005114218 Dec 2005 WO
WO-2005119238 Dec 2005 WO
WO-2005121355 Dec 2005 WO
WO-2005121785 Dec 2005 WO
WO-2005122296 Dec 2005 WO
WO-2006001929 Jan 2006 WO
WO-2006001973 Jan 2006 WO
WO-2006002960 Jan 2006 WO
WO-2006005503 Jan 2006 WO
WO-2006010533 Feb 2006 WO
WO-2006015922 Feb 2006 WO
WO-2006017358 Feb 2006 WO
WO-2006018425 Feb 2006 WO
WO-2006019665 Feb 2006 WO
2006026741 Mar 2006 WO
WO-2006021430 Mar 2006 WO
WO-2006024671 Mar 2006 WO
WO-2006029293 Mar 2006 WO
WO-2006040083 Apr 2006 WO
WO-2006023241 May 2006 WO
WO-2006050405 May 2006 WO
WO-2006050843 May 2006 WO
WO-2006060806 Jun 2006 WO
WO-2006071770 Jul 2006 WO
WO-2006072089 Jul 2006 WO
WO-2006076412 Jul 2006 WO
WO-2006079114 Jul 2006 WO
WO-2006088576 Aug 2006 WO
WO 2006099151 Sep 2006 WO
WO 2006099151 Sep 2006 WO
WO-2006094513 Sep 2006 WO
WO-2006098887 Sep 2006 WO
WO-2006099151 Sep 2006 WO
WO-2006102359 Sep 2006 WO
WO-2006102412 Sep 2006 WO
WO-2006104843 Oct 2006 WO
WO-2006105146 Oct 2006 WO
WO-2006108811 Oct 2006 WO
WO-2006118713 Nov 2006 WO
WO-2006118947 Nov 2006 WO
WO-2006122048 Nov 2006 WO
WO-2006122553 Nov 2006 WO
WO-2006124759 Nov 2006 WO
WO-2006130268 Dec 2006 WO
WO-2006131288 Dec 2006 WO
WO-2006132884 Dec 2006 WO
WO-2006133171 Dec 2006 WO
WO-2007002209 Jan 2007 WO
WO-2007002579 Jan 2007 WO
WO-2007005170 Jan 2007 WO
WO-2007006454 Jan 2007 WO
WO-2007009911 Jan 2007 WO
WO-2007011587 Jan 2007 WO
WO-2007016399 Feb 2007 WO
WO-2007021892 Feb 2007 WO
WO-2007021894 Feb 2007 WO
WO-2007025088 Mar 2007 WO
WO-2007027788 Mar 2007 WO
WO-2007028138 Mar 2007 WO
WO-2007028271 Mar 2007 WO
WO-2007033010 Mar 2007 WO
WO-2007037970 Apr 2007 WO
WO-2007037989 Apr 2007 WO
WO-2007040559 Apr 2007 WO
WO-2007041069 Apr 2007 WO
WO-2007041070 Apr 2007 WO
WO-2007041072 Apr 2007 WO
WO-2007041248 Apr 2007 WO
WO-2007053832 May 2007 WO
WO-2007056638 May 2007 WO
WO-2007058921 May 2007 WO
WO-2007059476 May 2007 WO
WO-2007059478 May 2007 WO
WO-2007061992 May 2007 WO
WO-2007065285 Jun 2007 WO
WO-2007070486 Jun 2007 WO
WO-2007076303 Jul 2007 WO
WO-2007079015 Jul 2007 WO
WO-2007079025 Jul 2007 WO
WO-2007081811 Jul 2007 WO
WO-2007090037 Aug 2007 WO
WO-2007097754 Aug 2007 WO
WO-2007101223 Sep 2007 WO
WO-2007101260 Sep 2007 WO
WO-2007109372 Sep 2007 WO
WO-2007111885 Oct 2007 WO
WO-2007112006 Oct 2007 WO
WO-2007114943 Oct 2007 WO
WO-2007115094 Oct 2007 WO
WO-2007120363 Oct 2007 WO
WO-2007120552 Oct 2007 WO
WO-2007126444 Nov 2007 WO
WO-2007127606 Nov 2007 WO
WO-2007127622 Nov 2007 WO
WO-2007127879 Nov 2007 WO
WO-2007127880 Nov 2007 WO
WO-2007130239 Nov 2007 WO
WO-2007137286 Nov 2007 WO
WO-2007053832 Dec 2007 WO
WO-2007143225 Dec 2007 WO
WO-2008001091 Jan 2008 WO
WO-2008003003 Jan 2008 WO
WO-2008005780 Jan 2008 WO
WO-2008013849 Jan 2008 WO
WO-2008016486 Feb 2008 WO
WO-2008021913 Feb 2008 WO
WO-2008022021 Feb 2008 WO
WO-2008028644 Mar 2008 WO
WO-2008031106 Mar 2008 WO
WO-2008031110 Mar 2008 WO
WO-2008037485 Apr 2008 WO
WO-2008039944 Apr 2008 WO
WO-2008039946 Apr 2008 WO
WO-2008039949 Apr 2008 WO
WO-2008042760 Apr 2008 WO
WO-2008048709 Apr 2008 WO
WO-2008051407 May 2008 WO
WO-2008051924 May 2008 WO
WO-2008052199 May 2008 WO
WO-2008055037 May 2008 WO
WO-2008055128 May 2008 WO
WO-2008055199 May 2008 WO
WO-2008067314 Jun 2008 WO
WO-2008069931 Jun 2008 WO
WO-2008069932 Jun 2008 WO
WO-2008073813 Jun 2008 WO
WO-2008076868 Jun 2008 WO
WO-2008079616 Jul 2008 WO
WO-2008080591 Jul 2008 WO
WO2008083379 Jul 2008 WO
WO2008088490 Jul 2008 WO
WO-2008094249 Aug 2008 WO
WO-2008101211 Aug 2008 WO
WO-2008101217 Aug 2008 WO
WO-2008103620 Aug 2008 WO
WO-2007079015 Oct 2008 WO
WO-2008116329 Oct 2008 WO
WO-2008118257 Oct 2008 WO
WO-2008119470 Oct 2008 WO
WO-2008124597 Oct 2008 WO
WO-2008134441 Nov 2008 WO
WO-2008135453 Nov 2008 WO
WO-2008137405 Nov 2008 WO
WO-2008138006 Nov 2008 WO
WO-2008150280 Dec 2008 WO
WO-2008150917 Dec 2008 WO
WO-2008150946 Dec 2008 WO
WO-2008150949 Dec 2008 WO
WO-2009006139 Jan 2009 WO
WO-2009105709 Aug 2009 WO
WO-2009116906 Sep 2009 WO
Non-Patent Literature Citations (618)
Entry
US 7,530,950 B2, 05/2009, Brister et al. (withdrawn)
U.S. Appl. No. 17/088,446 U.S. Pat. No. 10,993,642, filed Nov. 3, 2020, Analyte Sensor.
U.S. Appl. No. 17/161,421 U.S. Pat. No. 11,026,605, filed Jan. 28, 2021, Analyte Sensor.
U.S. Appl. No. 17/341,318, filed Jun. 7, 2021, Analyte Sensor.
U.S. Appl. No. 17/246,481, filed Apr. 30, 2021, Analyte Sensor.
U.S. Appl. No. 17/246,500, filed Apr. 30, 2021, Analyte Sensor.
U.S. Appl. No. 17/453,571, filed Nov. 4, 2021, Analyte Sensor.
U.S. Appl. No. 17/453,576, filed Nov. 4, 2021, Analyte Sensor.
U.S. Appl. No. 11/373,628 U.S. Pat. No. 7,920,906, filed Mar. 9, 2006, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 17/076,714, filed Oct. 21, 2020, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 17/076,716 U.S. Pat. No. 11,000,213, filed Oct. 21, 2020, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 17/316,112, filed May 10, 2021, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 12/683,755 U.S. Pat. No. 8,611,978, filed Jan. 7, 2010, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 13/607,162 U.S. Pat. No. 9,314,196, filed Sep. 7, 2012, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 15/065,623 U.S. Pat. No. 9,918,668, filed Mar. 9, 2016, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 15/787,595, filed Oct. 18, 2017, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 16/457,628 U.S. Pat. No. 10,610,136, filed Jun. 28, 2019, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 16/691,107 U.S. Pat. No. 10,898,114, filed Nov. 21, 2019, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 16/983,885, filed Aug. 3, 2020, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
U.S. Appl. No. 17/076,730, filed Oct. 21, 2020, System and Methods for Processing Analyte Sensor Data for Sensor Calibration.
Aalders, et al., “Development of a Wearable Glucose Sensor; Studies in Healthy Volunteers and in Diabetic Patients,” The International Journal of Artificial Organs, 1991, vol. 14, No. 2, pp. 102-108.
Abe, et al., “Characterization of Glucose Microsensors for Intracellular Measurements,” Analytical Chemistry, 1992, vol. 64, No. 18, pp. 2160-2163.
Abel, et al., “Biosensors for in Vivo Glucose Measurements: Can We Cross the Experimental Stage,” Biosensors & Bioelectronics, 2002, vol. 17, pp. 1059-1070.
Abel, et al., “Experience With an Implantable Glucose Sensor as a Prerequisite of an Artificial Beta Cell,” Biomed. Biochim. Actan, 1984, vol. 43, No. 5, pp. 577-584.
Abo-Zahhad M., et al., “A Wireless Emergency Telemedicine System for Patients Monitoring and Diagnosis,” International Journal of Telemedicine and Applications, 2014, Article ID 380787, 11 pages.
Adilman, et al., “Videogames: Knowing the Score, Creative Computing,” Dec. 1983, Dialog: File 148; IAC Trade & Industry Database, vol. 9, p. 224(5) (9 pages).
Aim, “Radio Frequency Identification RFID,” The Association of the Automatic Identification and Data Capture Industry, Aug. 23, 2001, White Paper WP-98/002R2, 17 pages.
Alberts B., et al., “Molecular Biology of the Cell,” 3rd edition, 1994, p. G19 (3 pages).
Alcock S.J., et al., “Continuous Analyte Monitoring to Aid Clinical Practice,” IEEE Engineering in Medicine & Biology, 1994, vol. 13, pp. 319-325.
Amato, et al., “Experience with the Polytetrafluoroethylene Surgical Membrane for Pericardial Closure in Operations for Congenital Cardiac Defects,” Journal of Thoracic and Cardiovascular Surgery, 1989, vol. 97, pp. 929-934.
Amer M.M.B., “An Accurate Amperometric Glucose Sensor Based Glucometer with Eliminated Cross-Sensitivity,” Journal of Medical Engineering & Technology, vol. 26 (5), Sep./Oct. 2002, pp. 208-213.
Amin R., et al., “Hypoglycemia Prevalence in Prepubertal Children With Type 1 Diabetes on Standard Insulin Regimen: Use of Continuous Glucose Monitoring System,” Diabetes Care, 2003, vol. 26, No. 3, pp. 662-667.
Armour J.C., et al., “Application of Chronic Intravascular Blood Glucose Sensor in Dogs,” Diabetes, Dec. 1990, vol. 39, pp. 1519-1526.
Asberg P., et al., “Hydrogels of a Conducting Conjugated Polymer as 3-D Enzyme Electrode,” Biosensors Bioelectronics, 2003, vol. 19, pp. 199-207.
Assolant-Vinet C.H., et al., “New Immobilized Enzyme Membranes for Tailor-Made Biosensors,” Analytical Letters, 1986, vol. 19(7&8), pp. 875-885.
ASTM International, Inc., “ASTM, Designation: D2240-05, Standard Test Method for Rubber Property-Durometer Hardness,” 2005, 13 pages.
Atanasov P., et al., “Biosensor for Continuous Glucose Monitoring,” Biotechnology and Bioengineering, John Wiley & sons Inc, 1994, vol. 43, pp. 262-266.
Atanasov P., et al., “Implantation of a Refillable Glucose Monitoring-Telemetry Device,” Biosensors and Bioelectronics, vol. 12 (7), 1997, pp. 669-680.
Aussedat B., et al., “A User-Friendly Method for Calibrating a Subcutaneous Glucose Sensor-Based Hypoglycaemic Alarm,” Elsevier Science Limited, Biosensors & Bioelectronic, 1997, vol. 12, No. 11, pp. 1061-1071.
Bailey T.S., et al., “Reduction in Hemoglobin A1C with Real-Time Continuous Glucose Monitoring: Results from a 12-Week Observational Study,” Diabetes Technology & Therapeutics, vol. 9 (3), 2007, pp. 203-210.
Baker D.A., et al., “Dynamic Concentration Challenges for Biosensor Characterization,” Biosensors & Bioelectronics, vol. 8, 1993, pp. 433-441.
Baker D.A., et al., “Dynamic Delay and Maximal Dynamic Error in Continuous Biosensors,” Analytical Chemistry, vol. 68 (8), Apr. 15, 1996, pp. 1292-1297.
Bard A.J., et al., “Electrochemical Methods,” Fundamentals and Applications, John Wiley & Sons, New York, 1980, pp. 173-175.
Bardeletti G., et al., “A Reliable L-Lactate Electrode with a New Membrane for Enzyme Immobilization for Amperometric Assay of Lactate,” Analytica Chemica Acta, vol. 187, 1986, pp. 47-54.
Beach R.D., et al., “Subminiature Implantable Potentiostat and Modified Commercial Telemetry Device for Remote Glucose Monitoring,” IEEE Transactions on Instrumentation and Measurement, vol. 48 (6), Dec. 1999, pp. 1239-1245.
Bellucci F., et al., “Electrochemical Behaviour of Graphite-Epoxy Composite Materials (GECM) in Aqueous Salt Solutions,” Journal of Applied Electrochemistry, vol. 16 (1), Jan. 1986, pp. 15-22.
Bennion N., et al., “Alternate Site Glucose Testing: a Crossover Design,” Diabetes Technology & Therapeutics, vol. 4 (1), 2002, pp. 25-33.
Bergveld, et al., “Fabrication and Mass Production,” Advances in Biosensors, Supplement 1, Chapter 6, 1993, pp. 165-186.
Bertrand C., et al., “Multipurpose Electrode with Different Enzyme Systems Bound to Collagen Films,” Analytica Chemica Acta, 1981, vol. 126, pp. 23-34.
Bessman S.P., et al., “Progress toward a Glucose Sensor for the Artificial Pancreas,” Proceedings of a Workshop on Ion-Selective Microelectrodes, Jun. 4-5, 1973, Boston University, 1973, pp. 189-197.
Biermann E., et al., “How Would Patients Behave if they were Continually Informed of their Blood Glucose Levels? A Simulation Study Using a “Virtual” Patient,” Diabetes Technology & Therapeutics, vol. 10 (3), 2008, pp. 178-187.
Bindra D.S., et al., “Design and in Vitro Studies of a Needle-Type Glucose Sensor for Subcutaneous Monitoring,” Analytical Chemistry, vol. 63, Sep. 1, 1991, pp. 1692-1696.
Bindra D.S., et al., “Pulsed Amperometric Detection of Glucose in Biological Fluids at a Surface-Modified Gold Electrode,” Analytical Chemistry, vol. 61 (22), Nov. 15, 1989, pp. 2566-2570.
Bisenberger M., et al., “A Tripie-Step Potential Waveform at Enzyme Muitisensors with Thick-Film Gold Electrodes for Detection of Glucose and Sucrose,” Sensors and Actuators B, vol. 28, 1995, pp. 181-189.
Bland J.M., et al., “A Note on the Use of the Infraclass Correlation Coefficient in the Evaluation of Agreement between Two Methods of Measurement,” Computers in Biology and Medicine, vol. 20 (5), 1990, pp. 337-340.
Bland J.M., et al., “Statistical Methods for Assessing Agreement Between Two Methods of Clinical Measurement,” The Lancet, Feb. 8, 1986, pp. 307-310.
Blank T.B., et al., “Clinical Results From a Non-Invasive Blood Glucose Monitor,” Optical Diagnostics and Sensing of Biological Fluids and Glucose and Cholesterol Monitoring II, Proceedings of SPIE, vol. 4624, 2002, pp. 1-10.
Bobbioni-Harsch E., et al., “Lifespan of Subcutaneous Glucose Sensors and their Performances during Dynamic Glycaemia Changes in Rats,” J. Biomed. Eng., vol. 15, 1993, pp. 457-463.
Bode B.W., “Clinical Utility of the Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S35-S41.
Bode B.W., et al., “Continuous Glucose Monitoring Used to Adjust Diabetes Therapy Improves Glycosylated Hemoglobin: A Pilot Study,” Diabetes Research and Clinical Practice, vol. 46, 1999, pp. 183-190.
Bode B.W., et al., “Using the Continuous Glucose Monitoring System to Improve the Management of Type 1 Diabetes,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S43-S48.
Boedeker Plastics Inc, “Polyethylene Specifications,” Polyethylene Data Sheet, Retrieved from http://www.boedeker.com/polye.sub.--p.htm on Aug. 19, 2009, 4 pages.
Boland E., et al., “Limitations of Conventional Methods of Self-Monitoring of Blood Glucose,” Diabetes Care, vol. 24 (11), Nov. 2001, pp. 1858-1862.
Bolinder J., et al., “Self-Monitoring of Blood Glucose in Type I Diabetic Patients: Comparison with Continuous Microdialysis Measurements of Glucose in Subcutaneous Adipose Tissue during Ordinary Life Conditions,” Diabetes Care, vol. 20 (1), Jan. 1997, pp. 64-70.
Bolinder J., et al., “Microdialysis Measurement of the Absolute Glucose Concentration in Subcutaneous Adipose Tissue Allowing Glucose Monitoring In Diabetic Patients,” Rapid Communication, Diabetologia, vol. 35, 1992, pp. 1177-1180.
Bott A.W., “A Comparison of Cyclic Voltammetry and Cyclic Staircase Voltammetry,” Current Separations, vol. 16 (1), 1997, pp. 23-26.
Bott A.W., “Electrochemical Methods for the Determination of Glucose,” Current Separations, vol. 17 (1), 1998, pp. 25-31.
Bowman L., et al., “The Packaging of Implantable Integrated Sensors,” IEEE Transactions in Biomedical Engineering, vol. BME-33 (2), Feb. 1986, pp. 248-255.
Brauker, et al., “Sustained Expression of High Levels of Human Factor IX from Human Cells Implanted within an Immunoisolation Device into Athymic Rodents,” Human Gene Therapy, Apr. 10, 1998, vol. 9, pp. 879-888.
Brauker J., et al., “Local Inflammatory Response Around Diffusion Chambers Containing Xenografts,” Transplantation, vol. 61 (12), Jun. 27, 1996, pp. 1671-1677.
Brauker J H., et al., “Neovascularization of Synthetic Membranes Directed by Membrane Microarchitecture,” Journal of Biomedical Material Research, 1995, vol. 29, pp. 1517-1524.
Brauker J., “Unraveling Mysteries at the Biointerface: Molecular Mediator of Inhibition of Blood Vessel Formation in the Foreign Body Capsule Revealed,” SurFACTS in Biomateriais, vol. 6(3), 2001, pp. 1,5.
Braunwald E., “Biomarkers in Heart Failure,” Medical Progress, The New England Journal of Medicine, vol. 358, May 15, 2008, pp. 2148-2159.
Bremer T., et al., “Is Blood Glucose Predictable from Previous Values? A Solicitation for Data,” Perspectives in Diabetes, vol. 48, Mar. 1999, pp. 445-451.
Bremer T.M., et al., “Benchmark Data from the Literature for Evaluation of New Glucose Sensing Technologies,” Diabetes Technology & Therapeutics, vol. 3 (3), 2001, pp. 409-418.
Brooks S.L., et al., “Development of an On-line Glucose Sensor for Fermentation Monitoring,” Biosensors, vol. 3, 1987/1988, pp. 45-56.
Bruckel J., et al., “in Vivo Measurement of Subcutaneous Glucose Concentrations with an Enzymatic Glucose Sensor and a Wick Method,” Klin Wochenschr, vol. 67, 1989, pp. 491-495.
Brunner G.A., et al., “Validation of Home Blood Glucose Meters with Respect to Clinical and Analytical Approaches,” Diabetes Care, vol. 21, No. 4, Apr. 1998, pp. 585-590.
Brunstein E., et al., “Preparation and Validation of Implantable Electrodes for the Measurement of Oxygen and Glucose,” Biomed Biochim. Acta, vol. 48 (11/12), 1989, pp. 911-917.
Cai Q., et al., “A Wireless, Remote Query Glucose Biosensor Based on a pH-Sensitive Polymer,” Analytical Chemistry, vol. 76 (14), Jul. 15, 2004, pp. 4038-4043.
Cameron T., et al., “Micromodular Implants to Provide Electrical Stimulation of Paralyzed Muscles and Limbs,” IEEE Transactions on Biomedical Engineering, vol. 44 (9), Sep. 1997, pp. 781-790.
Campanella L., et al., “Biosensor for Direct Determination of Glucose and Lactate in Undiluted Biological Fluids,” Biosensors & Bioelectronics, vol. 8, 1993, pp. 307-314.
Candas B., et al., “An Adaptive Plasma Glucose Controller Based on a Nonlinear Insulin/Glucose Model,” IEEE Transactions on Biomedical Engineering, vol. 41 (2), Feb. 1994, pp. 116-124.
Cass A.E.G., et al., “Ferrocene-Mediated Enzyme Electrodes for Amperometric Determination of Glucose,” Analytical Chemistry, vol. 56 (4), Apr. 1984, pp. 667-671.
Cassidy J.F., et al., “Novel Electrochemical Device for the Detection of Cholesterol or Glucose,” Analyst, vol. 118, Apr. 1993, pp. 415-418.
Chase H.P., et al., “Continuous Subcutaneous Glucose Monitoring in Children with Type 1 Diabetes,” Pediatrics, vol. 107 (2), Feb. 2001, pp. 222-226.
Chatterjee G., et al., “Poly(ether urethane) and Poly(ether urethane urea) Membranes with High H2S/CH4 Selectivity,” Journal of Membrane Science, vol. 135, 1997, pp. 99-106.
Chen C., et al., “A Noninterference Polypyrrole Glucose Biosensor,” Biosensors and Bioelectronics, vol. 22, 2006, pp. 639-643.
Chen T., et al., “Defining the Period of Recovery of the Glucose Concentration after its Local Perturbation by the Implantation of a Miniature Sensor,” Clinical Chemistry and Laboratory Medicine, vol. 40 (8), 2002, pp. 786-789.
Chia C.W., et al., “Glucose Sensors: Toward Closed Loop Insulin Delivery,” Endocrinology and Metabolism Clinics of North America, vol. 33, 2004, pp. 175-195.
Choleau C., et al., “Calibration of a Subcutaneous Amperometric Glucose Sensor Implanted for 7 Days in Diabetic Patients Part 2. Superiority of the One-point Calibration Method,” Biosensors and Bioelectronics, vol. 17 (8), 2002, pp. 647-654.
Choleau C., et al., “Calibration of a Subcutaneous Amperometric Glucose Sensor Part 1. Effect of Measurement Uncertainties on the Determination of Sensor Sensitivity and Background Current,” Biosensors and Bioelectronics, vol. 17, 2002, pp. 641-646.
Ciba Specialty Chemicals, “Ciba® IRGACURE® 2959,” Coating Effects Segment, Photoinitiator Product Description, Basel Switzerland, Apr. 2, 1998, 3 pages.
Claremont D.J., et al., “Potentially-Implantable, Ferrocene-Mediated Glucose Sensor,” Journal of Biomedical Engineering, vol. 8, Jul. 1986, pp. 272-274.
Claremont D.J., et al., “Subcutaneous Implantation of a Ferrocene-Mediated Glucose Sensor in Pigs,” Diabetologia, vol. 29, 1986, pp. 817-821.
Clark L.C., et al., “Configurational Cyclic Voltammetry: Increasing the Specificity and Reliability of Implanted Electrodes,” IEEE/Ninth Annual Conference of the Engineering in Medicince and Biology Society, 1987, pp. 0782-0783.
Clark L.C., et al., “Long-Term Stability of Electroenzymatic Glucose Sensors Implanted in Mice,” vol. XXXIV, Transactions—American Society for Artificial Internal Organs, 1988, vol. 34, pp. 259-265.
Clark L.C., et al., “One-Minute Electrochemical Enzymic Assay for Cholesterol in Biological Materials,” Clinical Chemistry, vol. 27 (12), 1981, pp. 1978-1982.
Clarke W.L., et al., “Evaluating Clinical Accuracy of Systems for Self Monitoring of Blood Glucose,” Technical Articles, Diabetes Care, vol. 10 (5), Sep.-Oct. 1987, pp. 622-628.
Clarke W.L., et al., “Evaluating the Clinical Accuracy of Two Continuous Glucose Sensors Using Continuous Glucose-Error Grid Analysis,” Emerging Treatment and Technologies, Diabetes Care, vol. 28(10), Oct. 2005, pp. 2412-2417.
Colangelo V.J., et al., “Corrosion Rate Measurements in Vivo,” Journal of Biomedical Materials Research, vol. 1, 1967, pp. 405-414.
Colowick S.P., et al., “Methods in Enzymology,” vol. XLIV, Immobilized Enzymes, Edited by Mosbach K, New York Academic Press, 1976, 11 pages.
Copeland J.G., et al., “Synthetic Membrane Neo-Pericardium Facilitates Total Artificial Heart Explanation,” The Journal of Heart Lung Transplantation, vol. 20(6), Jun. 2001, pp. 654-656.
Coulet P.R., et al., “Enzymes Immobilized on Collagen Membranes: A Tool for Fundamental Research and Enzyme Engineering,” Journal of Chromatography, vol. 215, 1981, pp. 65-72.
Coulet P.R., “Polymeric Membranes and Coupled Enzymes in the Design of Biosensors,” Journal of Membrane Science, 1992, vol. 68, pp. 217-228.
Cox D.J., et al., “Accuracy of Perceiving Blood Glucose in IDDM,” Diabetes Care, vol. 8 (6), Nov.-Dec. 1985, pp. 529-536.
Csoregi E., et al., “Amperometric Microbiosensors for Detection of Hydrogen Peroxide and Glucose Based on Peroxidase-Modified Carbon Fibers,” Electroanalysis, vol. 6, 1994, pp. 925-933.
Csoregi E., et al., “Design and Optimization of a Selective Subcutaneously Implantable Glucose Electrode Based on ‘Wired’ Glucose Oxidase,” Analytical Chemistry, vol. 67 (7). Apr. 1, 1995, pp. 1240-1244.
Csoregi E., et al., “Design, Characterization and One-Point in Vivo Calibration of a Subcutaneously Implanted Glucose Electrode,” American Chemical Society, Analytical Chemistry, vol. 66 (19), Oct. 1, 1994, pp. 3131-3138.
Currie J.F., et al., “Novel Non-Intrusive Trans-Dermal Remote Wireless Micro-Fluidic Monitoring System Applied to Continuous Glucose and Lactate Assays for Casualty Care and Combat Readiness Assessment,” RTO HFM Symposium, RTO-MP-HFM-109, Aug. 16-18, 2004, pp. ‘24-1’-‘24-18’.
Dai W.S., et al., “Hydrogel Membranes with Mesh Size Asymmetry based on the Gradient Crosslinking of Poly(Vinyl Alcohol),” Journal of Membrane Science, 1999, vol. 156, pp. 67-79.
Danielsson B., et al., “Enzyme Thermistors,” Methods in Enzymology, vol. 137, 1988, pp. 181-197.
D'Arrigo G., et al., “Porous-Si Based Bio Reactors for Glucose Monitoring and Drugs Production,” Proceedings of SPIE, 2003, vol. 4982, pp. 178-184.
Dassau E., et al., “In Silico Evaluation Platform for Artificial Pancreatic β-Cell Development—A Dynamic Simulator for Closed-Loop Control with Hardware-in-the-loop,” Diabetes Technology & Therapeutics, vol. 11 (3), 2009, pp. 1-8.
Dassau E., et al., “Real-Time Hypoglycemia Prediction Suite Using Continuous Glucose Monitoring,” Emerging Treatment and Technologies, Diabetes Care, vol. 33 (6), Jun. 2010, pp. 1249-1254.
Davies M.L., et al., “Polymer Membranes in Clinical Sensor Applications,” An overview of membrane function, Biomateriais, vol. 13 (14), 1992, pp. 971-978.
Davis G., et al., “Bioelectrochemical Fuel Cell and Sensor Based ona Quinoprotein, Alcohol Dehydrogenase,” Enzyme and Microbial Technology, vol. 5 (5), Sep. 1983, pp. 383-388.
Definition of plunger: https://www.merriam-webster.com/dictionary/plunger, dated Nov. 7, 2016, 2 pages.
Deutsch T., et al., “Time Series Analysis and Control of Blood Glucose Levels in Diabetic Patients,” Computer Methods and Programs in Biomedicine, Elsevier Scientific Publishers, vol. 41, 1994, pp. 167-182.
Dixon B.M., et al., “Characterization in Vitro and in Vivo of the Oxygen Dependence of an Enzyme/Polymer Biosensor for Monitoring Brain Glucose,” Journal of Neuroscience Methods, vol. 119, 2002, pp. 135-142.
Dobson D.E., et al.,“1-Butyrul-Glycerol: A Novel Angiogenesis Factor Secreted by Differentiating Adipocytes,” Cell, Apr. 20, 1990, vol. 61 (2), pp. 223-230.
Dowla F., et al., “Handbook of RF and Wirelesstechnologies,” Elsevier, Inc. All rights reserved, 2004, 44 pages.
DuPont, “Dimension® AR Clinical Chemistry System,” The Chemistry Analyzer that Makes the most of your Time, Money and Effort, Dade International, Chemistry Systems, Newark, 1998, 18 pages.
Durliat H., et al., “Spectrophotometric and Electrochemical Determinations of L( +)-Lactate in Blood by Use of Lactate Dehydrogenase from Yeast,” Clinical Chemistry, vol. 22 (11), 1976, pp. 1802-1805.
Edwards Lifesciences, “Accuracy for You and Your Patients,” Marketing materials, 2002, 4 pages.
El Degheidy M.M., et al., “Optimization of an Implantable Coated Wire Glucose Sensor,” Journal of Biomedical Engineering, vol. 8, Apr. 1986, pp. 121-129.
Elco Diagnostics Company, “Direct 30/30® Blood Glucose Sensor,” Markwell Medical Catalog, 1990, 1 page.
El-Khatib F.H., et al., “Adaptive Closed-Loop Control Blood-Glucose Regulation Using Dual Subcutaneous Insulin and Glucagon Infusion in Diabetic Swine,” Journal of Diabetes Science and Technology, Diabetes Technology Society, vol. 1 (2), 2007, pp. 181-192.
El-Sa'Ad L., et al., “Moisture Absorption by Epoxy Resins: The Reverse Thermal Effect,” Journal of Materials Science, vol. 25, 1990, pp. 3577-3582.
English D., et al., “Platelet-Released Phospholipids Link Haemostasis and Angiogenesis,” Cardiovascular Research, 2001, vol. 49, pp. 588-599.
Ernst H., et al., “Reliable Glucose Monitoring Through the Use of Microsystem Technology,” Analytical Bioanalytical Chemistry, vol. 373, 2002, pp. 758-761.
Fabietti P.G., et al., “Clinical Validation of a New Control-Oriented Model of Insulin and Glucose Dynamics in Subjects with Type 1 Diabetes,” Diabetes Technology & Therapeutics, vol. 9 (4), 2007, pp. 327-338.
Fahy B.G., et al., “An Analysis: Hyperglycemic Intensive Care Patients Need Continuous Glucose Monitoring—Easier Said Than Done,” Journal of Diabetes Science and Technology, Diabetes Technology Society, vol. 2 (2), Mar. 2008, pp. 201-204.
Fare T.L., et al., “Functional Characterization of a Conducting Polymer-Based Immunoassay System,” Biosensors & Bioelectronics, vol. 13 (3-4), 1998, pp. 459-470.
Farlex, Inc., “Statistical Distribution—Definition of Statistical Distribution by the Free Dictionary—Thesaurus,” 2003-2016, 2 pages.
Farlex, Inc, Definition of term “elastomeric”, Free Dictionary, Copyright 2008, retrieved from http://www.thefreedictionary.com/elastomeric, 3 pages.
Feldman B., et al., “A Continuous Glucose Sensor Based on Wired EnzymeTM Technology-Results from a 3-Day Trial in Patients with Type 1 Diabetes,” Diabetes Technology & Therapeutics, vol. 5 (5), 2003, pp. 769-779.
Feldman B., et al., “Correlation of Glucose Concentrations in Interstitial Fluid and Venous Blood During Periods of Rapid Glucose Change,” Abbott Diabetes Care, Inc. Freestyle Navigator Continuous Glucose Monitor Pamphlet, 2004, 1 page.
Finkenzeller K., “Rfid Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification,” John Wiley & Sons, Ltd, 2003, ISBN: 0-470-84402-7, 114 pages.
Fischer U., et al., “Assessment of Subcutaneous Glucose Concentration: Validation of the Wick Technique as a Reference for Implanted Electrochemical Sensors in Normal and Diabetic Dogs,” Diabetologia, vol. 30, 1987, pp. 940-945.
Fischer U., et al., “Hypoglycaemia-Warning by Means of Subcutaneous Electrochemical Glucose Sensors: An Animal Study,” Horm. Metab. Res, vol. 27, 1995, p. 53. (Abstract Only).
Fischer U., et al., “Oxygen Tension at the Subcutaneous Implantation Site of Glucose Sensors,” Biomed. Biochim. Acta, vol. 48 (11/12), 1989, pp. 965-971.
Freedman D., et al., “Statistics,” Second Edition, W.W. Norton & Company, New York & London, 1991, p. 74 (3 pages).
Freiberger P., “Video Game Takes on Diabetes Superhero ‘Captain Novolin’ Offers Treatment Tips,” Fourth Edition, Jun. 26, 1992, Business Section, 2 pages.
Frohnauer M.K., et al., “Graphical Human Insulin Time-Activity Profiles Using Standardized Definitions,” Diabetes Technology & Therapeutics, vol. 3 (3), 2001, pp. 419-429.
Frost M.C., et al., “Implantable Chemical Sensors for Real-Time Clinical Monitoring: Progress and Challenges,” Current Opinion in Chemical Biology, Analytical Techniques, vol. 6, 2002, pp. 633-641.
Gabby R.A., et al., “Optical Coherence Tomography-Based Continuous Noninvasive Glucose Monitoring in Patients with Diabetes,” Diabetes Technology & Therapeutics, vol. 10, Nov. 3, 2008, pp. 188-193.
Ganesan N., et al., “Gold Layer-Based Dual Crosslinking Procedure of Glucose Oxidase with Ferrocne Monocarboxylic Acid Provides a Stable Biosensor,” Analytical Biochemistry, Notes & Tips, vol. 343, 2005, pp. 188-191.
Ganesh A., et al., “Evaluation of the VIA® Blood Chemistry Monitor for Glucose in Healthy and Diabetic Volunteers,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 182-193.
Gao S., et al., “Determination of Interfacial Parameters of Cellulose Acetate Membrane Materials by HPLC,” Journal of Liquid Chromatography, 1989, vol. 12(11), pp. 2083-2092.
Garg S.K., et al., “Correlation of Fingerstick Blood Glucose Measurements With GlucoWatch Biographer Glucose Results in Young Subjects With Type 1 Diabetes,” Emerging Treatments and Technologies, Diabetes Care, vol. 22 (10), Oct. 1999, pp. 1708-1714.
Garg S.K., et al., “Improved Glucose Excursions Using an Implantable Real-Time Continuous Glucose Sensor in Adults With Type 1 Diabetes,” Emerging Treatments and Technologies, Diabetes Care, vol. 27 (3), 2004, pp. 734-738.
Geller R.I., et al., “Use of an Immunoisolation Device for Cell Transplantation and Tumor Immunotherapy,” Annals of the New York Academy of Science, 1997, vol. 831, pp. 438-451.
Gerritsen M., et al., “Influence of Inflammatory Cells and Serum on the Performance of Implantable Glucose Sensors,” Journal of Biomedical Material Research, 2001, vol. 54, pp. 69-75.
Gerritsen M., et al., “Performance of Subcutaneously Implanted Glucose Sensors for Continuous Monitoring,” The Netherlands Journal of Medicine, vol. 54, 1999, pp. 167-179.
Gerritsen M., et al., “Problems Associated with Subcutaneously Implanted Glucose Sensors,” Diabetes Care, vol. 23 (2), Feb. 2000, pp. 143-145.
Gilligan B.J., et al., “Evaluation of a Subcutaneous Glucose Sensor Out to 3 Months in a Dog Model” Diabetes Care, vol. 17 (8), Aug. 1994, pp. 882-887.
Gilligan B.J., et al., “Feasibility of Continuous Long-Term Glucose Monitoring from a Subcutaneous Glucose Sensor in Humans,” Diabetes Technology & Therapeutics, vol. 6 (3), 2004, pp. 378-386.
Godsland I.F., et al., “Maximizing the Success Rate of Minimal Model Insulin Sensitivity Measurement in Humans: The Importance of Basal Glucose Levels,” The Biochemical Society and the Medical Research Society, Clinical Science, vol. 101, 2001, pp. 1-9.
Gore Preclude®, Pericardial Membrane Brochure, Jun. 2009. W.L. Gore & Associates Inc., Flagstaff, AZ 86004.
Gore Preclude®, Pericardial Membrane Brochure, Nov. 2001, W.L. Gore & Associates Inc., Flagstaff, AZ—86004, 4 pages.
Gouda M.D., et al., “Thermal Inactivation of Glucose Oxidase,” The Journal of Biological Chemistry, vol. 278 (27), Issue of Jul. 4, 2003, pp. 24324-24333.
Gough D.A., et al., “Frequency Characterization of Blood Glucose Dynamics,” Annals of Biomedical Engineering, vol. 31, 2003, pp. 91-97.
Gough D.A., et al., “Immobilized Glucose Oxidase in Implantable Glucose Sensor Technology,” Diabetes Technology & Therapeutics, vol. 2 (3), 2000, pp. 377-380.
Gough D.A., “The implantable Glucose Sensor: An Example of Bioengineering Design,” Introduction to Bioengineering, 2001, Chapter 3, pp. 57-66.
Gregg B A., et al., “Cross-Linked Redox Gels Containing Glucose Oxidase for Amperometric Biosensor Applications,” Anal Chem, 1990, vol. 62, pp. 258-263.
Gross, et al., “Diabetes Technology & Therapeutics,” Letters to the Editor, Diabetes Technology & Therapeutics, vol. 3 (1), 2001, pp. 129-131.
Gross T.M., et al., “Efficacy and Reliability of the Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S19-S26.
Gross T.M., et al., “Performance Evaluation of the Minimed® Continuous Glucose Monitoring System During Patient Home Use,” Diabetes Technology & Therapeutics, vol. 2(1), 2000, pp. 49-56.
Guerci B., et al., “Clinical Performance of CGMS in Type 1 Diabetic Patients Treated by Continuous Subcutaneous Insulin Infusion Using Insulin Analogs,” Diabetes Care, vol. 26, 2003, pp. 582-589.
Guerra S., et al., “Enhancing the Accuracy of Subcutaneous Glucose Sensors: A Real-Time Deconvolution-Based Approach,” IEEE Transactions on Biomedical Engineering, vol. 59(6), Jun. 2012, pp. 1658-1669.
Guo M., et al., “Modification of Cellulose Acetate Ultrafiltration Membrane by Gamma Ray Radiation,” Shuichuli Jishi Bianji Weiyuanhui, 1998, vol. 23(6), pp. 315-318. (Abstract only).
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part 1. An Adsorption-controlled Mechanism,” Electrochimica Acta, vol. 43, Nos. 5/6, 1998, pp. 579-588.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part II: Effect of potential,” Electrochimica Acta, vol. 43 (14-15), 1998, pp. 2015-2024.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part III: Effect of Temperature,” Electrochimica Acta, vol. 44, 1999, pp. 2455-2462.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part IV: Phosphate Buffer Dependence,” Electrochimica Acta, vol. 44, 1999, pp. 4573-4582.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part V: Inhibition by Chloride,” Electrochimica Acta, vol. 45, 2000, pp. 3573-3579.
Halvorsen C., et al., “Vasodilation of Rat Retinal Microvessels Induced by Monobutyrin,” Journal of Clinical Investigation, Dec. 1993, vol. 92, pp. 2872-2876.
Hamilton, “Complete Guide to Selecting the Right Hamilton Gastight, Microliter, and Specialty Syringe for your Application,” Syringe Selection, www.hamiltoncompany.com 2006, 20 pages.
Harada, et al., “Long-Term Results of the Clinical Use of an Expanded Polytetrafluoroethylene Surgical Membrane as a Pericardial Substitute,” Journal of Thoracic and Cardiovascular Surgery, 1988, vol. 96(5), pp. 811-815.
Harrison, et al., “Characterization of Perfluorosulfonic Acid Polymer Coated Enzyme Electrodes and a Miniaturized Integrated Potentiostat for Glucose Analysis in Whole Blood,” Analytical Chemistry, 1988, vol. 60, pp. 2002-2007.
Hashiguchi Y., et al., “Development of a Miniaturized Glucose Monitoring System by Combining a Needle-Type Glucose Sensor with Microdialysis Sampling Method: Long-term subcutaneous tissue glucose monitoring in ambulatory diabetic patients,” Diabetes Care, vol. 17, No. 5, May 1994, pp. 387-396.
Heise T., et al., “Hypoglycemia warning signal and glucose sensors: Requirements and concepts,” Diabetes Technology & Therapeutics, vol. 5, No. 4, 2003, pp. 563-571.
Heller A., “Electrical Connection of Enzyme Redox Centers to Electrodes,” J. Phys. Chem., vol. 96, 1992, pp. 3579-3587.
Heller A., “Electrical Wiring of Redox Enzymes,” Ace. Chem. Res., vol. 23, 1990, pp. 128-134.
Heller A., et al., “Electrochemical Glucose Sensors and Their Applications in Diabetes Management,” Chemical Reviews, 2008, vol. 108, No. 7 pp. 2482-2505.
Heller A., “Implanted Electrochemical Glucose Sensors for the Management of Diabetes,” Annu. Rev., Biomed Eng., vol. 1, 1999, pp. 153-175.
Heller A., “Plugging Metal Connectors into Enzymes,” Nature Biotechnology, vol. 21, No. 6, Jun. 2003, pp. 631-632.
Heller, et al., “In vivo Glucose Monitoring with Miniature “Wired” Glucose Oxidase Electrodes,” Analytical Sciences, 2001, vol. 17 Supplement, pp. i297-i300.
Heydron W H., et al., “A New Look at Pericardial Substitutes”, Journal of Thoracic and Cardiovascular Surgery, 1987, vol. 94(2), pp. 291-296.
Hicks J.M., “In Situ Monitoring,” Clinical Chemistry, vol. 31 (12), 1985, pp. 1931-1935.
Hitchman M.L., “Measurement of Dissolved Oxygen,” Edited by Elving P.J et al., Chemical Analysis, New York, John Wiley & Sons, vol. 49, Chapter 3, 1978, pp. 34-49 and 59-123.
Hoel P.G., “Elementary Statistics,” Fourth Edition, John Wiley & Sons, Inc., 1976, pp. 113-114.
Houghton Mifflin Company, “American Heritage Dictionary,” 4th Edition, 2000, pp. 82.
Houghton Mifflin Company, “Xenogenic, the American Heritage Stedman's Medical Dictionary,” 2002, Answers.Com, retrieved from http://www.answers.com/fopic/xenogenic, on Nov. 7, 2006, 2 Pages.
Hrapovic S., et al., “Picoamperometric Detection of Glucose at Ultrasmall Platinum-Based Biosensors Preparation and Characterization,” Anal. Chem, vol. 75, 2003, pp. 3308-3315.
Hu Y., et al., “A Needle-Type Enzyme-Based Lactate Sensor for In Vivo Monitoring,” Analytics Chimica Acta, vol. 281, 1993, pp. 503-511.
Huang C., et al., “Electrochemical Generation of Oxygen. 1: The Effects of Anions and Cations on Hydrogen Chemisorption and Anodic Oxide Film Formation on Platinum Electrode. 2: The Effects of Anions and Cations on Oxygen Generation on Platinum Electrode,” U.S. Department of Commence/NTIS, 1975, 126 pages.
Huang Q., et al., “A 0.5mW Passive Telemetry IC for Biomedical Applications,” Proceedings of the 23rd European Solid-State Circuits Conference (ESSCIRC '97), Southampton, UK, Sep. 16-18, 1997, pp. 172-175.
Hunter I., et al., “Minimally Invasive Glucose Sensor and Insulin Delivery System,” MIT Home Automation and Healthcare Consortium, Mar. 31, 2000, Progress Report No. 25, 17 pages.
International Preliminary Examination Report for Application No. PCT/US2002/023903 dated Apr. 20, 2005, 5 pages.
International Preliminary Report on Patentability for Application No. PCT/US2004/023455 dated Jan. 23, 2006, 7 pages.
International Preliminary Report on Patentability for Application No. PCT/US2004/040476 dated Dec. 8, 2006, 4 pages.
International Preliminary Report on Patentability for Application No. PCT/US2005/014696 dated Nov. 7, 2006, 6 pages.
International Preliminary Report on Patentability for Application No. PCT/US2005/024993, dated Jan. 16, 2007, 7 pages.
International Preliminary Report on Patentability for Application No. PCT/US2005/024994 dated Jan. 16, 2007, 8 pages.
International Preliminary Report on Patentability for Application No. PCT/US2006/006574 dated Aug. 26, 2008, 10 pages.
International Preliminary Report on Patentability for Application No. PCT/US2006/008616 dated Mar. 3, 2009, 7 pages.
International Preliminary Report on Patentability for Application No. PCT/US2006/024132, dated Dec. 24, 2007, 6 pages.
International Preliminary Report on Patentability for Application No. PCT/US2006/031496 dated Nov. 27, 2008, 8 pages.
International Preliminary Report on Patentability for Application No. PCT/US2007/005422 dated Sep. 1, 2009, 5 pages.
International Preliminary Report on Patentability for Application No. PCT/US2008/058158, dated Sep. 29, 2009, 9 pages.
International Preliminary Report on Patentability for Application No. PCT/US2009/040285, dated Oct. 21, 2010, 8 pages.
International Search Report and Written Opinion for Application No. PCT/US2003/15816 dated Sep. 22, 2003, 4 pages.
International Search Report and Written Opinion for Application No. PCT/US2004/023455 dated Dec. 23, 2004, 8 pages.
International Search Report and Written Opinion for Application No. PCT/US2004/040476 dated Nov. 16, 2006, 4 pages.
International Search Report and Written Opinion for Application No. PCT/US2005/014696 dated Jun. 29, 2006, 8 pages.
International Search Report and Written Opinion for Application No. PCT/US2005/014969 dated Dec. 12, 2005, 8 pages.
International Search Report and Written Opinion for Application No. PCT/US2005/024993, dated Nov. 4, 2005, 12 pages.
International Search Report and Written Opinion for Application No. PCT/US2005/024994 dated Nov. 15, 2005, 11 pages.
International Search Report and Written Opinion for Application No. PCT/US2006/001998 dated Jul. 25, 2006, 5 pages.
International Search Report and Written Opinion for Application No. PCT/US2006/006574 dated Aug. 4, 2006, 13 pages.
International Search Report and Written Opinion for Application No. PCT/US2006/008616 dated Mar. 13, 2008, 9 pages.
International Search Report and Written Opinion for Application No. PCT/US2006/019889 dated Feb. 20, 2007, 6 pages.
International Search Report and Written Opinion for Application No. PCT/US2006/024132, dated Jul. 20, 2007, 6 pages.
International Search Report and Written Opinion for Application No. PCT/US2006/031496 dated Sep. 20, 2007, 9 pages.
International Search Report and Written Opinion for Application No. PCT/US2006/038820 dated Jun. 20, 2007, 7 pages.
International Search Report and Written Opinion for Application No. PCT/US2007/005422 dated May 20, 2008, 5 pages.
International Search Report and Written Opinion for Application No. PCT/US2008/058158, dated Aug. 8, 2008, 10 pages.
International Search Report and Written Opinion for Application No. PCT/US2009/040285, dated May 29, 2009, 8 pages.
International Search Report for Application No. PCT/US2001/023850 dated Jan. 16, 2002, 3 pages.
International Search Report for Application No. PCT/US2002/023903 dated Feb. 27, 2003, 4 pages.
Isermann R., et al., “Trends in the Application of Model-Based Fault Detection and Diagnosis of Technical Processes”, Control Engineering Practice, vol. 5 (5), 1997, pp. 709-719.
Isermann R., “Supervision, Fault-Detection and Fault-Diagnosis Methods—An Introduction,” Control Engineering Practice, vol. 5 (5), 1997, pp. 639-652.
Ishikawa M., et al., “Initial Evaluation of a 290-Mm Diameter Subcutaneous Glucose Sensor: Glucose Monitoring With a Biocompatible, Flexible-Wire, Enzyme-Based Amperometric Microsensor in Diabetic and Nondiabetic Humans,” Journal of Diabetes and Its Complications, vol. 12, 1998, pp. 295-301.
Jablecki M., et al., “Simulations of the Frequency Response of Implantable Glucose Sensors,” Analytical Chemistry, vol. 72, 2000, 1853-1859.
Jaffari S.A., et al., “Recent Advances in Amperometric Glucose Biosensors for In Vivo Monitoring,” Physiological Measurement, 1995, vol. 16, pp. 1-15.
Jaremko J., et ai., “Advances Toward the Implantable Artificial Pancreas for Treatment of Diabetes,” Diabetes Care, vol. 21 (3), Mar. 1998, pp. 444-450.
Jensen M.B., et al., “Fast Wave Forms for Pulsed Electrochemical Detection of Glucose by Incorporation of Reductive Desorption of Oxidation Products, ”Analytical Chemistry, vol. 69 (9), May 1997, pp. 1776-1781.
Jeong R.A., et al., “In Vivo Calibration of the Subcutaneous Amperometric Glucose Sensors Using a Non-Enzyme Electrode,” Biosensors and Bioelectronics, Elsevier, vol. 19, 2003, pp. 313-319.
Jeutter D.C., “A Transcutaneous Implanted Battery Recharging and Biotelemeter Power Switching System,” IEEE Transactions on Biomedical Engineering, vol. BME-29 (5), May 1982, pp. 314-321.
Jeutter D.C., et al., “Design of a Radio-Linked Implantable Cochlear Prosthesis Using Surface Acoustic Wave Devices,” IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 40 (5), Sep. 1993, pp. 469-477.
Jobst G., et al., “Thin-Film Microbiosensors for Glucose-Lactate Monitoring,” Anal Chem, Sep. 15, 1996, vol. 68(18), pp. 3173-3179.
Johnson K.W., et al., “In Vivo Evaluation of an Electroenzymatic Glucose Sensor Implanted in Subcutaneous Tissue,” Biosensors and Bioelectronics, 1992, vol. 7, pp. 709-714.
Johnson K.W., “Reproducible Electrodeposition of Biomolecules for the Fabrication of Miniature Electroenzymatic Biosensors,” Sensore and Actuators B, vol. 5, 1991, pp. 85-89.
Johnson P.C., “Peripheral Circulation,” John Wiley & Sons, 1978, p. 198 (5 pages).
Johnson R.C., et al., “Abstract: Neovascularization of Cell Transplantation Devices: Role of Membrane Architecture and Encapsulated Tissue,” Abstracts of Papers, American Chemical Society, Sep. (7-11), 1997, 214th ACS National Meeting, Part 2, 305-PMSE, 2 pages.
Joung G.B., et al., “An Energy Transmission System for an Artificial Heart Using Leakage Inductance Compensation of Transcutaneous Transformer,” IEEE Transactions on Power Electronics, vol. 13 (6), Nov. 1998, pp. 1013-1022.
Jovanovic L.M.D., “The Role of Continuous Glucose Monitoring in Gestational Diabetes Mellitus,” Diabetes Technology and Therapeutics, vol. 2 (1), 2000, pp. S67-S71.
Jungheim K., et al., “How Rapid Does Glucose Concentration Change in Daily Life of Patients with Type 1 Diabetes?,” Diabetologia, 2002, vol. 45, pp. A250-A276.
Jungheim K., et al., “Risky Delay of Hypoglycemia Detection by Glucose Monitoring at the Arm,” Diabetes Care, vol. 24 (7), Jul. 2001, pp. 1303-1304.
Kacaniklic V., et al., “Amperometric Biosensors for Detection of L- and D-Amino Acids Based on Coimmoblized Peroxidase and L- and D-Amino Acid Oxidases in Carbon Paste Electrodes,” Electroanalysis, vol. 6, May-Jun. 1994, pp. 381-390.
Kamath A., et al., “Analysis of Time Lags and Other Sources of Error of the DexCom SEVEN Continuous Glucose Monitor,” Diabetics Technology and Therapeutic, Nov. 2009, vol. 11, No. 11, pp. 689-695.
Kamath A., et al., “Calibration of a Continuous Glucose Monitor: Effect of Glucose Rate of Change,” Eighth Annual Diabetes Technology Meeting, Nov. 13-15, 2008, pp. A88 (2 pages).
Kang S.K., et al., “In Vitro and Short-Term in Vivo Characteristics of a Kel-F Thin Film Modified Glucose Sensor,” Analytical Sciences, vol. 19, Nov. 2003, pp. 1481-1486.
Kaplan S.M., “Wiley Electrical and Electronics Engineering Dictionary,” IEEE Press, John Wiley & Sons, Inc., 2004, pp. 141, 142, 548 & 549.
Kargol M., et al., “Studies on the Structural Properties of Porous Membranes: Measurement of Linear Dimensions of Solutes,” Biophysical Chemistry, 2001, vol. 91, pp. 263-271.
Karube I., et al., “Microbiosensors for Acetylcholine and Glucose,” Biosensors & Bioelectronics, 1993, vol. 8, pp. 219-228.
Kaufman F.R., et al., “A Pilot Study of the Continuous Glucose Monitoring System,” Diabetes Care, vol. 24 (12), Dec. 2001, pp. 2030-2034.
Kaufman F.R., “Role of the Continuous Glucose Monitoring System in Pediatric Patients,” Diabetes Technology and Therapeutics, vol. 2 (1), 2000, S49-S52.
Kawagoe J.L., et al., “Enzyme-Modified Organic Conducting Salt Microelectrode,” Analytical Chemistry, vol. 63, 1991, pp. 2961-2965.
Keedy F.H., et al., “Determination of Urate in Undiluted Whole Blood by Enzyme Electrode,” Biosensors and Bioelectronics, vol. 6, 1991, pp. 491-499.
Kerner, et al., “A Potentially Implantable Enzyme Electrode for Amperometric Measurement of Glucose,” Hormone and Metabolic Research Supplement, vol. 20, 1988, pp. 8-13.
Kerner W., et al., “The Function of a Hydrogen Peroxide-Detecting Electroenzymatic Glucose Electrode is Markedly Impaired in Human Sub-Cutaneous Tissue and Plasma,” Biosensors and Bioelectronics, vol. 8, 1993, pp. 473-482.
Kerner W., “Implantable Glucose Sensors: Present Status and Future Developments,” Experimental and Clinical Endocrinol Diabetes, vol. 109 (2), 2001, pp. S341-S346.
Kidd K R., et al., “Angiogenesis and Neovascularization Associated with Extracellular Matrix Modified Porous implants,” Journal of Biomedical Materials Research, 2001, vol. 59(2), pp. 366-377.
Kiechle F.L., “The Impact of Continuous Glucose Monitoring on Hospital Point-of-Care Testing Programs,” Diabetes Technology and Therapeutics, vol. 3 (4), 2001, pp. 647-649.
Klonoff D., et al., “Performance Metrics for Continuous Interstitial Glucose Monitoring; Approved Guideline,” Clinical and Laboratory Standards Institute, POCT05-A, vol. 28 (33), 2008, 72 pages.
Klueh U., et al., “Inflammation and Glucose Sensors: Use of Dexamethasone to Extend Glucose Sensor Function and Life Span in Vivo,” Journal of Diabetes Science and Technology, vol. 1 (4), Jul. 2007, pp. 496-504.
Klueh U., et al., “Use of Vascular Endothelial Cell Growth Factor Gene Transfer to Enhance Implantable Sensor Function in Vivo,” Biosensor Function and VEGF-Gene Transfer, vol. 67 (4), 2003, pp. 1072-1086.
Kobunshi Keiki Co., Ltd, “What is durometer?,” retrieved from http://www.asker.co.jp/en/products/durometer/analog/about/index.htmnl on May 9, 2018, 2 pages.
Kondo T., et al., “A Miniature Glucose Sensor, Implantable in the Blood Stream,” Diabetes Care, vol. 5 (3), May-Jun. 1982, 218-221.
Koschinsky T., et al., “Sensors for Glucose Monitoring: Technical and Clinical Aspects,” Diabetes Metabolism Research and Reviews, vol. 17, No. 2, Jan. 1, 2001, pp. 113-123.
Koschinsky T., et al., “New Approach to Technical and Clinical Evaluation of Devices for Self-Monitoring of Blood Glucose,” Diabetes Care, vol. 11 (8), Sep. 1988, pp. 619-629.
Kost J., et al., “Glucose-Sensitive Membranes Containing Glucose Oxidase: Activity, Swelling, and Permeability Studies,” Journal of Biomedical Materials Research, vol. 19, 1985, pp. 1117-1133.
Koudelka M., et al., “In Vivo Response of Microfabricated Glucose Sensors to Glycemia Changes in Normal Rats,” Biomed. Biochim. Acta, vol. 48 (11/12), Nov.-Dec. 1989, pp. 953-956.
Koudelka M., et al., “In-Vivo Behaviour of Hypodemically Implanted Microfabricated Glucose Sensors,” Biosensors and Bioelectronics, vol. 6, 1991, pp. 31-36.
Kovatchev B.P., et al., “Evaluating the Accuracy of Continuous Glucose-Monitoring Sensors: Continuous Glucose-Error Grid Analysis Illustrated by TheraSense Freestyle Navigator Data,” Diabetes Care, vol. 27 (8), Aug. 2004, pp. 1922-1928.
Kraver., et al., “A Mixed-Signal Sensor Interface Microinstrument,” Sensors and Actuators A, Physical 2001, vol. 91, pp. 266-277.
Krouwer J.S., “Setting Performance Goals and Evaluating Total Analytical Error for Diagnostic Assays,” Clinical Chemistry, vol. 48 (6), 2002, pp. 919-927.
Kruger D., et al., “Psychological Motivation and Patient Education: A Role for Continuous Glucose Monitoring,” Diabetes Technology and Therapeutics, vol. 2 (1), 2000, pp. S93-S97.
Kugler J D., et al., “A New Steroid-Eluting Epicardial Lead: Experience with Atrial and Ventricular Implantation in the Immature Swine,” PACE, Aug. 1990, vol. 13, pp. 976-981.
Kulys J., et al., “Carbon-Paste Biosensors Array for Long-Term Glucose Measurement,” Biosensors & Bioelectronics, vol. 9, 1994, pp. 491-500.
Kunjan K., et al., “Automated Blood Sampling and Glucose Sensing in Critical Care Settings,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 194-200.
Kunzler J., et al.,“Hydrogels based on Hydrophilic Side Chain Siloxanes,” Poly Mat Sci and Eng, 1993, vol. 69, pp. 226-227.
Kunzler J F., et al., “Contact Lens Materials,” Chemistry & Industry, Aug. 21, 1995, pp. 651-655.
Kurnik R.T., et al., “Application of the Mixtures of Experts Algorithm for Signal Processing in a Noninvasive Glucose Monitoring System,” Sensors and Actuators B, vol. 60, 1999, pp. 19-26.
Kurtz T.W., et al., “Recommendations for Blood Pressure Measurement in Humans and Experimental Animals, Part 2: Blood Pressure Measurement in Experimental Animals: A Statement for Professionals From the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research,” Hypertension, Feb. 2005, vol. 45, pp. 299-310.
Kusano H., “Glucose Enzyme Electrode with Percutaneous Interface which Operates Independently of Dissolved Oxygen,” Clinical Physics and Physiological Measurement, 1989, vol. 10, No. 1, pp. 1-9.
Lacourse W.R., et al., “Optimization of Waveforms for Pulsed Amperometric Detection of Carbohydrates Based on Pulsed Voltammetry,” Analytical Chemistry, vol. 65, 1993, pp. 50-52.
Ladd M.F.C., et al., “Structure Determination by X-Ray Crystallography,” 3rd Edition, Plenum Press, 1994, Ch. 1, pp. xxi-xxiv and 1-58.
Lee E., et al., “Effects of Pore Size, Void Volume, and Pore Connectivity on Tissue Responses to Porous Silicone Implants,” Society for Biomateriais, 25th Annual Meeting, 1999, p. 171.
Lee Y., “RFID Coil Design,” Microchip Technology Inc., 1998, AN678, 21 pages.
Lehmann E.D., et al., Retrospective Validation of a Physiological Model of Glucose-Insulin Interaction in Type 1 Diabetes Mellitus. Medical Engineering & Physics, vol. 16, May 1994, pp. 193-202.
Leprince P., et al., “Expanded Polytetrafluoroethylene Membranes to Wrap Surfaces of Circulatory Support Devices in Patients Undergoing Bridge to Heart Transplantation,” European Journal of Cardiothoracic Surgery, 2001, vol. 19, pp. 302-306.
Lerner., et al., “An Implantable Electrochemical Glucose Sensor,” Ann. N. Y. Acad. Sci., vol. 428, May 1984, pp. 263-278.
Lewandowski J.J., et al., “Evaluation of a Miniature Blood Glucose Sensor,” Transactions—American Society for Artificial Internal Organs, vol. 34, 1988, pp. 255-258.
Leypoldt J.K., et al., “Model of a Two-Substrate Enzyme Electrode for Glucose,” Analytical Chemistry, vol. 56, 1984, pp. 2896-2904.
Linke B., et al., “Amperometric Biosensor for In Vivo Glucose Sensing Based on Glucose Oxidase Immobilized in a Redox Hydrogel,” Biosensors and Bioelectronics, vol. 9, 1994, pp. 151-158.
Loebe M., et al., “Use of Polytetrafluoroethylene Surgical Membranes as a Pericardial Substitute,” PTFE Membrane in Correction of Congenital Heart Defects, Texas Heart Institute Journal, 1993, vol. 20, No. 3, pp. 213-217.
Loffler P., et al., “Separation and Determination of Traces of Ammonia in Air by Means of Chromatomembrane Cells,” Fresenius Journal of Analytical Chemistry, 1995, vol. 352, pp. 613-614.
Lohn A., et al., “A Knowledge-Based System for Real-Time Validation of Calibrations and Measurements,” Chemometrics and Intelligent Laboratory Systems, vol. 46, 1999, pp. 57-66.
Lortz J., et al., “What is Bluetooth? We Explain the Newest Short-Range Connectivity Technology,” In Smart Computing Learning Series, Wireless Computing, vol. 8 (5), 2002, pp. 72-74.
Lowe C.R., “Biosensors,” Trends in Biotechnology, vol. 2 (3), 1984, pp. 59-65.
Luong J.H.T., et al., “Solubilization of Multiwall Carbon Nanotubes by 3-Aminopropyltriethoxysilane towards the Fabrication of Electrochemical Biosensors with Promoted Electron Transfer,” Electroanalysis, vol. 16 (1-2), 2004, pp. 132-139.
Lyandres O., et al. “Progress toward an In Vivo Surface-Enhanced Raman Spectroscopy Glucose Sensor,” Diabetes Technology and Therapeutics, vol. 10 (4), 2008, pp. 257-265.
Lyman D J., “Polyurethanes. I. The Solution Polymerization of Diisocyanates with Ethylene Glycol,” Journal of Polymer Science, 1960, vol. XLV, pp. 49-59.
Lynch S.M., et al., “Estimation-Based Model Predictive Control of Blood Glucose in Type I Diabetics: A Simulation Study,” Proceedings of the IEEE 27th Annual Northeast Bioengineering Conference, 2001, pp. 79-80.
Lynn P.A., “Recursive Digital Filters for Biological Signals,” Med. & Biol. Engineering, vol. 9, 1971, pp. 37-43.
Madaras M B., et al., “Microfabricated Amperometric Creatine and Creatinine Biosensors,” Analytica Chimica Acta, 1996, vol. 319, pp. 335-345.
Maidan R., et al., “Elimination of Electrooxidizable Interferent-Produced Currents in Amperometric Biosensors,” Analytical Chemistry, vol. 64, 1992, pp. 2889-2896.
Makale M.T., et al., “Tissue Window Chamber System for Validation of Implanted Oxygen Sensors,” American Journal of Physiology-Heart and Circulatory Physiology, vol. 284, Feb. 21, 2003, pp. 1-27.
Malin S.F., et al., “Noninvasive Prediction of Glucose by Near-Infrared Diffuse Reflectance Spectroscopy,” Clinical Chemistry, vol. 45 (9), 1999, pp. 1651-1658.
Mancy K.H., et al., “A Galvanic Cell Oxygen Analyzer,” Journal of Electroanalytical Chemistry, vol. 4, 1962, pp. 65-92.
Maran A., et al., “Continuous Subcutaneous Glucose Monitoring in Diabetic Patients,” A Multicenter Analysis, Diabetes Care, vol. 25 (2), Feb. 2002, pp. 347-352.
March W.F., “Dealing with the Delay,” Diabetes Technology & Therapeutics, vol. 4 (1), 2002, pp. 49-50.
Marena S., et al., “The Artificial Endocrine Pancreas in Clinical Practice and Research,” Panminerva Medica, vol. 35 (2), 1993, pp. 67-74.
Martin R.F., “General Deming Regression for Estimating Systematic Bias and its Confidence Interval in Method-Comparison Studies,” Clinical Chemistry, vol. 46 (1), 2000, pp. 100-104.
Mascini M., et al., “Glucose Electrochemical Probe with Extended Linearity for Whole Blood,” Journal Pharmaceutical and Biomedical Analysis, vol. 7 (12), 1989, pp. 1507-1512.
Mastrototaro J.J., et al., “An Electroenzymatic Glucose Sensor Fabricated on a Flexible Substrate,” Sensors and Actuators B, vol. 5, 1991, pp. 139-144.
Mastrototaro J.J., et al., “Reproducibility of the Continuous Glucose Monitoring System Matches Previous Reports and the Intended Use of the Product,” Diabetes Care, vol. 26 (1), Jan. 2003, pp. 256-257.
Mastrototaro J.J., “The MiniMed Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S13-S18.
Mathivanar R., et al., “In Vivo Elution Rate of Drug Eluting Ceramic Leads with a Reduced Dose of Dexamethasone Sodium Phosphate,” PACE, vol. 13, Part II, Dec. 1990, pp. 1883-1886.
Matsuki H., “Energy Transfer System Utilizing Amorphous Wires for Implantable Medical Devices,” IEEE Transactions on Magnetics, vol. 31 (2), 1994, pp. 1276-1282.
Matsumoto T., et al., “A Micro-Planar Amperometric Glucose Sensor Unsusceptible to Interference Species,” Sensors and Actuators B, 49, 1998, pp. 68-72.
Matthews D.R., et al., “An Amperometric Needle-Type Glucose Sensor Testing in Rats and Man,” Diabetic Medicine, vol. 5, 1988, pp. 248-252.
Mazze R.S., et al., “Characterizing Glucose Exposure for Individuals with Normal Glucose Tolerance Using Continuous Glucose Monitoring and Ambulatory Glucose Profile Analysis,” Diabetes Technology & Therapeutics, vol. 10 (3), 2008, pp. 149-159.
Mazzola F., et al., “Video Diabetes: A Teaching Tool for Children with Insulin-Dependent Diabetes,” IEEE, Proceedings 7th Annual Symposium on Computer Applications in Medical Care, Oct. 1983, 1 page Abstract.
McCartney L.J., et al., “Near-Infrared Flurescence Lifetime Assay for Serum Glucose Based on Allophycocyanin-Labeled Concanavalin A,” Analytical Biochemistry, vol. 292, 2001, pp. 216-221.
McGarraugh G., et al., “Glucose Measurements Using Blood Extracted From the Forearm and the Finger,” TheraSense, Inc., 2001, pp. 1-8.
McGarraugh G., et al., “Physiological Influences on Off-Finger Glucose Testing”, Diabetes Technology & Therapeutics, vol. 3 (3), 2001, pp. 367-376.
McGrath M.J., et al., “The Use of Differential Measurements with a Glucose Biosensor for Interference Compensation During Glucose Determinations by Flow Injection Analysis,” Biosens Bioelectron, vol. 10, 1995, pp. 937-943.
McKean B.D., et al., “A Telemetry Instrumentation System for Chronically Implanted Glucose and Oxygen Sensors,” IEEE Transactions on Biomedical Engineering, vol. 35 (7), Jul. 1988, pp. 526-532.
Memoli A., et al., “A Comparison between Different Immobilised Glucoseoxidase-Based Electrodes,” Journal of Pharmaceutical and Biomedical Analysis, vol. 29, 2002, pp. 1045-1052.
Merriam Webster Online Dictionary, Definition for “Aberrant,” retrieved from https://www.merriam-webster.com/dictionary/aberrant Aug. 19, 2008, 1 page.
Merriam-Webster Online Dictionary, Definition of “Acceleration” retrieved from http://www.merriam-webster.com/dictionary/Acceleration Jan. 11, 2010, 1 page.
Merriam-Webster Online Dictionary, Definition of “Nominal” retrieved from http://www.merriam-webster.com/dictionary/nominal Apr. 23, 2007, 1 page.
Merriam-Webster Online Dictionary, Definition of “System”. http://www.merriamwebster.com/dictionary/System Jan. 11, 2010, 2 pages.
Metzger M., et al., “Reproducibility of Glucose Measurements using the Glucose Sensor,” Diabetes Care, vol. 25 (6), Jul. 2002, pp. 1185-1191.
Meyerhoff C., et al., “On Line Continuous Monitoring of Subcutaneous Tissue Glucose in Men by Combining Portable Glucosensor With Microdialysis,” Diabetologia, vol. 35 (11), 1992, pp. 1087-1092.
Mid-West Innovators, Inc., “Durometer Product Description,” 2014, 1 page.
Miller J.A., et al., “Development of an Autotuned Transcutaneous Energy Transfer System,” ASAIO Journal, vol. 39, 1993, pp. M706-M710.
Miller K.M., et al., “Generation of IL-1 like Activity in Response to Biomedical Polymer Implants: a Comparison of in Vitro and in Vivo Models,” Journal of Biomedical Materials Research, vol. 23(9), 1989, pp. 1007-1026.
Miller K.M., et al., “Human monocyte/macrophage activation and interleukin 1 generation by biomedical polymers,” Journal of Biomedical Materials Research, vol. 22 (8), 1988, pp. 713-731.
Miller K.M., et al., “In Vitro Stimulation of Fibroblast Activity by Factors Generated from Human Monocytes Activated by Biomedical Polymers,” Journal of Biomedical Materials Research, vol. 23(8), 1989, pp. 911-930.
Minale C., et al., “Clinical Experience with Expanded Polytetrafluoroethylene Gore-Tex Surgical Membrane for Pericardial Closer: A Study of 110 Cases,” Journal of Cardiac Surgery, vol. 3, Sep. 1988, pp. 193-201.
Moatti-Sirat D., et al., “Evaluating In Vitro and In Vivo the Interference of Ascorbate and Acetaminophen on Glucose Detection by a Needle-Type Glucose Sensor,” Biosensors and Bioelectronics, vol. 7, 1992, pp. 345-352.
Moatti-Sirat D., et al., “Reduction of Acetaminophen Interference in Glucose Sensors by a Composite Nafion Membrane: Demonstration in Rats and Man,” Diabetologia, vol. 37 (6), Jun. 1994, pp. 610-616.
Moatti-Sirat., et al., “Towards Continuous Glucose Monitoring: In Vivo Evaluation of a Miniaturized Glucose Sensor Implanted for Several Days in Rat Subcutaneous Tissue,” Diabetologia, vol. 35, 1992, pp. 224-230.
Mond H.G., et al., “The Electrode-Tissue Interface: The Revolutionary Role of Steroid Elution,” PACE, vol. 15, Jan. 1992, pp. 95-107.
Monsod T.P., et al., “Do Sensor Glucose Levels Accurately Predict Plasma Glucose Concentrations During Hypoglycemia and Hyperinsulinemia?,” Diabetes Care, vol. 25 (5), 2002, pp. 889-893.
Morff R.J., et al., “Microfabrication of Reproducible, Economical, Electroenzymatic Glucose Sensors,” Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 12 (2), 1990, pp. 0483-0484.
Mosbach K., et al., “Determination of Heat Changes in the Proximity of Immobilized Enzymes with an Enzyme Thermistor and its Use for the Assay of Metabolites,” Biochimica Biophysica Acta, vol. 403, 1975, pp. 256-265.
Motonaka J., et al., “Determination of Cholesterol and Cholesterol Ester with Novel enzyme Microsensors,” Anal. Chem., vol. 65, 1993, pp. 3258-3261.
Moussy F., et al., “A Miniaturized Nafion-Based Glucose Sensor: In Vitro and In Vivo Evaluation in Dogs,” International Journals of Artificial Organs, vol. 17 (2), 1994, pp. 88-94.
Moussy F., et al., “Biomateriais community examines biosensor biocompatibility,” Diabetes Technology & Therapeutics, vol. 2(3), 2000, pp. 473-477.
Moussy F., et al., “Performance of Subcutaneously Implanted Needle-Type Glucose Sensors Employing a Novel Trilayer Coating,” Analytical Chemistry, vol. 65, Aug. 1, 1993, pp. 2072-2077.
Moussy F., “Implantable Glucose Sensor: Progress and Problems,” IEEE, Nov. 2002, pp. 270-273.
Mowery K.A., et al., “Preparation and Characterization by Hydrophobic Polymeric Films that are Thromboresistant via Nitric Oxide Release,” Biomateriais, vol. 21, 2000, pp. 9-21.
Murphy S.M., et al., “Polymer Membranes in Clinical Sensor Applications, II. The Design and Fabrication of Permselective Hydrogels for Electrochemical Devices,” Biomaterials, 1992, vol. 13 (14), pp. 979-990.
Muslu, “Trickling Filter Performance,” Applied Biochemistry and Biotechnology, vol. 37, 1992, pp. 211-224.
Myler S., et al., “Ultra-Thin-Polysiloxane-Film-Composite Membranes for the Optimisation of Amperometric Oxidase Enzyme Electrodes,” Biosensors & Bioelectronics, vol. 17, 2002, pp. 35-43.
Nakayama Y., et al., “Surface Fixation of Hydrogels: Heparin and Glucose Oxidase Hydrogelated Surfaces” ASAIO Journal, 1992, pp. M421-M424.
Nam Y.S., et al., “A Novel Fabrication Method of Macroporous Biodegradable Polymer Scaffolds Using Gas Foaming Salt as a Porogen Additive,” J Biomed Mater Res, 2000, vol. 53, pp. 1-7.
Neuburger G.G., et al., “Pulsed Amperometric Detection of Carbohydrates at Gold Electrodes with a Two-Step Potential Waveform,” Anal. Chem., vol. 59, 1987, pp. 150-154.
Nintendo Healthcare, Wired, Dec. 1993, 1 page.
Novo Nordisk Pharmaceuticals Inc., “Diabetes Educational Video Game Recognized by Software Publishers Association,” Press Release, Mar. 14, 1994, 4 pages.
Ohara T.J., et al., “Glucose Electrodes Based on Cross-Linked [Os(bpy)2CI](+/2+) Complexed Poly(1-Vinylimidazole) Films,” Analytical Chemistry, vol. 65, Dec. 1993, pp. 3512-3517.
Ohara T.J., et al., ““Wired” Enzyme Electrodes for Amperometric Determination of Glucose or Lactate in the Presence of Interfering Substances,” Anal Chem, vol. 66, 1994, pp. 2451-2457.
Okuda, et al., “Mutarotase Effect on Micro Determinations of D-Glucose and its Anomers with β D-Glucose Oxidase,” Anal Biochem, vol. 43 (1), 1971, pp. 312-315.
Oxford English Dictionary Online, Definition of “Impending,” http://www.askoxford.com/results/?view=devdict&field-12668446_Impending&branch Jan. 11, 2010, 1 page.
Palmisano F., et al., “Simultaneous Monitoring of Glucose and Lactate by an Interference and Cross-Talk Free Dual Electrode Amperometric Biosensor Based on Electropolymerized Thin Films,” Biosensors & Bioelectronics, vol. 15, 2000, pp. 531-539.
Panetti T.S., “Differential Effects of Sphingosine 1-Phosphate and Lysophosphatidic Acid on Endothelial Cells,” Biochimica et Biophysica Acta, vol. 1582, 2002, pp. 190-196.
Panteleon A.E., et al., “The Role of the Independent Variable to Glucose Sensor Calibration,” Diabetes Technology & Therapeutics, vol. 5 (3), 2003, pp. 401-410.
Paramount PDS., “Durometer Made Easy (R) / Durometer Hardness Scales—General Reference Guide,” Paramount Industries Inc., 2008, 1 page.
Park I.B., et al., “Gas Separation Properties of Polysiloxane/Polyether Mixed Soft Segment Urethane Urea Membranes,” Journal of Membrane science, vol. 204, 2002, pp. 257-269.
Parker R.S., et al., “A Model-Based Algorithm for Blood Glucose Control In Type I Diabetic Patients,” IEEE Trans Biomed Engg (BME), vol. 46(2), 1999, pp. 148-157.
Parkes J.L., et al., “A New Consensus Error Grid to Evaluate the Clinical Significance of Inaccuracies in the Measurement of Blood Glucose,” Diabetes Care, vol. 23, No. 8, Aug. 2000, pp. 1143-1148.
Patel H., et al., “Amperometric Glucose Sensors Based on Ferrocene Containing Polymeric Electron Transfer Systems—A Preliminary Report,” Biosensors & Bioelectronics, vol. 18, 2003, pp. 1073-1076.
Peacock W.F., et al., “Cardiac Troponin and Outcome in Acute Heart Failure,” N. Engl. J. Med., vol. 358, 2008, pp. 2117-2126.
Pegoraro M., et al., “Gas Transport Properties of Siloxane Polyurethanes,” Journal of Applied Polymer Science, vol. 57, 1995, pp. 421-429.
Peguin S., et al., “Pyruvate Oxidase and Oxaloacetate Decarboxylase Enzyme Electrodes—Simultaneous Determination of Transaminases with a Two-electrode-based Analyzer,” Analytica Chimica Acta, vol. 222, 1989, pp. 83-93.
Pfeiffer E.F., et al., “On Line Continuous Monitoring of Subcutaneous Tissue Glucose is Feasible by Combining Portable Glucosensor with Microdialysis,” Horm. Metab, Res., vol. 25, 1993, pp. 121-124.
Pfeiffer E.F., “The Glucose Sensor: The Missing Link in Diabetes Therapy,” Horm Metab Res Suppl., vol. 24, 1990, pp. 154-164.
Phillips R.E., et al., “Biomedical Applications of Polyurethanes: Implications of Failure Mechanisms,” Journal of Biomedical application, vol. 3, Oct. 1988, pp. 206-227.
Phillips R.P., “A High Capacity Transcutaneous Energy Transmission System,” ASIAO Journal, vol. 41, 1995, pp, M259-M262.
Pichert J.W., et al., “Issues for the Coming Age of Continuous Glucose Monitoring,” Diabetes Educator, vol. 26 (6), Nov.-Dec. 2000, pp. 969-980.
Pickup J.C., et al., “Developing Glucose Sensors for In Vivo Use,” Elsevier Science Publishers Ltd (UK), TIBTECH, vol. 11, 1993, pp. 285-291.
Pickup J.C., et al., “Implantable Glucose Sensors: Choosing the Appropriate Sensor Strategy,” Biosensors, vol. 3, (1987/1988), pp. 335-346.
Pickup J.C., et al., “In Vivo Molecular Sensing in Diabetes Mellitus: An Implantable Glucose Sensor with Direct Electron Transfer,” Diabetologia, vol. 32, 1989, pp. 213-217.
Pickup J.C., et al., “Potentially-Implantable, Amperometric Glucose Sensors with Mediated Electron Transfer: Improving the Operating Stability,” Biosensors, vol. 4, 1989, pp. 109-119.
Pickup J.C., et al., “Progress Towards in Vivo Glucose Sensing with a Ferrocene-Mediated Amperometric Enzyme Electrode,” Horm Metab Res Suppl, vol. 20, 1988, pp. 34-36.
Pickup J.C., et al., “Responses and Calibration of Amperometric Glucose Sensors Implanted in the Subcutaneous Tissue of Man,” ACTA Diabetol, vol. 30, 1993, pp. 143-148.
Pineda L.M., et al., “Bone Regeneration with Resorbable Polymeric Membranes, III. Effect of Poly(L-lactide) Membrane Pore Size on the Bone Healing Process in Large Defects,” Journal of Biomedical Materials Research, vol. 31, 1996, pp. 385-394.
Pinner S.H., et al., “Cross-Linking of Cellulose Acetate by Ionizing Radiation,” Nature, vol. 184, Oct. 24, 1959, pp. 1303-1304.
Pishko M.V., et al., “Amperometric Glucose Microelectrodes Prepared Through Immobilization of Glucose Oxidase in Redox Hydrogels,” Analytical Chemistry, vol. 63 (20), 1991, pp. 2268-2272.
Pitzer K.R., et al., “Detection of Hypoglycemia with the Glucowatch Biographer,” Diabetes Care, vol. 24 (5), 2001, pp. 881-885.
Poirier J.Y., et al., “Clinical and Statistical Evaluation of Self-Monitoring Blood Glucose Meters,” Diabetes Care, vol. 21 (11), Nov. 1998, pp. 1919-1924.
Poitout V., et al., “A Glucose Monitoring System for on Line Estimation in Man of Blood Glucose Concentration Using a Miniaturized Glucose Sensor Implanted in the Subcutaneous Tissue and a Wearable Control Unit,” Diabetologia, vol. 36, 1993, pp. 658-663.
Poitout V., et al., “Development of a Glucose Sensor for Glucose Monitoring in Man: The Disposable Implant Concept,” Clinical Materials, vol. 15, 1994, pp. 241-246.
Poitout V., et al., “In Vitro and In Vivo Evaluation in Dogs of a Miniaturized Glucose Sensor,” ASAIO Transactions, vol. 37, 1991, pp. M298-M300.
Postlethwaite T.A., et al., “Interdigitated Array Electrode as an Alternative to the Rotated Ring-Disk Electrode for Determination of the Reaction Products of Dioxygen Reduction,” Analytical Chemistry, vol. 68 (17), Sep. 1996, pp. 2951-2958.
Prabhu V.G., et al., “Electrochemical Studies of Hydrogen Peroxide at a Platinum Disc Electrode,” Electrochimica Acta, vol. 26 (6), 1981, pp. 725-729.
Quinn C.A.P., et al., “Biocompatible, Glucose-Permeable Hydrogel for In situ Coating of Implantable Biosensors,” Biomaterials, vol. 18 (24), 1997, pp. 1665-1670.
Quinn C.P., et al., “Kinetics of Glucose Delivery to Subcutaneous Tissue in Rats Measured with 0.3-mm Amperometric Microsensors,” The American Physiological Society, vol. 269, 1995, pp. 155-161.
Rabah M.A., et al., “Electrochemical Wear of Graphite Anodes During Electrolysis of Brine,” Carbon, vol. 29 (2), 1991, pp. 165-171.
Radovsky A.N., et al., “Effects of Dexamethasone Elution on Tissue Reaction Around Stimulating Electrodes of Endocardial Pacing Leads in Dogs,” American Heart Journal, vol. 117 (6), Jun. 1989, pp. 1288-1298.
Rafael E., “Cell Transplantation and Immunoisolation: Studies on a Macroencapsulation Device,” Departments of Transplantation Surgery and Pathology, Karolinska Institutet, Huddinge Hospital, Stockholm, Sweden, 1999, pp. 1-83.
Ratner B.D., “Reducing Capsular Thickness and Enhancing Angiogenesis around Implant Drug Release Systems,” Journal of Controlled Release, vol. 78, 2002, pp. 211-218.
Rawlings R.A., et al., “Translating Glucose Variability Metrics into the Clinic via Continuous Glucose Monitoring: A Graphical User Interface for Diabetes Evaluation (CGM-Guide),” Diabetes Technology & Therapeutics, vol. 13 (12), 2011, pp. 1241-1248.
Raya Systems Pioneers, “Raya Systems Pioneers Healthy Video Games,” PlayRight, Nov. 1993, pp. 14-15.
Reach, et al., “Clinical Sensors for In Vivo Monitoring,” Advances in Biosensors, COMAC Biomedical Engineering Concerted Action on Chemical Sensors for In Vivo Monitoring, Supplement 1: Chapter 1, 1993, pp. 7-28.
Reach G., “A Method for Evaluating in vivo the Functional Characteristics of Glucose Sensors,” Biosensors, vol. 2, 1986, pp. 211-220.
Reach G., et al., “Can Continuous Glucose Monitoring Be Used for the Treatment of Diabetes?,” Analytical Chemistry, vol. 64 (6), Mar. 15, 1992, pp. 381A-386A.
Reach G., “Which Threshold to Detect Hypoglycemia? Value of Receiver-Operator Curve Analysis to Find a Compromise Between Sensitivity and Specificity,” Diabetes Care, vol. 24 (5), May 2001, pp. 803-804.
Rebrin K., et al., “Automated Feedback Control of Subcutaneous Glucose Concentration in Diabetic Dogs,” Diabetologia, vol. 32, 1989, pp. 573-576.
Rebrin K., et al., “Subcutaneous Glucose Monitoring by Means of Electrochemical Sensors: Fiction or Reality?,” Journal of Biomedical Engineering, vol. 14, Jan. 1992, pp. 33-40.
Rebrin K., et al., “Subcutaneous Glucose Predicts Plasma Glucose Independent of Insulin: Implications for Continuous Monitoring,” The American Physiological Society, vol. 277, 1999, pp. E561-E571.
Reush, “Organometallic Compounds,” Chemical Reactivity, Virtual Textbook of Organic Chemistry, Retrieved from http://www.cem.msu.edu/-reuschlVirtualText/orgmetal.htm 2004, pp. 1-16.
Revuelta J.M., et al., “Expanded Polytetrafluoroethylene Surgical Membrane for Pericardial Closure,” The Journal of Thoracic and cardiovascular Surgery, vol. 89 (3), Mar. 1985, pp. 451-455.
Rhodes R.K., et al., “Prediction of Pocket-Portable and Implantable Glucose Enzyme Electrode Performance from Combined Species Permeability and Digital Simulation Analysis,” Analytical Chemistry, vol. 66 (9), May 1, 1994, pp. 1520-1529.
Rigla M., et al., “Real-Time Continuous Glucose Monitoring Together with Telemedical Assistance Improves Glycemic Control and Glucose Stability in Pump-Treated Patients,” Diabetes Technology & Therapeutics, vol. 10 (3), 2008, pp. 194-199.
Rinken T., et al., “Calibration of Glucose Biosensors by Using Pre-Steady State Kinetic Data,” Biosensors & Bioelectronics, vol. 13, 1998, pp. 801-807.
Rivers E.P., et al., “Central Venous Oxygen Saturation Monitoring in the Critically III Patient,” Current Opinion in Critical Care, 2001, vol. 7, pp. 204-211.
Roe J.N., et ai., “Bloodless Glucose Measurements,” Critical Reviews™ in Therapeutic Drug Carrier Systems, vol. 15 (3), 1998, pp. 199-241.
Sachlos E., et al., “Making Tissue Engineering Scaffolds Work Review on the Application of Solid Freeform Fabrication Technology to the Production of Tissue Engineering Scaffolds,” European Cells and Materials, vol. 5, 2003, pp. 29-40.
Sakakida M., et al., “Development of Ferrocene-Mediated Needle-Type Glucose Sensor as a Measure of True Subcutaneous Tissue Glucose Concentrations,” Artif. Organs Today, vol. 2 (2), 1992, pp. 145-158.
Sakakida M., et al., “Ferrocene-Mediated Needle Type Glucose Sensor Covered with Newly Designed Biocompatible Membrane,” Sensors and Actuators B, vol. 13-14, 1993, pp. 319-322.
Salardi S., et al., “The Glucose Area Under the Profiles Obtained with Continuous Glucose Monitoring System Relationships with HbA1C in Pediatric Type 1 Diabetic Patients,” Diabetes Care, vol. 25 (10), Oct. 2002, pp. 1840-1844.
Salehi C., et al., “A Telemetry-Instrumentation System for Long-Term Implantable Glucose and Oxygen Sensors,” Analytical Letters, vol. 29 (13), 1996, pp. 2289-2308.
Samuels M.P., “The Effects of Flight and Altitude,” Arch Dis Child, vol. 89, 2004, pp. 448-455.
San Diego Plastics Inc, “Polyethylene,” Datasheet, Retrieved from http://www.sdplastics.com/polyeth.htmnl on Aug. 19, 2009, 7 pages.
Sanders E., et al., “Fibrous Encapsulation of Single Polymer Microfibers Depends on their Vertical Dimension in Subcutaneous Tissue Polymer Microfibers,” Journal of Biomedical Material Research, vol. 67A, 2003, pp. 1181-1187.
Sansen W., et al., “A Smart Sensor for the Voltammetric Measurement of Oxygen or Glucose Concentrations,” Sensors and Actuators B1, 1990, pp. 298-302.
Sansen W., et al., “Glucose Sensor with Telemetry System,” In Implantable Sensors for Closed Loop Prosthetic Systems edited by Ko W.H, Chapter 12, 1985, pp. 167-175.
Schaffar B.P.H., “Thick Film Biosensors for Metabolites in Undiluted Whole Blood and Plasma Samples,” Analytical Bioanalyticai Chemistry, Dec. 2001, vol. 372, pp. 254-260.
Schmidt F.J., et al., “Calibration of a Wearable Glucose Sensor,” The International Journal of Artificial Organs, Wichtig Publishing, IT, vol. 15 (1), Jan. 1, 1992, pp. 55-61.
Schmidt F.J., et al., “Glucose Concentration in Subcutaneous Extracellular Space,” Diabetes Care, vol. 16 (5), May 1993, pp. 695-700.
Schmidtke D.W., et al., “Accuracy of the One-Point in Vivo Calibration of “Wired” Glucose Oxidase Electrodes Implanted in Jugular Veins of Rats in Periods of Rapid Rise and Decline of the Glucose Concentration,” Analytical Chemistry, vol. 70 (10), May 15, 1998, pp. 2149-2155.
Schmidtke D.W., et al., “Measurement and Modeling of the Transient Difference Between Blood and Subcutaneous Glucose Concentrations in the Rat After Injection of Insulin,” Proceedings of the National Academy of Sciences, vol. 95, Jan. 1998, pp. 294-299.
Schoemaker M., et al., “The SCGMI System: Subcutaneous Continuous Glucose Monitoring Based on Microdialysis Technique,” Diabetes Technology & Therapeutics, vol. 5 (4), 2003, pp. 599-608.
Schoonen A.J.M., et ai., “Development of a Potentially Wearable Glucose Sensor for Patients with Diabetes Mellitus: Design and In-vitro Evaluation,” Biosensors & Bioelectronics, vol. 5, 1990, pp. 37-46.
Schuler, et al., “Modified Gas-Permeable Silicone Rubber Membranes for Covalent Immobilisation of Enzymes and their Use in Biosensor Development,” Analyst, 1999, vol. 124, pp. 1181-1184.
Selam J.L., “Management of Diabetes with Glucose Sensors and Implantable Insulin Pumps,” From the Dream of the 60s to the Realities of the 90s, ASAIO Journal 1997, vol. 43, pp. 137-142.
Service F.J., et al., “Mean Amplitude of Glycemic Excursions, A Measure of Diabetic Instability,” Diabetes, vol. 19 (9), Sep. 1970, pp. 644-655.
Service F.J., et al., “Measurements of Glucose Control,” Diabetes Care, vol. 10 (2), Mar.-Apr. 1987, pp. 225-237.
Service R.F., “Can Sensors Make a Home in the Body?,” Science, Materials Science: Soft Surface, vol. 297, Aug. 9, 2002, pp. 962-963.
Sharkawy A.A., et al., “Engineering the Tissue Which Encapsulates Subcutaneous Implants. I. Diffusion Properties,” Journal of Biomedical Materials Research, vol. 37, 1996, pp. 401-412,
Shawg.W., et al., “In Vitro Testing of a Simply Constructed, Highly Stable Glucose Sensor Suitable for Implantation in Diabetic Patients,” Biosensors & Bioelectronics, vol. 6, 1991, pp. 401-406.
Shichiri, et al., “In Vivo Characteristics of Needle-Type Glucose Sensor-Measurements of Subcutaneous Glucose Concentrations in Human Volunteers,” Implantable Glucose Sensors—The State of the Art, Hormone and Metabolic Research Supplement Series, 1988, vol. 20, pp. 17-20.
Shichiri M., et al., “Glycaemic Control in Pancreatectomized Dogs with a Wearable Artificial Endocrine Pancreas,” Diabetologia, vol. 24, 1983, pp. 179-184.
Shichiri M., et al., “Membrane Design for Extending the Long-Life of an Implantable Glucose Sensor,” Diabetes Nutrition & Metabolism, vol. 2 (4), 1989, pp. 309-313.
Shichiri M., et al., “Needle Type Glucose Sensor for Wearable Artificial Endocrine Pancreas,” In Implantable Sensors for Closed-Loop Prosthetic Systems edited by Ko W.H, Chapter 15, 1985, pp. 197-210.
Shichiri M., et al., “Telemetry Glucose Monitoring Device with Needle-Type Glucose Sensor: A Useful Tool for Blood Glucose Monitoring in Diabetic Individuals,” Diabetes Care, vol. 9 (3), May-Jun. 1986, pp. 298-301.
Shichiri M., et al., “Wearable Artificial Endocrine Pancreas with Needle-Type Glucose Sensor,” Preliminary Communication, Lancet, vol. 2, Nov. 20, 1982, pp. 1129-1131.
Shults M.C., et al., “A Telemetry-Instrumentation System for Monitoring Multiple Subcutaneously Implanted Glucose Sensors,” IEEE Transactions on Biomedical Engineering, vol. 41 (10), Oct. 1994, pp. 937-942.
Sieminski, et al., “Biomaterial-Microvasculature Interactions,” Biomateriais, 2000, vol. 21, pp. 2233-2241.
Sigma-Aldrich Corp., “Cellulose Acetate,” Product Description, Product No. 419028, St. Louis, MO, 2005, 1 page.
Sigma-Aldrich Corp. “Nafion® 117 Solution Product Description, Product No. 70160,” retrieved from https//:www.sigmaaldrich.com/cgi-bin/hsrun/Suite7/Suite/HAHTpage/Suite.HsExternalProd on Apr. 7, 2005, 1 page.
Skyler J.S., “The Economic Burden of Diabetes and the Benefits of Improved Glycemic Control: The Potential Role of a Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S7-S12.
Slater-Maclean L., et al., “Accuracy of Glycemic Measurements in the Critically III,” Diabetes Technology and Therapeutics, vol. 10 (3), 2008, pp. 169-177.
Smith B., et al., “An Externally Powered, Multichannel, Implantable Stimulator-Telemeter for Control of Paralyzed Muscle,” IEEE Transactions on Biomedical Engineering, vol. 45 (4), Apr. 1998, pp. 463-475.
Smith, et al.,“A Comparison of Islet Transplantation and Subcutaneous Insulin Injections for the Treatment of Diabetes Mellitus,” Computers in Biology and Medicine, 1991, vol. 21 (6), pp. 417-427.
Smith, “The Scientist and Engineer's Guide to Digital Signal Processing,” California Technical Publishing, 1997-2007, retrieved from http://www.dspguide.com/ch19.htm on Jan. 1, 2009, 2 Pages.
Smooth-On, “Durometer Shore Hardness Scale,” downloaded from https://www.smooth-on.com/page/durometer-shore-hardness-scale/on May 19, 2016, 1 page.
Sokol L., et al., “Immobilized-Enzyme Rate-Determination Method for Glucose Analysis,” Clinical Chemistry, vol. 26 (1), 1980, pp. 89-92.
Sokolov S., et al., “Metrological Opportunities of the Dynamic Mode of Operating an Enzyme Amperometric Biosensor,” Medical Engineering & Physics, vol. 17 (6), 1995, pp. 471-476.
Sorrells P., “Passive RFID Basics,” Microchip Technology Inc., 1988, AN680, 7 pages.
Sparacino G., et al., “Continuous Glucose Monitoring Time Series and Hypo-Hyperglycemia Prevention: Requirements, Methods, Open Problems,” Current Diabetes Reviews, vol. 4 (3), 2008, pp. 181-192.
Sproule B.A., et al., “Fuzzy Pharmacology: Theory and Applications,” Trends in Pharmacological Sciences, vol. 23 (9), Sep. 2002, pp. 412-417.
Sriyudthsak M., et al., “Enzyme-Epoxy Membrane Based Glucose Analyzing System and Medical Applications,” Biosensors & Bioelectronics, vol. 11 (8), 1996, pp. 735-742.
Steil G.M., et al., “Determination of Plasma Glucose During Rapid Glucose Excursions with a Subcutaneous Glucose Sensor,” Diabetes Technology & Therapeutics, vol. 5 (1), 2003, pp. 27-31.
Stern M., et al., “Electrochemical Polarization: I. A Theoretical Analysis of the Shape of Polarization Curves,” Journal of the Electrochemical Society, vol. 104 (1), Jan. 1957, pp. 56-63.
Sternberg, et al., “Covalent Enzyme Coupling on Cellulose Acetate Membranes for Glucose Sensor Development,” Anal Chem, Dec. 1988, vol. 60(24), pp. 2781-2786.
Sternberg F., et al., “Does Fall in Tissue Glucose Precede Fall in Blood Glucose?,” Diabetologia, vol. 39, 1996, pp. 609-612.
Sternberg R., et al., “Study and Development of Multilayer Needle-type Enzyme Based Glucose Microsensors,” Biosensors, Mar. 20, 1988, vol. 4 (1), pp. 27-40.
Stokes, “Polyether Polyurethanes: Biostable or Not,” Journal of Biomateriais Applications, Oct. 1988, vol. 3, pp. 228-259.
Street, et al., “Islet Graft Assessment in the Edmonton Protocol: Implications for Predicting Long-Term Clinical Outcome,” Diabetes, 2004, vol. 53, pp. 3107-3114.
Street J.O., et al., “A Note on Computing Robust Regression Estimates via Iteratively Reweighted Least Squares,” The American Statistician, vol. 42 (2), May 1988, pp. 152-154.
Submission in Opposition Proceedings for European Application No. 10195519.3, dated Nov. 9, 2020, 33 pages.
Suh, et al., “Behavior of Fibroblasts on a Porous Hyaluronic Acid Incorporated Collagen Matrix,” Yonsei Medical Journal, 2002, vol. 43 (2), pp. 193-202.
Sumino T., et al., “Preliminary Study of Continuous Glucose Monitoring with a Microdialysis Technique,” Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 20 (4), 1998, pp. 1775-1778.
Takatsu I., et al., “Solid State Biosensors Using Thin-Film Electrodes,” Sensors and Actuators, 1987, vol. 11, pp. 309-317.
Takegami S., et al., “Pervaporation of Ethanol/Water Mixtures Using Novel Hydrophobic Membranes Containing Polydimethylsiloxane,” Journal of Membrane Science, vol. 75, 1992, pp. 93-105.
Tamura T., et al., “Preliminary Study of Continuous Glucose Monitoring with a Microdialysis Technique and a Null Method—A Numerical Analysis,” Frontiers of Medical & Biological Engineering, vol. 10 (2), 2000, pp. 147-156.
Tanenberg R.J., et al., “Continuous Glucose Monitoring System: A New Approach to the Diagnosis of Diabetic Gastroparesis,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S73-S80.
Tang, et al., “Fibrin(ogen) Mediates Acute Inflammatory Responses to Biomaterials,” J.Exp.Med, 1993, vol. 178, pp. 2147-2156.
Tang, et al., “Inflammatory Responses to Biomateriais,” Am J Clin Pathol, 1995, vol. 103, pp. 466-471.
Tang, et al., “Mast Cells Mediate Acute Inflammatory Responses to Implanted Biomateriais,” Proceedings of the National Academy of Sciences of the USA, 1998, vol. 95, pp. 8841-8846.
Tang, et al., “Molecular Determinants of Acute Inflammatory Responses to Biomateriais,” J Clin Invest, 1996, vol. 97, pp. 1329-1334.
Tatsuma T., et al., “Oxidase/Peroxidase Bilayer-Modified Electrodes as Sensors for Lactate, Pyruvate, Cholesterol and Uric Acid,” Analytica Chimica Acta, vol. 242, 1991, pp. 85-89.
Taub M.B., et al., “Numerical Simulation of the Effect of Rate of Change of Glucose on Measurement Error of Continuous Glucose Monitors,” Journal of Diabetes Science and Technology, vol. 1 (5), Sep. 2007, pp. 685-694.
Thijssen, et al., “A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 1,Theory and Simulations, Analytica chimica Acta, 1984, vol. 156, pp. 87-101.
Thijssen, et al., “A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 3,Variance Reduction ,Analytica chimica Acta, 1985, vol. 173, pp. 265-272.
Thijssen, et al., “A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 4,Flow Injection Analysis, Analytica chimica Acta, 1985, vol. 174, pp. 27-40.
Thijssen P.C.,“A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 2,Optimal Designs, Analytica chimica Acta, vol. 162, 1984, pp. 253-262.
Thome V., et al., “(Abstract) Can the Decrease in Subcutaneous Glucose Concentration Precede the Decrease in Blood Glucose Level? Proposition for a Push-Pull Kinetics Hypothesis,” Horm. metab. Res., vol. 27, 1995, p. 53.
Thome-Duret V., et al., “Continuous Glucose Monitoring in the Free-Moving Rat,” Metabolism, vol. 47 (7), Jul. 1998, pp. 799-803.
Thome-Duret V., et al., “Modification of the Sensitivity of Glucose Sensor Implanted into Subcutaneous Tissue,” Diabetes & Metabolism, vol. 22, 1996, pp. 174-178.
Thome-Duret V., et al., “Use of a Subcutaneous Glucose Sensor to Detect Decreases in Glucose Concentration Prior to Observation in Blood,” Analytical Chemistry, vol. 68 (21), Nov. 1, 1996, pp. 3822-3826.
Thompson M., et al., “In Vivo Probes: Problems and Perspectives,” Clinical Biochemistry, vol. 19 (5), Oct. 1986, pp. 255-261.
Tibell, et al., “Survival of Macroencapsulated Allogeneic Parathyroid Tissue One Year after Transplantation in Nonimmunosuppressed Humans,” Cell Transplantation, 2001, vol. 10, pp. 591-599.
Tierney M.J., et al., “Effect of Acetaminophen on the Accuracy of Glucose Measurements Obtained with the GlucoWatch Biographer,” Diabetes Technology & Therapeutics, vol. 2 (2), 2000, pp. 199-207.
Tierney M.J., et al., “The Gluco Watch® Biographer: A Frequent, Automatic and Noninvasive Glucose Monitor,” Annals of Medicine, vol. 32, 2000, pp. 632-641.
Tilbury J.B., et al., “Receiver Operating Characteristic Analysis for Intelligent Medical Systems—A New Approach for Finding Confidence Intervals,” IEEE Transactions on Biomedical Engineering, vol. 47 (7), Jul. 2000, pp. 952-963.
Torjman M.C., et al., “Glucose Monitoring in Acute Care: Technologies on the Horizon,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 178-181.
Trajanoski Z., et al., “Neural Predictive Controller for Insulin Delivery Using the Subcutaneous Route,” IEEE Transactions on Biomedical Engineering, vol. 45(9), 1998, pp. 1122-1134.
Trecroci D., “A Glimpse into the Future-Continuous Monitoring of Glucose with a Microfiber,” Diabetes Interview, Jul. 2002, pp. 42-43.
TSE P.S.H., et al., “Time-Dependent Inactivation of Immobilized Glucose Oxidase and Catalase,” Biotechnology & Bioengineering, vol. 29, 1987, pp. 705-713.
Turner A.P.F., “Amperometric Biosensor based on Mediator-Modified Electrodes,” Methods in Enzymology, 1988, vol. 137, pp. 90-103.
Turner A.P.F., et al., “Carbon Monoxide: Acceptor Oxidoreductase from Pseudomonas Thermocarboxydovorans Strain C2 and its Use in a Carbon Monoxide Sensor,” Analytica Chimica Acta, vol. 163, 1984, pp. 161-174.
Turner A.P.F., et al., “Diabetes Mellitus: Biosensors for Research and Management,” Biosensors, vol. 1, 1985, pp. 85-115.
Unger J., et al., “Glucose Control in the Hospitalized Patient,” Emergency Medicine, vol. 36 (9), 2004, pp. 12-18.
Updike S.J., et al., “A Subcutaneous Glucose Sensor with Improved Longevity, Dynamic Range, and Stability of Calibration,” Diabetes Care, vol. 23 (2), Feb. 2000, pp. 208-214.
Updike S.J., et al., “Continuous Glucose Monitor Based on an Immobilized Enzyme Electrode Detector,” Journal of Laboratory and Clinical Medicine, vol. 93(4), 1979, pp. 518-527.
Updike S.J., et al., “Enzymatic Glucose Sensor: Improved Long-Term Performance in Vitro and In Vivo,” ASAIO Journal, vol. 40 (2), Apr.-Jun. 1994, pp. 157-163.
Updike S.J., et al., “Implanting the Glucose Enzyme Electrode: Problems, Progress, and Alternative Solutions,” Diabetes Care, vol. 5 (3), May-Jun. 1982, pp. 207-212.
Updike S.J., et al., “Laboratory Evaluation of New Reusable Blood Glucose Sensor,” Diabetes Care, vol. 11 (10), Nov.-Dec. 1988, pp. 801-807.
Updike S.J., et al., “Principles of Long-Term Fully Implanted Sensors with Emphasis on Radiotelemetric Monitoring of Blood Glucose Form Inside a Subcutaneous Foreign Body Capsule (FBC),” Edited by Fraser D M, Biosensors in the Body: Continuous in vivo Monitoring, John Wiley & Sons Ltd., New York, 1997, Chapter 4, pp. 117-137.
Updike S.J., et al., “The Enzyme Electrode,” Nature, vol. 214, Jun. 3, 1967, pp. 986-988.
U.S. Pat. No. 7,530,950, May 12, 2009, Brister et al. (withdrawn).
Utah Medical Products Inc., “Deltran—Disposable Blood Pressure Transducers,” Product Specifications, 2003-2006, 6 pages.
Vadgama P., “Diffusion Limited Enzyme Electrodes,” NATO ASI Series: Series C, Math and Phys. Sci, vol. 226, 1988, pp. 359-377.
Vadgama P., “Enzyme Electrodes as Practical Biosensors,” Journal of Medical Engineering & Technology, vol. 5 (6), Nov. 1981, pp. 293-298.
Valdes T.I., et al., “In Vitro and In Vivo Degradation of Glucose Oxidase Enzyme used for an Implantable Glucose Biosensor,” Diabetes Technology & Therapeutics, vol. 2 (3), 2000, pp. 367-376.
Van Den Berghe, “Tight Blood Glucose Control with Insulin in “Real-Life” Intensive Care,” Mayo Clinic Proceedings, vol. 79 (8), Aug. 2004, pp. 977-978.
Velho G., et al., “In Vitro and In Vivo Stability of Electrode Potentials in Needle-Type Glucose Sensors,” Influence of Needle Material, Diabetes, vol. 38, Feb. 1989, pp. 164-171.
Velho G., et al., “Strategies for Calibrating a Subcutaneous Glucose Sensor,” Biomed Biochim Acta, vol. 48 (11/12), 1989, pp. 957-964.
Vig, et al., “A Review of Sensor Sensitivity and Stability,” IEEE/EIA International Frequency Control Symposium and Exibition, 2000, pp. 30-33.
Von Woedtke T., et al., “in Situ Calibration of Implanted Electrochemical Glucose Sensors,” Biomed. Biochim. Acta 48 vol. 11/12, 1989, pp. 943-952.
Von Woedtke T., et al., “Sterilization of Enzyme Glucose Sensors: Problems and Concepts,” Biosensors & Bioelectronics, vol. 17, 2002, pp. 373-382.
Wade L.G., “Reactions of Aromatic Compounds,” Organic Chemistry, Chapter 17, 5th edition, 2003, pp. 762-763.
Wagner, et al., “Continuous Amperometric Monitoring of Glucose in a Brittle Diabetic Chimpanzee with a Miniature Subcutaneous Electrode,” Proc. Natl. Acad. Sci. USA, vol. 95, May 1998, pp. 6379-6382.
Wang J., “Electrochemical Glucose Biosensors,” American Chemical Society, Chemical Reviews, Published on Web, Dec. 23, 2007, pp. 1-12.
Wang J., et al., “Highly Selective Membrane-Free Mediator-Free Glucose Biosensor,” Analytical Chemistry, vol. 66 (21), Nov. 1, 1994, pp. 3600-3603.
Wang X., et al., “Improved Ruggedness for Membrane-Based Amperometric Sensors using a Pulsed Amperometric Method,” Analytical Chemistry, vol. 69 (21), Nov. 1, 1997, pp. 4482-4489.
Ward, et al., “A Wire-Based Dual-Analyte Sensor for Glucose and Lactate: In Vitro and In Vivo Evaluation,” Diabetes Technology and Therapeutics, 2004, vol. 6 (3), pp. 389-401.
Ward W.K., et al., “A New Amperometric Glucose Microsensor: In Vitro and Short-Term In Vivo Evaluation,” Biosensors & Bioelectronics, vol. 17, 2002, pp. 181-189.
Ward W.K., et al., “Assessment of Chronically Subcutaneous Glucose Sensors in Dogs: The Effect of Surrounding Fluid Masses,” ASAIO Journal, 1999, vol. 45 (6), pp. 555-561.
Ward W.K., et al., “Rise in Background Current Over Time in a Subcutaneous Glucose Sensor in the Rabbit,” Relevance to Calibration and Accuracy, Biosensors & Bioelectronics, vol. 15, 2000, pp. 53-61.
Ward W.K., et al., “Understanding Spontaneous Output Fluctuations of an Amperometric Glucose Sensor: Effect of Inhalation Anesthesia and Use of a Nonenzyme Containing Electrode,” ASAIO Journal, 2000, pp. 540-546.
Wientjes K.J.C., “Development of a Glucose Sensor for Diabetic Patients,” (Ph.D. Thesis), 2000, 212 pages.
Wikipedia., “Intravenous Therapy,” http://en.wikipedia.org/wiki/Intravenous_therapy, Aug. 15, 2006, 6 pages.
Wilkins E., et al., “Glucose Monitoring: State of the Art and Future Possibilities,” Med. Eng. Phys., vol. 18 (4), 1996, pp. 273-288.
Wilkins E., et al., “Integrated Implantable Device for Long-Term Glucose Monitoring,” Biosensors & Bioelectronics, vol. 10, 1995, pp. 485-494.
Wilkins E.S., et al., “The Coated Wire Electrode Glucose Sensor,” Horm Metab Res Suppl., vol. 20, 1988, pp. 50-55.
Wilson G. S., et al., “Biosensors for Real-time in Vivo Measurements,” Biosensors and Bioelectronics, Elsevier Science Ltd, Jan. 15, 2005, vol. 20 (12), pp. 2388-2403.
Wilson G.S., et al., “Enzyme-Based Biosensors for In Vivo Measurements,” Chem. Rev., vol. 100, 2000, pp. 2693-2704.
Wilson G.S., et al., “Progress Toward the Development of an Implantable Sensor for Glucose,” Clinical Chemistry, vol. 38 (9), 1992, pp. 1613-1617.
Wolpert H., “Establishing a Continuous Glucose Monitoring Program,” Journal of Diabetes Science and Technology, Mar. 2008, vol. 2 (2), pp. 307-310.
Wood W D., et al., “Hermetic Sealing with Epoxy,” Pave Technology-Mechanical Engineering, Mar. 1990, 3 pages.
Woodward S.C., “How Fibroblasts and Giant Cells Encapsulate Implants: Considerations in Design of Glucose Sensors,” Diabetes Care, vol. 5 (3) May-Jun. 1982, pp. 278-281.
Worsley G.J et al., “Measurement of Glucose in Blood with a Phenylboronlc Acid Optical Sensor,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 213-220.
Wright M., et al., “Bioelectrochemical Dehalogenations via Direct Electrochemistry of Poly(ethylene oxide)-Modified Myoglobin,” Electrochemistry Communications, vol. 1, 1999, pp. 609-613.
Written Opinion for Application No. PCT/US2002/023903 dated Nov. 15, 2004, 5 pages.
Wu H., et al., “In Situ Electrochemical Oxygen Generation with an Immunoisolation Device,” Annals New York Academy of Sciences, vol. 875, 1999, pp. 105-125.
Yamasaki Y., et ai., “Direct Measurement of Whole Blood Glucose by a Needle-Type Sensor,” Clinica Chimica Acta. 93, 1989, pp. 93-98.
Yamasaki Y., “The Development of a Needle-Type Glucose Sensor for Wearable Artificial Endocrine Pancreas,” Medical Journal of Osaka University, vol. 35 (1-2), Sep. 1984, pp. 25-34.
Yang C., et al., “A Comparison of Physical Properties and Fuel Cell Performance of Nafion and Zirconium Phosphate/Nation Composite Membranes,” Journal of Membrane Science, vol. 237, 2004, pp. 145-161.
Yang Q., et al., “Development of Needle-Type Glucose Sensor with High Selectivity,” Science and Actuators B, vol. 46, 1998, pp. 249-256.
Yang S., et al., “A Glucose Biosensor Based on an Oxygen Electrode: In-Vitro Performances in a Model Buffer Solution and in Blood Plasma,” Biomedical Instrumentation & Technology, vol. 30 (1), 1996, pp. 55-61.
Yang S., et al., “Glucose Biosensors with Enzyme Entrapped in Polymer Coating,” Biomedical Instrument and Techology, Mar./Apr. 1995, vol. 29 (2), pp. 125-133.
Yang X., et al., “Polyelectrolyte and Molecular Host Ion Self-Assembly to Multilayer Thin Films: An Approach to Thin Film Chemical Sensors,” Sensors and Actuators B, vol. 45, 1997, pp. 87-92.
Ye L., et al., “High Current Density Wired' Quinoprotein Glucose Dehydrogenase Electrode,” Analytical Chemistry, vol. 65, 1993, pp. 238-241.
Zamzow K.L., et al., “Development and Evaluation of a Wearable Blood Glucose Monitor,” ASAIO Transactions, vol. 36 (3), 1990, pp. M588-M591.
Zavalkoff S.R., et al., “Evaluation of Conventional Blood Glucose Monitoring as an Indicator of Integrated Glucose Values Using a Continuous Subcutaneous Sensor,” Diabetes Care, vol. 25(9), 2002, pp. 1603-1606.
Zethelius B., et al., “Use of Multiple Biomarkers to Improve the Prediction of Death From Cardiovascular Causes,” N. Engl. J. Med., vol. 358, May 2008, pp. 2107-2116.
Zhang, et al., “Elimination of the Acetaminophen Interference in an Implantable Glucose Sensor,” Analytical Chemistry, 1994, vol. 66 (7), pp. 1183-1188.
Zhang Y., et al., “Electrochemical Oxidation of H2O2 on Pt and Pt + Ir Electrodes in Physiological Buffer and its Applicability to H2O2-Based Biosensors,” J. Electro Analytical Chemistry, vol. 345, 1993, pp. 253-271.
Zhang Y., et al., “In Vitro and In Vivo Evaluation of Oxygen Effects on a Glucose Oxidase Based Implantable Glucose Sensor,” Analytica Chimica Acta, vol. 281, 1993, pp. 513-520.
Zhu, et al., “Fabrication and Characterization of Glucose Sensors Based on a Microarray H2O2 Electrode,” Biosensors & Bioelectronics, 1994, vol. 9, pp. 295-300.
Zhu, et al., “Planar Amperometric Glucose Sensor Based on Glucose Oxidase Immobilized by Chitosan Film on Prussian blue Layer,” Sensors, 2002, vol. 2, pp. 127-136.
Ziaie, et al., “A Single-Channel Implantable Microstimulator for Functional Neuromuscular Stimulation,” IEEE Transactions on Biomedical Engineering, 1997, vol. 44(10), pp. 909-920.
Brief communication for European Patent Application No. 20210129.1, dated Mar. 13, 2023, 40 pages.
Corrected Petition for Inter Partes Review of Claims, Abbott Diabetes Care Inc. , vs Dexcom, Inc., for the U.S. Pat. No. 10,993,642, dated May 7, 2022, 109 pages.
Decision Granting Institution of Inter Partes Review, Abbott Diabetes Care Inc. , vs Dexcom, Inc., for the U.S. Pat. No. 10,993,642, dated Nov. 3, 2022, 39 pages.
Decision Granting Institution of Inter Partes Review, Abbott Diabetes Care Inc. , vs Dexcom, Inc., for the U.S. Pat. No. 10,993,642, dated Nov. 3, 2022, 40 pages.
Decision Granting Institution of Inter Partes Review, Abbott Diabetes Care Inc. , vs Dexcom, Inc., for the U.S. Pat. No. 11,000,213, dated Nov. 3, 2022, 43 pages.
Decision Granting Institution of Inter Partes Review, Abbott Diabetes Care Inc. , vs Dexcom, Inc., for the U.S. Pat. No. 11,000,213, dated Nov. 3, 2022, 46 pages.
Defendant's Preliminary Invalidity Contentions, Dexcom, Inc. , vs Abbott Diabetes Care Inc. and Abott Diabetes Care Sales Corp, dated Jan. 25, 2022, 239 pages.
Main R.I., et al., “Data Management Programs for Bedside Glucose Testing,” Laboratory Medicine, Dec. 1994, vol. 25, No. 12, 8 pages.
Notice of Opposition for the European application No. 20210129.1, dated Jun. 1, 2022, 45 pages.
Notice of Opposition for the European application No. 20210129.1, dated May 30, 2022, 109 pages.
Patent Owner's Preliminary Response, Abbott Diabetes Care Inc.,, vs Dexcom, Inc., for the U.S. Pat. No. 10,993,642, dated Aug. 4, 2022, 74 pages.
Patent Owner's Preliminary Response, Abbott Diabetes Care Inc.,, vs Dexcom, Inc., for the U.S. Pat. No. 10,993,642, dated Aug. 4, 2022, 83 pages.
Patent Owner's Preliminary Response, Abbott Diabetes Care Inc., vs Dexcom, Inc., for the U.S. Pat. No. 11,000,213, dated Aug. 4, 2022, 75 pages.
Patent Owner's Preliminary Response, Abbott Diabetes Care Inc., vs Dexcom, Inc., for the U.S. Pat. No. 11,000,213, dated Aug. 4, 2022, 85 pages.
Petition for Inter Partes Review of Claims, Abbott Diabetes Care Inc., vs Dexcom, Inc., for the U.S. Pat. No. 10,993,642, dated Apr. 23, 2022, 102 pages.
Petition for Inter Partes Review of Claims, Abbott Diabetes Care Inc., vs Dexcom, Inc., for the U.S. Pat. No. 10,993,642, dated Apr. 23, 2022, 109 pages.
Petition for Inter Partes Review of Claims, Abbott Diabetes Care Inc., vs Dexcom, Inc., for the U.S. Pat. No. 11,000,213, dated Apr. 23, 2022, 92 pages.
Petition for Inter Partes Review of Claims, Abbott Diabetes Care Inc., vs Dexcom, Inc., for the U.S. Pat. No. 11,000,213, dated Apr. 23, 2022, 93 pages.
Reply of the Patent Proprietor to the Notice(s) of Opposition for the Eurpean application No. 20210129.1, dated Jan. 2, 2023, 52 pages.
U.S. Appl. No. 60/606,334, filed Aug. 31, 2004, 36 pages.
Garg S., et al. “Improvement in Glycemic Excursions with a Transcutaneous, Real-Time Continuous Glucose Sensor: A Randomized Controlled Trial,” Diabetes Care, vol. 29(1), 2006, pp. 44-50.
EP 3797682 Notice of Opposition Letter dated Mar. 2, 2022 by Opponent Roche Diabetes Care GmbH, 43 pages.
EP 3797682 Notice of Opposition Letter dated Mar. 2, 22 by Opponent Abbott Diabetes Care Inc., 90 pages.
EP 3797682 Letter from patent owner dated Aug. 2, 2022, 31 pages.
EP 3797682 Letter from Opponent in response to Patent Owner's Aug. 2, 2022 Letter, dated Nov. 30, 2022, 20 pages.
EP 3797682 Letter from Opponent in response to Patent Owner's Aug. 2, 2022 Letter, 28 pages.
Poitout, V., et al., Calibration in dogs of a subcutaneous miniaturized glucose sensor using a glucose meter for blood glucose determination, Biosensors and Bioelectronics vol. 7, Issue 8, 1992, pp. 587-592, 1992.
Nishida, K., et al., “Development of a ferrocene-mediated needle-type glucose sensor covered with newly designed biocompatible membrane, 2-methacryloyloxyethyl phosphorelcholine -co-n-butyl methacrylate”, Medical Progress though Technology 21: 91- 103, 1995, 13 pgs.
Chen, Ting, et al., “In vivo Glucose Monitoring with Miniature ‘Wired’ Glucose Oxidase Electrodes”, Analytical Sciences 2001, vol. 17 Supplement, The Japan Society for Analytical Chemistry, 4 pgs.
Johnson, Kirk W. et al., “Reduction of Electrooxidizable Interferent Effects: Optimization of the Applied Potential for Amperometric Glucose Sensors”, Central Nervous System Research Division, Lilly Research Laboratories, Electroanalysis, 1994, 6 pgs.
Turner, Anthony P.F., et al., “Biosensors: Fundamentals and Applications”, Oxford Science Publications, 1987, 786 pgs.
Fischer, U., “Fundamentals of Glucose Sensors”, Institute of Diabetes 'Gerhardt Katsch', Diabetic Medicine, John Wiley & Sons, Ltd., 1991, 13 pgs.
Lodwig, Volker et al., “Continuous Glucose Monitoring with Glucose Sensors: Calibration and Assessment Criteria”, Diabetes Technology & Therapeutics, vol. 5, No. 4, 2003, 15 pgs.
EP 3797682 Notice of Opposition Letter dated Mar. 2, 2022 by Opponent Roche Diabetes Care GmbH, 43 pages.
EP 3797682 Notice of Opposition Letter dated Mar. 2, 22 by Opponent Abbott Diabetes Care Inc., 90 pages.
EP 3797682 Letter from patent owner dated Aug. 2, 2022, 31 pages.
EP 3797682 Letter from Opponent in response to Patent Owner's Aug. 2, 2022 Letter, dated Nov. 30, 2022, 20 pages.
EP 3797682 Letter from Opponent in response to Patent Owner's Aug. 2, 2022 Letter, 28 pages.
Poitout, V., et al., Calibration in dogs of a subcutaneous miniaturized glucose sensor using a glucose meter for blood glucose determination, Biosensors and Bioelectronics vol. 7, Issue 8, 1992, pp. 587-592, 1992.
Nishida, K., et al., “Development of a ferrocene-mediated needle-type glucose sensor covered with newly designed biocompatible membrane, 2-methacryloyloxyethyl phosphorelcholine -co-n-butyl methacrylate”, Medical Progress though Technology 21: 91- 103, 1995, 13 pgs.
Chen, Ting, et al., “In vivo Glucose Monitoring with Miniature ‘Wired’ Glucose Oxidase Electrodes”, Analytical Sciences 2001, vol. 17 Supplement, The Japan Society for Analytical Chemistry, 4 pgs.
Johnson, Kirk W. et al., “Reduction of Electrooxidizable Interferent Effects: Optimization of the Applied Potential for Amperometric Glucose Sensors”, Central Nervous System Research Division, Lilly Research Laboratories, Electroanalysis, 1994, 6 pgs.
Turner, Anthony P.F., et al., “Biosensors: Fundamentals and Applications”, Oxford Science Publications, 1987, 786 pgs.
Fischer, U., “Fundamentals of Glucose Sensors”, Institute of Diabetes 'Gerhardt Katsch', Diabetic Medicine, John Wiley & Sons, Ltd., 1991, 13 pgs.
Lodwig, Volker et al., “Continuous Glucose Monitoring with Glucose Sensors: Calibration and Assessment Criteria”, Diabetes Technology & Therapeutics, vol. 5, No. 4, 2003, 15 pgs.
Related Publications (1)
Number Date Country
20220125355 A1 Apr 2022 US
Provisional Applications (1)
Number Date Country
60660743 Mar 2005 US
Continuations (9)
Number Date Country
Parent 17076714 Oct 2020 US
Child 17574447 US
Parent 16983885 Aug 2020 US
Child 17076714 US
Parent 16691107 Nov 2019 US
Child 16983885 US
Parent 16457628 Jun 2019 US
Child 16691107 US
Parent 15787595 Oct 2017 US
Child 16457628 US
Parent 15065623 Mar 2016 US
Child 15787595 US
Parent 13607162 Sep 2012 US
Child 15065623 US
Parent 12683755 Jan 2010 US
Child 13607162 US
Parent 11373628 Mar 2006 US
Child 12683755 US