Patent Grant
9937293
The present invention relates generally to systems and methods monitoring glucose in a host. More particularly, the present invention relates to an integrated medicament delivery device and continuous glucose sensor.
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 may cause an array of physiological derangements (for example, 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) may 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. In fact, it is not only unlikely that a diabetic will take a timely SMBG value, but the diabetic will not know if their blood glucose value is going up (higher) or down (lower) based on conventional methods, inhibiting their ability to make educated insulin therapy decisions.
Home diabetes therapy requires personal discipline of the user, appropriate education from a doctor, proactive behavior under sometimes-adverse situations, patient calculations to determine appropriate therapy decisions, including types and amounts of administration of insulin and glucose into his or her system, and is subject to human error. Technologies are needed that ease the burdens faced by diabetic patients, simplify the processes involved in treating the disease, and minimize user error which may cause unnecessarily dangerous situations in some circumstances.
In a first embodiment, a method for treating diabetes with an integrated glucose sensor and medicament delivery device is provided, including: receiving in a receiver a data stream from a glucose sensor, including one or more sensor data points; calculating medicament therapy responsive to the one or more sensor data points; validating the calculated therapy based on at least one of data input into the receiver and data obtained from an integrated single point glucose monitor; and outputting validated information reflective of the therapy recommendations.
In an aspect of the first embodiment, the therapy validation is configured to trigger a fail-safe module, if the validation fails, wherein the user must confirm a therapy decision prior to outputting therapy recommendations.
In an aspect of the first embodiment, the output step includes outputting the sensor therapy recommendations to a user interface.
In an aspect of the first embodiment, the output step includes displaying the sensor therapy recommendations on the user interface of at least one of a receiver and a medicament delivery device.
In an aspect of the first embodiment, the output step includes transmitting the therapy recommendations to a medicament delivery device.
In an aspect of the first embodiment, the output step includes delivering the recommended therapy via an automated delivery device.
In a second embodiment, a method for treating diabetes in a host with an integrated glucose sensor and medicament delivery device is provided, including: receiving in a receiver medicament delivery data responsive to medicament delivery from a medicament delivery device; receiving in a receiver a data stream from a glucose sensor, including one or more sensor data points for a time period before and after the medicament delivery; determining a host's metabolic response to the medicament delivery; receiving a subsequent data stream from the glucose sensor including one or more sensor data points; and calculating medicament therapy responsive to the host's metabolic response to the medicament delivery.
In an aspect of the second embodiment, the host's metabolic response is calculated using a pattern recognition algorithm.
In an aspect of the second embodiment, the step of determining a host's metabolic response to medicament delivery is repeated when the receiver receives additional medicament delivery data.
In an aspect of the second embodiment, the host's metabolic response iteratively determined for a time period exceeding one week.
In a third embodiment, a method for estimating glucose levels from an integrated glucose sensor and medicament delivery device is provided, including: receiving in a receiver a data stream from a glucose sensor, including one or more sensor data points; receiving in the receiver medicament delivery data responsive to medicament delivery from a medicament delivery device; evaluating medicament delivery data with glucose sensor data corresponding to delivery and release times of the medicament delivery data to determine individual metabolic patterns associated with medicament delivery; and estimating glucose values responsive to individual metabolic patterns associated with the medicament delivery.
In an aspect of the third embodiment, the individual's metabolic patterns associated with medicament delivery are calculated using a pattern recognition algorithm.
In an aspect of the third embodiment, the step of determining the individual's metabolic patterns to medicament delivery is repeated when the receiver receives additional medicament delivery data.
In an aspect of the third embodiment, the individual's metabolic patterns are iteratively determined for a time period exceeding one week.
In a fourth embodiment, an integrated system for monitoring and treating diabetes is provided, including: a glucose sensor, wherein the glucose sensor substantially continuously measures glucose in a host for a period exceeding one week, and outputs a data stream, including one or more sensor data points; a receiver operably connected to the glucose sensor, wherein the receiver is configured to receive the data stream; and a medicament delivery device, wherein the delivery device is at least one of physically and operably connected to the receiver.
In an aspect of the fourth embodiment, the glucose sensor includes an implantable glucose sensor.
In an aspect of the fourth embodiment, the glucose sensor includes a long-term subcutaneously implantable glucose sensor.
In an aspect of the fourth embodiment, the medicament delivery device includes a syringe detachably connectable to the receiver.
In an aspect of the fourth embodiment, the medicament delivery device includes one or more transdermal patches detachably connectable to the receiver.
In an aspect of the fourth embodiment, the medicament delivery device includes an inhaler or spray delivery device detachably connectable to the receiver.
In an aspect of the fourth embodiment, the medicament delivery device includes a pen or jet-type injector.
In an aspect of the fourth embodiment, the medicament delivery device includes a transdermal pump.
In an aspect of the fourth embodiment, the medicament delivery device includes an implantable pump.
In an aspect of the fourth embodiment, the medicament delivery device includes a manual implantable pump.
In an aspect of the fourth embodiment, the medicament delivery device includes a cell transplantation device.
In an aspect of the fourth embodiment, the medicament delivery device is detachably connected to the receiver.
In an aspect of the fourth embodiment, the medicament delivery device is operably connected to the receiver by a wireless connection.
In an aspect of the fourth embodiment, the medicament delivery device is operably connected by a wired connection.
In an aspect of the fourth embodiment, further including a single point glucose monitor, wherein the single point glucose monitor is at least one of physically and operably connected to the receiver.
In an aspect of the fourth embodiment, the glucose sensor includes an enzyme membrane system for electrochemical detection of glucose the single point glucose monitor includes an enzyme membrane system for electrochemical detection of glucose.
In an aspect of the fourth embodiment, the receiver includes a microprocessor, and wherein the microprocessor includes programming for calculating and outputting medicament delivery instructions
In an aspect of the fourth embodiment, the microprocessor further includes a validation module that validates the medicament delivery instructions prior to outputting the instructions.
In an aspect of the fourth embodiment, the receiver is configured to receive medicament delivery data responsive to medicament delivery for a first time period from the medicament delivery device.
In an aspect of the fourth embodiment, the receiver includes a microprocessor, and wherein the microprocessor includes programming to determine a host's metabolic response to the medicament delivery by evaluating the sensor data points substantially corresponding to delivery and release of the medicament delivery for the first time period.
In an aspect of the fourth embodiment, the microprocessor calculates medicament therapy for a second time period responsive to sensor data and the host's metabolic response to the medicament delivery.
In an aspect of the fourth embodiment, the microprocessor includes programming to estimate glucose values responsive to glucose sensor data and host's metabolic response.
The following description and examples illustrate some exemplary embodiments of the disclosed 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 certain exemplary embodiment should not be deemed to limit the scope of the present invention.
In order to facilitate an understanding of the disclosed invention, a number of terms are defined below.
The term “continuous glucose sensor,” as used herein, is a broad term and are used in its ordinary sense, including, but not limited to, a device that continuously or continually measures glucose concentration, for example, at time intervals ranging from fractions of a second up to, for example, 1, 2, or 5 minutes, or longer. It should be understood that continual or continuous glucose sensors can continually measure glucose concentration without requiring user initiation and/or interaction for each measurement, such as described with reference to U.S. Pat. No. 6,001,067, for example.
The phrase “continuous glucose sensing,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, the period in which monitoring of plasma glucose concentration is continuously or continually performed, for example, at time intervals ranging from fractions of a second up to, for example, 1, 2, or 5 minutes, or longer.
The term “biological sample,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, sample of a host body, for example, blood, interstitial fluid, spinal fluid, saliva, urine, tears, sweat, or the like.
The term “host,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, mammals such as humans.
The term “biointerface membrane,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, a permeable or semi-permeable membrane that can include two or more domains and is typically constructed of materials of a few microns thickness or more, which can be placed over the sensing region to keep host cells (for example, macrophages) from gaining proximity to, and thereby damaging the sensing membrane or forming a barrier cell layer and interfering with the transport of glucose across the tissue-device interface.
The term “sensing membrane,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, a permeable or semi-permeable membrane that can be comprised of two or more domains and is typically constructed of materials of a few microns thickness or more, which are permeable to oxygen and are optionally permeable to glucose. 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 “domain,” as used herein is a broad term and is used in its ordinary sense, including, without limitation, regions of a membrane that can be layers, uniform or non-uniform gradients (for example, anisotropic), functional aspects of a material, or provided as portions of the membrane.
As used herein, the term “copolymer,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, polymers having two or more different repeat units and includes copolymers, terpolymers, tetrapolymers, etc.
The term “sensing region,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, the region of a monitoring device responsible for the detection of a particular glucose. In one embodiment, the sensing region generally 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 connection at another location on the body, and a sensing membrane affixed to the body and covering the electrochemically reactive surface. The counter electrode typically has a greater electrochemically reactive surface area than the working electrode. During general operation of the sensor a biological sample (for example, blood or interstitial fluid) or a portion thereof contacts (for example, directly or after passage through one or more domains of the sensing membrane) an enzyme (for example, glucose oxidase); the reaction of the biological sample (or portion thereof) results in the formation of reaction products that allow a determination of the glucose level in the biological sample.
The term “electrochemically reactive surface,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, the surface of an electrode where an electrochemical reaction takes place. In the case of the working electrode, the hydrogen peroxide produced by the enzyme catalyzed reaction of the glucose being detected reacts creating a measurable electronic current (for example, detection of glucose 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 “electrochemical cell,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, a device in which chemical energy is converted to electrical energy. Such a cell typically consists of two or more electrodes held apart from each other and in contact with an electrolyte solution. Connection of the electrodes to a source of direct electric current renders one of them negatively charged and the other positively charged. Positive ions in the electrolyte migrate to the negative electrode (cathode) and there combine with one or more electrons, losing part or all of their charge and becoming new ions having lower charge or neutral atoms or molecules; at the same time, negative ions migrate to the positive electrode (anode) and transfer one or more electrons to it, also becoming new ions or neutral particles. The overall effect of the two processes is the transfer of electrons from the negative ions to the positive ions, a chemical reaction.
The term “proximal” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, near to a point of reference such as an origin or a point of attachment. For example, in some embodiments of a sensing membrane that covers an electrochemically reactive surface, the electrolyte domain is located more proximal to the electrochemically reactive surface than the interference domain.
The term “distal” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, spaced relatively far from a point of reference, such as an origin or a point of attachment. For example, in some embodiments of a sensing membrane that covers an electrochemically reactive surface, a resistance domain is located more distal to the electrochemically reactive surfaces than the enzyme domain.
The term “substantially” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, being largely but not necessarily wholly that which is specified.
The term “microprocessor,” as used herein, is a broad term and is used in its ordinary sense, including, without limitation, 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 term “ROM,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, read-only memory, which is a type of data storage device manufactured with fixed contents. ROM is broad enough to include EEPROM, for example, which is electrically erasable programmable read-only memory (ROM).
The term “RAM,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, a data storage device for which the order of access to different locations does not affect the speed of access. RAM is broad enough to include SRAM, for example, which is static random access memory that retains data bits in its memory as long as power is being supplied.
The term “A/D Converter,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, hardware and/or software that converts analog electrical signals into corresponding digital signals.
The term “RF transceiver,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, a radio frequency transmitter and/or receiver for transmitting and/or receiving signals.
The terms “raw data stream” and “data stream,” as used herein, are broad terms and are used in their ordinary sense, including, but not limited to, an analog or digital signal directly related to the analyte concentration measured by the analyte sensor. In one example, the raw data stream is digital data in “counts” converted by an A/D converter from an analog signal (for example, voltage or amps) representative of an analyte concentration. The terms broadly encompass a plurality of time spaced data points from a substantially continuous analyte sensor, which comprises individual measurements taken at time intervals ranging from fractions of a second up to, for example, 1, 2, or 5 minutes or longer.
The term “counts,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, a unit of measurement of a digital signal. In one example, a raw data stream measured in counts is directly related to a voltage (for example, converted by an A/D converter), which is directly related to current from a working electrode.
The term “electronic circuitry,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, the components (for example, hardware and/or software) of a device configured to process data. In the case of an analyte sensor, the data includes biological information obtained by a sensor regarding the concentration of the analyte in a biological fluid. U.S. Pat. Nos. 4,757,022, 5,497,772 and 4,787,398, which are hereby incorporated by reference in their entirety, describe suitable electronic circuits that can be utilized with devices of certain embodiments.
The term “potentiostat,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, an electrical system that controls the potential between the working and reference electrodes of a three-electrode cell at a preset value. The potentiostat forces whatever current is necessary to flow between the working and counter electrodes to keep the desired potential, as long as the needed cell voltage and current do not exceed the compliance limits of the potentiostat.
The terms “operably connected” and “operably linked,” as used herein, are broad terms and are used in their ordinary sense, including, but not limited to, one or more components being linked to another component(s) in a manner that allows transmission of signals between the components. For example, one or more electrodes can be used to detect the amount of glucose in a sample and convert that information into a signal; the signal can then be transmitted to an electronic circuit. In this case, the electrode is “operably linked” to the electronic circuit. These terms are broad enough to include wired and wireless connectivity.
The term “algorithmically smoothed,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, modification of a set of data to make it smoother and more continuous and remove or diminish outlying points, for example, by performing a moving average of the raw data stream.
The term “algorithm,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, the computational processes (for example, programs) involved in transforming information from one state to another, for example using computer processing.
The term “regression,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, finding a line in which a set of data has a minimal measurement (for example, deviation) from that line. Regression can be linear, non-linear, first order, second order, and so forth. One example of regression is least squares regression.
The terms “recursive filter” and “auto-regressive algorithm,” as used herein, are broad terms and are used in their ordinary sense, including, but not limited to, an equation in which previous averages are part of the next filtered output. More particularly, the generation of a series of observations whereby the value of each observation is partly dependent on the values of those that have immediately preceded it. One example is a regression structure in which lagged response values assume the role of the independent variables.
The terms “velocity” and “rate of change,” as used herein, are broad terms and are used in their ordinary sense, including, but not limited to, time rate of change; the amount of change divided by the time required for the change. In one embodiment, these terms refer to the rate of increase or decrease in an analyte for a certain time period.
The term “acceleration” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, the rate of change of velocity with respect to time. This term is broad enough to include deceleration.
The term “clinical risk,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, an identified danger or potential risk to the health of a patient based on a measured or estimated analyte concentration, its rate of change, and/or its acceleration.
The term “clinically acceptable,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, an analyte concentration, rate of change, and/or acceleration associated with that measured analyte that is considered to be safe for a patient.
The term “time period,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, an amount of time including a single point in time and a path (for example, range of time) that extends from a first point in time to a second point in time.
The term “measured analyte values,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, an analyte value or set of analyte values for a time period for which analyte data has been measured by an analyte sensor. The term is broad enough to include data from the analyte sensor before or after data processing in the sensor and/or receiver (for example, data smoothing, calibration, or the like).
The term “alarm,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, audible, visual, or tactile signal that are triggered in response to detection of clinical risk to a patient. In one embodiment, hyperglycemic and hypoglycemic alarms are triggered when present or future clinical danger is assessed based on continuous analyte data.
The term “computer,” as used herein, is broad term and is used in its ordinary sense, including, but not limited to, machine that can be programmed to manipulate data.
The term “modem,” as used herein, is a broad term and is used in its ordinary sense, including, but not limited to, an electronic device for converting between serial data from a computer and an audio signal suitable for transmission over a telecommunications connection to another modem.
Overview
Accordingly, a receiver 14 is provided that receives and processes the raw data stream, including calibrating, validating, and displaying meaningful glucose values to a patient, such as described in more detail below. A medicament delivery device 16 is further provided as a part of the integrated system 10. In some embodiments, the medicament delivery device 16 is a manual delivery device, for example a syringe, inhaler, or transdermal patch, which is manually integrated with the receiver 14. In some embodiments, the medicament delivery device 16 is a semi-automated delivery device, for example a pen or jet-type injector, an inhaler, a spray, or pump, which provides a semi-automated integration with the receiver 14. In some embodiments, the medicament delivery device 16 is an automated delivery device, for example a transcutaneous or implantable pump system, which provides an automated integration with the receiver 14. In some embodiments, an optional single point glucose monitor 18 is further provided as a part of the integrated system 10, for example a self-monitoring blood glucose meter (SMBG), non-invasive glucose meter, or the like.
Conventionally, each of these devices separately provides valuable information and or services to diabetic patients. Thus, a typical diabetic patient has numerous individual devices, which they track and consider separately. In some cases, the amount of information provided by these individual devices may require complex understanding of the nuances and implications of each device, for example types and amounts of insulin to deliver. Typically, each individual device is a silo of information that functions as well as the data provided therein, therefore when the devices are able to communicate with each other, enhanced functionality and safety may be realized. For example, when a continuous glucose monitor functions alone (for example, without data other than that which was gathered by the device), sudden changes in glucose level are tracked, but may not be fully understood, predicted, preempted, or otherwise considered in the processing of the sensor data; however, if the continuous glucose sensor were provided with information about time, amount, and type of insulin injections, calories consumed, time or day, meal time, or like, more meaningful, accurate and useful glucose estimation, prediction, and other such processing can be provided, such as described in more detail herein. By integrating these devices, the information from each component can be leveraged to increase the intelligence, benefit provided, convenience, safety, and functionality of the continuous glucose sensor and other integrated components. Therefore, it would be advantageous to provide a device that aids the diabetic patient in integrating these individual devices in the treatment of his/her disease.
Glucose Sensor
The body 20 is preferably formed from epoxy molded around the sensor electronics, however the body may be formed from a variety of materials, including metals, ceramics, plastics, or composites thereof. Co-pending U.S. patent application Ser. No. 10/646,333, entitled, “Optimized Sensor Geometry for an Implantable Glucose Sensor” discloses suitable configurations suitable for the body 20, and is incorporated by reference in its entirety.
In one embodiment, the sensing region 22 comprises three electrodes including a platinum working electrode, a platinum counter electrode, and a silver/silver chloride reference electrode, for example. However a variety of electrode materials and configurations may be used with the implantable glucose sensor of the preferred embodiments. 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 and the electrodes. In one 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 (
In some embodiments, the sensing membrane includes an enzyme, for example, glucose oxidase, and covers the electrolyte phase. In one embodiment, the sensing membrane generally includes a resistance domain most distal from the electrochemically reactive surfaces, an enzyme domain less distal from the electrochemically reactive surfaces than the resistance domain, and an electrolyte domain adjacent to the electrochemically reactive surfaces. 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. Co-pending U.S. patent application Ser. No. 09/916,711, entitled, “SENSOR HEAD FOR USE WITH IMPLANTABLE DEVICES,” which is incorporated herein by reference in its entirety, describes membranes that can be used in some embodiments of the sensing membrane. It is noted that in some embodiments, the sensing membrane may additionally include an interference domain that blocks some interfering species; such as described in the above-cited co-pending patent application. Co-pending U.S. patent application Ser. No. 10/695,636, entitled, “SILICONE COMPOSITION FOR BIOCOMPATIBLE MEMBRANE” also describes membranes that may be used for the sensing membrane of the preferred embodiments, and is incorporated herein by reference in its entirety.
Preferably, the biointerface membrane supports tissue ingrowth, serves to interfere with the formation of a barrier cell layer, and protects the sensitive regions of the device from host inflammatory response. In one embodiment, the biointerface membrane 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. Copending U.S. patent application Ser. No. 09/916,386, entitled, “MEMBRANE FOR USE WITH IMPLANTABLE DEVICES,” U.S. patent application Ser. No. 10/647,065, entitled, “POROUS MEMBRANES FOR USE WITH IMPLANTABLE DEVICES,” and U.S. Provisional Patent Application 60/544,722, filed Feb. 12, 2004 entitled, “BIOINTERFACE WITH INTEGRATED MACRO- AND MICRO-ARCHITECTURE,” describe biointerface membranes that may be used in conjunction with the preferred embodiments, and are incorporated herein by reference in their entirety. It is noted that the preferred embodiments may be used with a short term (for example, 1 to 7 day sensor), in which case a biointerface membrane may not be required. It is noted that the biointerface membranes described herein provide a continuous glucose sensor that has a useable life of greater than about one week, greater than about one month, greater than about three months, or greater than about one year, herein after referred to as “long-term.”
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.
A microprocessor 28 is the central control unit that houses ROM 30 and RAM 32, and controls the processing of the sensor electronics. It is noted that certain alternative embodiments can utilize a computer system other than a microprocessor to process data as described herein. In some alternative embodiments, an application-specific integrated circuit (ASIC) can be used for some or all the sensor's central processing as is appreciated by one skilled in the art. The ROM 30 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 described in copending U.S. patent application entitled, “SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM,” filed Aug. 22, 2003). The RAM 32 can be used for the system's cache memory, for example for temporarily storing recent sensor data. In some alternative embodiments, memory storage components comparable to ROM 30 and RAM 32 may be used instead of or in addition to the preferred hardware, such as dynamic RAM, static-RAM, non-static RAM, EEPROM, rewritable ROMs, flash memory, or the like.
A battery 34 is operably connected to the microprocessor 28 and provides the necessary power for the sensor 12. 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. In some embodiments, a plurality of batteries can be used to power the system. In yet other embodiments, the receiver can be transcutaneously powered via an inductive coupling, for example. A Quartz Crystal 36 is operably connected to the microprocessor 28 and maintains system time for the computer system as a whole.
An RF Transceiver 38 is operably connected to the microprocessor 28 and transmits the sensor data from the sensor 12 to a receiver within a wireless transmission 40 via antenna 42. Although an RF transceiver is shown here, some other embodiments can include a wired rather than wireless connection to the receiver. A second quartz crystal 44 provides the system time for synchronizing the data transmissions from the RF transceiver. It is noted that the transceiver 38 can be substituted with a transmitter in other embodiments. In some alternative embodiments other mechanisms such as optical, infrared radiation (IR), ultrasonic, or the like may be used to transmit and/or receive data.
In one alternative embodiment, the continuous glucose sensor comprises a transcutaneous sensor such as described in U.S. Pat. No. 6,565,509 to Say et al. In another alternative embodiment, the continuous glucose sensor comprises a subcutaneous sensor such as described with reference to U.S. Pat. No. 6,579,690 to Bonnecaze et al. and U.S. Pat. No. 6,484,046 to Say et al. In another alternative embodiment, the continuous glucose sensor comprises a refillable subcutaneous sensor such as described with reference to U.S. Pat. No. 6,512,939 to Colvin et al. In another alternative embodiment, the continuous glucose sensor comprises an intravascular sensor such as described with reference to U.S. Pat. No. 6,477,395 to Schulman et al. In another alternative embodiment, the continuous glucose sensor comprises an intravascular sensor such as described with reference to U.S. Pat. No. 6,424,847 to Mastrototaro et al. All of the above patents are incorporated in their entirety herein by reference. In general, it should be understood that the disclosed embodiments are applicable to a variety of continuous glucose sensor configurations.
Receiver
The preferred embodiments provide an integrated system, which includes a receiver 14 that receives and processes the raw data stream from the continuous glucose sensor 12. The receiver may perform all or some of the following operations: a calibration, converting sensor data, updating the calibration, evaluating received reference and sensor data, evaluating the calibration for the analyte sensor, validating received reference and sensor data, displaying a meaningful glucose value to a user, calculating therapy recommendations, validating recommended therapy, adaptive programming for learning individual metabolic patterns, and prediction of glucose values, for example. Some complementary systems and methods associated with the receiver are described in more detail with reference to co-pending U.S. patent application Ser. No. 10/633,367, entitled, “SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA,” which is incorporated herein by reference in its entirety.
In some embodiments, the receiver 14 is a PDA- or pager-sized housing 46, for example, and comprises a user interface 48 that has a plurality of buttons 50 and a liquid crystal display (LCD) screen, which may include a backlight. In some embodiments, the receiver may take other forms, for example a computer, server, or other such device capable of receiving and processing the data such as described herein. In some embodiments the user interface may also include a keyboard, a speaker, and a vibrator such as described with reference to
In some embodiments, the receiver 14 is integrally formed with at least one of the medicament delivery device 16, and single point glucose monitor 18. In some embodiments, the receiver 14, medicament delivery device 16 and/or single point glucose monitor 18 are detachably connected, so that one or more of the components can be individually detached and attached at the user's convenience. In some embodiments, the receiver 14, medicament delivery device 16, and/or single point glucose monitor 18 are separate from, detachably connectable to, or integral with each other; and one or more of the components are operably connected through a wired or wireless connection, allowing data transfer and thus integration between the components. In some embodiments, one or more of the components are operably linked as described above, while another one or more components (for example, the syringe or patch) are provided as a physical part of the system for convenience to the user and as a reminder to enter data for manual integration of the component with the system. Some exemplary embodiments are described with reference to
Medicament Delivery Device
The preferred embodiments provide an integrated system 10, which includes a medicament delivery device 16 for administering a medicament to the patient 8. The integrated medicament delivery device can be designed for bolus injection, continuous injection, inhalation, transdermal absorption, other method for administering medicament, or any combinations thereof. The term medicament includes any substance used in therapy for a patient using the system 10, for example, insulin, glucacon, or derivatives thereof. Published International Application WO 02/43566 describes glucose, glucagon, and vitamins A, C, or D that may be used with the preferred embodiments. U.S. Pat. Nos. 6,051,551 and 6,024,090 describe types of insulin suitable for inhalation that may be used with the preferred embodiments. U.S. Pat. No. 5,234,906, U.S. Pat. No. 6,319,893, and EP 760677 describe various derivatives of glucagon that may be used with the preferred embodiments. U.S. Pat. No. 6,653,332 describes a combination therapy that may be used with the preferred embodiments. U.S. Pat. No. 6,471,689 and WO 81/01794 describe insulin useful for delivery pumps that may be used with the preferred embodiments. U.S. Pat. No. 5,226,895 describes a method of providing more than one type of insulin that may be used with the preferred embodiments. All of the above references are incorporated herein by reference in their entirety and may be useful as the medicament(s) in the preferred embodiments.
Manual Integration
In some embodiments, the medicament delivery device 16 is a manual delivery device, for example a syringe, inhaler, transdermal patch, cell transplantation device, and/or manual pump for manual integration with the receiver. Manual integration includes medicament delivery devices wherein a user (for example, patient or doctor) manually selects the amount, type, and/or time of delivery. In some embodiments, the medicament delivery device 16 is any syringe suitable for injecting a medicament, as is appreciated by one skilled in the art. One example of a syringe suitable for the medicament delivery device of the preferred embodiments is described in U.S. Pat. No. 5,137,511, which is incorporated herein by reference in its entirety.
Referring now to the integration between the syringe and the receiver, it is noted that the receiver can be programmed with information about the time, amount, and types of medicament that may be administered with the syringe, for example. In some embodiments during set-up of the system, the patient and/or doctor manually enters information about the amounts and types of medicament available via the syringe of the integrated system. In some alternative embodiments, manufacturer-provided data can be downloaded to the receiver so that the patient and/or doctor can select appropriate information from menus on the screen, for example, to provide easy and accurate data entry. Thus, by knowing the available medicaments, the receiver may be programmed to customize the patient's therapy recommendations considering available types and amounts of medicaments in combination with concentration, rate-of-change, and/or acceleration of the patient's glucose. While not wishing to be bound by theory, it is believed that by storing available medicament therapies, the receiver is able to customize medicament calculations and recommend appropriate therapy based glucose on trend information and the preferred types and the amounts of medicament available to the patient.
Subsequently in some embodiments, once the patient has administered a medicament (including via the syringe and or by other means), the amount, type, and/or time of medicament administration are input into the receiver by the patient. Similarly, the receiver may be programmed with standard medicaments and dosages for easy selection by the patient (for example, menus on the user interface). This information can be used by the receiver to increase the intelligence of the algorithms used in determining the glucose trends and patterns that may be useful in predicting and analyzing present, past, and future glucose trends, and in providing therapy recommendations, which will be described in more detail below. Additionally, by continuously monitoring the glucose concentration over time, the receiver provides valuable information about how a patient responds to a particular medicament, which information may be used by a doctor, patient, or by the algorithms within the receiver, to determine patterns and provide more personalized therapy recommendations. In other words, in some embodiments, the receiver includes programming that learns the patterns (for example, an individual's metabolic response to certain medicament deliveries and patient behavior) and to determine an optimum time, amount, and type of medicament to delivery in a variety of conditions (e.g., glucose concentration, rate-of-change, and acceleration). While not wishing to be bound by theory, it is believed that by continuously monitoring an individual's response to various medicaments, the patient's glucose levels can be more proactively treated, keeping the diabetic patient within safe glucose ranges substantially all the time.
In some embodiments, the receiver includes programming to predict glucose trends, such as described in U.S. provisional patent application 60/528,382, entitled, “SIGNAL PROCESSING FOR CONTINUOUS ANALYTE SENSORS”, which is incorporated herein by reference in its entirety. In some embodiments, the predictive algorithms consider the amount, type, and time of medicament delivery in predicting glucose values. For example, a predictive algorithm that predicts a glucose value or trend for the upcoming 15 to 20 minutes uses a mathematical algorithm (for example, regression, smoothing, or the like) such as described in the above-cited provisional patent application 60/528,382 to project a glucose value. However outside influences, including medicament delivery may cause this projection to be inaccurate. Therefore, some embodiments provide programming in the receiver that uses the medicament delivery information received from the delivery device 14, in addition to other mathematical equations, to more accurately predict glucose values in the future.
In some alternative embodiments, the medicament delivery device 16 includes one or more transdermal patches 58 suitable for administering medicaments as is appreciated by one skilled in the art. WO 02/43566 describes one such transdermal patch, which may be used in the preferred embodiments. Although the above-cited reference and description associated with the
The integration of the patches 58 with the receiver 14 includes similar functionality and provides similar advantages as described with reference to other manual integrations including manual medicament delivery devices (for example, syringe and inhaler). However, a unique advantage may be seen in the integration of a continuous glucose sensor with a glucagon-type patch. Namely, a continuous glucose sensor, such as described in the preferred embodiments, provides more than single point glucose readings. In fact, because the continuous glucose sensor 12 knows the concentration, rate-of-change, acceleration, the amount of insulin administered (in some embodiments), and/or individual patterns associated with a patient's glucose trends (learned over time as described in more detail elsewhere herein), the use of the glucagon patch can be iteratively optimized (inputting its usage into the receiver and monitoring the individual's metabolic response) to proactively preempt hypoglycemic events and maintain a more controlled range of glucose values. This may be particularly advantageous for nighttime hypoglycemia by enabling the diabetic patient (and his/her caretakers) to improve overall nighttime diabetic health. While not wishing to be bound by theory, the integration of the continuous glucose sensor and transdermal glucagon-type patch can provide diabetic patients with a long-term solution to reduce or avoid hypoglycemic events.
In some embodiments, the holder 58 is detachably connectable to the receiver 14 (for example on the side opposite the LCD), which enables convenient availability of the patch to the patient when the receiver indicates that a medicament (for example, glucose or glucagon) is recommended. It is further noted that although this holder is shown without another medicament delivery device 16 in the illustrations of
Manual Integration of delivery devices with the continuous glucose sensor 12 of the preferred embodiments may additionally be advantageous because the continuous device of the preferred embodiments is able to track glucose levels long-term (for example weeks to months) and adaptively improve therapy decisions based on the patients response over time.
In some alternative embodiments, the medicament delivery device 16 includes an inhaler or spray device suitable for administering a medicament into the circulatory system, as is appreciated by one skilled in the art. Some examples of inhalers suitable for use with the preferred embodiments include U.S. Pat. Nos. 6,167,880, 6,051,551, 6,024,090, which are incorporated herein by reference in their entirety. In some embodiments, the inhaler or spray device is considered a manual medicament delivery device, such as described with reference to
In some embodiments, the inhaler or spray device is integrally housed within, detachably connected to, or otherwise physically associated with (for example, in a kit) to the receiver. The functionality and advantages for the integrated inhaler or spray device are similar to those described with reference to the syringe and/or patch integration, above. It is noted that the inhaler or spray device may be provided in combination with any other of the medicament delivery devices of the preferred embodiments, for example, a fast-acting insulin inhaler and a slow acting insulin pump may be advantageously integrated into the system of the preferred embodiments and utilized at the appropriate time as is appreciated by one skilled in the art. In some embodiments, wherein the inhaler or spray device includes a semi-automated integration with the receiver, the inhaler or spray device may by physically integrated with receiver such as described above and also operably connected to the receiver, for example via a wired (for example, via electrical contacts) or wireless (for example, via RF) connection.
In one alternative embodiment, a manual medicament delivery pump is implanted such as described in U.S. Pat. No. 6,283,944, which is incorporated herein by reference in its entirety. In this alternative embodiment, the patient-controlled implantable pump allows the patient to press on the device (through the skin) to administer a bolus injection of a medicament when needed. It is believed that providing glucagon or other medicament for treating hypoglycemia within this device will provide the ease and convenience that can be easily released by the patient and/or his or her caretaker when the continuous glucose sensor indicates severe hypoglycemia, for example. In some alternative embodiments, the manual implantable pump is filled with insulin, or other medicament for treating hyperglycemia. In either case, the manual pump and continuous glucose sensor will benefit from manual integrations described in more detail above.
In another alternative embodiment, a cell transplantation device, such as described in U.S. Pat. Nos. 6,015,572, 5,964,745, and 6,083,523, which are incorporated herein by reference in their entirety, is manually integrated with the continuous sensor of the preferred embodiments. In this alternative embodiment, a patient would be implanted with beta islet cells, which provide insulin secretion responsive to glucose levels in the body. The receiver associated with the implantable glucose sensor can be programmed with information about the cell transplantation (for example, time, amount, type, etc). In this way, the long-term continuous glucose sensor may be used to monitor the body's response to the beta islet cells. This may be particularly advantageous when a patient has been using the continuous glucose sensor for some amount of time prior to the cell transplantation, and the change in the individual's metabolic patterns associated with the transplantation of the cells can be monitored and quantified. Because of the long-term continuous nature of the glucose sensor of the preferred embodiments, the long-term continuous effects of the cell transplantation can be consistently and reliably monitored. This integration may be advantageous to monitor any person's response to cell transplantation before and/or after the implantation of the cells, which may be helpful in providing data to justify the implantation of islet cells in the treatment of diabetes.
It is noted that any of the manual medicament delivery devices can be provided with an RF ID tag or other communication-type device, which allows semi-automated integration with that manual delivery device, such as described in more detail below.
Semi-Automated Integration
Semi-automated integration of medicament delivery devices 16 in the preferred embodiments includes any integration wherein an operable connection between the integrated components aids the user (for example, patient or doctor) in selecting, inputting, or calculating the amount, type, or time of medicament delivery of glucose values, for example, by transmitting data to another component and thereby reducing the amount of user input required. In the preferred embodiments, semi-automated may also refer to a fully automated device (for example, one that does not require user interaction), wherein the fully automated device requires a validation or other user interaction, for example to validate or confirm medicament delivery amounts. In some embodiments, the semi-automated medicament delivery device is an inhaler or spray device, a pen or jet-type injector, or a transdermal or implantable pump.
Medicament delivery pen 60 includes at least a microprocessor and a wired or wireless connection to the receiver 14, which are described in more detail with reference to
Subsequently, the pen 60 includes programming to send information regarding the amount, type, and time of medicament delivery to the receiver 14 for processing. The receiver 14 can use this information received from the pen 60, in combination with the continuous glucose data obtained from the sensor, to monitor and determine the patient's glucose patterns to measure their response to each medicament delivery. Knowing the patient's individual response to each type and amount of medicament delivery may be useful in adjusting or optimizing the patient's therapy. It is noted that individual metabolic profiles (for example, insulin sensitivity) are variable from patient to patient. While not wishing to be bound by theory, it is believed that once the receiver has learned (for example, monitored and determined) the individual's metabolic patterns, including glucose trends and associated medicament deliveries, the receiver can be programmed to adjust and optimize the therapy recommendations for the patient's individual physiology to maintain their glucose levels within a desired target range. In alternative embodiments, the pen 60 may be manually integrated with the receiver.
In some embodiments, the receiver includes algorithms that use parameters provided by the continuous glucose sensor, such as glucose concentration, rate-of-change of the glucose concentration, and acceleration of the glucose concentration to more particularly determine the type, amount, and time of medicament administration. In fact, all of the functionality of the above-described manual and semi-automated integrated systems, including therapy recommendations, adaptive programming for learning individual metabolic patterns, and prediction of glucose values, can be applied to the semi-automated integrated system 10, such as described herein. However, the semi-automated integrated sensing and delivery system additionally provides convenience by automation (for example, data transfer through operable connection) and reduced opportunity for human error than may be experienced with the manual integration.
In some alternative embodiments, the semi-automated integration provides programming that requires at least one of the receiver 14, single point glucose monitor 18, and medicament delivery device 16 to be validated or confirmed by another of the components to provide a fail safe accuracy check; in these embodiments, the validation includes algorithms programmed into any one or more of the components. In some alternative embodiments, the semi-automated integration provides programming that requires at least one of the receiver 14 and medicament delivery device 16 to be validated or confirmed by an a human (for example, confirm the amount and/or type of medicament). In these embodiments, validation provides a means by which the receiver can be used adjunctively, when the patient or doctor would like to have more control over the patient's therapy decisions, for example. See
Although the above description of semi-automated medicament delivery is mostly directed to an integrated delivery pen, the same or similar integration can be accomplished between a semi-automated inhaler or spray device, and/or a semi-automated transdermal or implantable pump device. Additionally, any combination of the above semi-automated medicament delivery devices may be combined with other manual and/or automated medicament delivery device within the scope of the preferred embodiments as is appreciated by one skilled in the art.
Automated Integration
Automated integration medicament delivery devices 16 in the preferred embodiments are any delivery devices wherein an operable connection between the integrated components provides for full control of the system without required user interaction. Transdermal and implantable pumps are examples of medicament delivery devices that may be used with the preferred embodiments of the integrated system 10 to provide automated control of the medicament delivery device 16 and continuous glucose sensor 12. Some examples of medicament pumps that may be used with the preferred embodiments include, U.S. Pat. No. 6,471,689, WO 81/01794, and EP 1281351, both of which are incorporated herein by reference in their entirety.
The receiver 14 receives, processes, and displays data associated with the continuous glucose monitor 12, data associated with the pump 70, and data manually entered by the patient 8. In some embodiments, the receiver includes algorithms that use parameters provided by the continuous glucose sensor, such as glucose concentration, rate-of-change of the glucose concentration, and acceleration of the glucose concentration to determine the type, amount, and time of medicament administration. In fact, all of the functionality of the above-described manual and semi-automated integrated systems, including therapy recommendations, confirmation or validation of medicament delivery, adaptive programming for learning individual metabolic patterns, and prediction of glucose values, can be applied to the fully automated integrated system 10, such as described herein with reference to
In some embodiments of the automated integrated system 10, a fail-safe mode is provided, wherein the system is programmed with conditions whereby when anomalies or potentially clinically risky situations arise, for example when a reference glucose value (for example, from an SMBG) indicates a discrepancy from the continuous sensor that could cause risk to the patient if incorrect therapy is administered. Another example of a situation that may benefit from a validation includes when a glucose values are showing a trend in a first direction that shows a possibility of “turn around,” namely, the patient may be able to reverse the trend with a particular behavior within a few minutes to an hour, for example. In such situations, the automated system may be programmed to revert to a semi-automated system requiring user validation or other user interaction to validate the therapy in view of the situation.
It is noted that in the illustrated embodiment, only one receiver 14 is shown, which houses the electronics for both the medicament delivery pump 70 and the continuous sensor 12. Although it is possible to house the electronics in two different receiver housings, providing one integrated housing 14 increases patient convenience and minimizes confusion or errors. In some embodiments, the sensor receiver electronics and pump electronics are separate, but integrated. In some alternative embodiments, the sensor and pump share the same electronics.
Additionally, the integrated receiver for the sensor and pump, can be further integrated with any combination with the above-described integrated medicament delivery devices, including syringe, patch, inhaler, and pen, as is appreciated by one skilled in the art.
Single Point Glucose Monitor
In the illustrated embodiments (
In the illustrated embodiments, the single point glucose monitor 18, such as described in the above-cited provisional patent application, 60/523,840, includes a body 62 that houses a sensing region 64, which includes a sensing membrane located within a port. A shuttle mechanism 66 may be provided that preferably feeds a single-use disposable bioprotective film that can be placed over the sensing region 64 to provide protection from contamination. The sensing region includes electrodes, the top ends of which are in contact with an electrolyte phase (not shown), which is a free-flowing fluid phase disposed between the sensing membrane and the electrodes. The sensing region measures glucose in the biological sample in a manner such as described in more detail above, with reference the continuous glucose sensor and/or U.S. Pat. Nos. 4,994,167 and 4,757,022. The similarity of the measurement technologies used for the continuous glucose sensor and the single point glucose sensor provides an internal control that creates increased reliability by nature of consistency and decreased error potential that can otherwise be increased due to combining dissimilar measurement techniques. Additionally, the disclosed membrane system is known to provide longevity, repeatability, and cost effectiveness, for example as compared to single use strips, or the like. However, other single point glucose monitors may be used with the preferred embodiments.
In one alternative embodiment, the single point glucose monitor comprises an integrated lancing and measurement device such as described in U.S. Pat. No. 6,607,658 to Heller et al. In another alternative embodiment, the single point glucose monitor comprises a near infrared device such as described in U.S. Pat. No. 5,068,536 to Rosenthal et al. In another alternative embodiment, the single point glucose monitor comprises a reflectance reading apparatus such as described in U.S. Pat. No. 5,426,032 to Phillips et al. In another alternative embodiment, the single point glucose monitor comprises a spectroscopic transflectance device such as described in U.S. Pat. No. 6,309,884 to Cooper et al. All of the above patents and patent applications are incorporated in their entirety herein by reference.
In some embodiments, the single point glucose meter further comprises a user interface that includes a display 72 and a button 74; however, some embodiments utilize the display 48 and buttons 50 of the receiver 14 rather than providing a separate user interface for the monitor 18. In some embodiments the single point glucose monitor measured glucose concentration, prompts, and/or messages can be displayed on the user interface 48 or 72 to guide the user through the calibration and sample measurement procedures, or the like. In addition, prompts can be displayed to inform the user about necessary maintenance procedures, such as “Replace Sensor” or “Replace Battery.” The button 74 preferably initiates the operation and calibration sequences. The button can be used to refresh, calibrate, or otherwise interface with the single point glucose monitor 18 as is appreciated by one skilled in the art.
Integrated Electronics
A quartz crystal 76 is operably connected to an RF transceiver 78 that together function to receive and synchronize data streams via an antenna 80 (for example, transmission 40 from the RF transceiver 44 shown in
The microprocessor 82 is the central control unit that provides the processing for the receiver, such as storing data, analyzing continuous glucose sensor data stream, analyzing single point glucose values, accuracy checking, checking clinical acceptability, calibrating sensor data, downloading data, recommending therapy instructions, calculating medicament delivery amount, type and time, learning individual metabolic patterns, and controlling the user interface by providing prompts, messages, warnings and alarms, or the like. The ROM 84 is operably connected to the microprocessor 82 and provides semi-permanent storage of data, storing data such as receiver ID and programming to process data streams (for example, programming for performing calibration and other algorithms described elsewhere herein). RAM 88 is used for the system's cache memory and is helpful in data processing. For example, the RAM 88 stores information from the continuous glucose sensor, delivery device, and/or single point glucose monitor for later recall by the user or a doctor; a user or doctor can transcribe the stored information at a later time to determine compliance with the medical regimen or evaluation of glucose response to medication administration (for example, this can be accomplished by downloading the information through the pc com port 90). In addition, the RAM 88 may also store updated program instructions and/or patient specific information.
In some embodiments, the microprocessor 82 monitors the continuous glucose sensor data stream 40 to determine a preferable time for capturing glucose concentration values using the single point glucose monitor electronics 116 for calibration of the continuous sensor data stream. For example, when sensor glucose data (for example, observed from the data stream) changes too rapidly, a single point glucose monitor reading may not be sufficiently reliable for calibration during unstable glucose changes in the host; in contrast, when sensor glucose data are relatively stable (for example, relatively low rate of change), a single point glucose monitor reading can be taken for a reliable calibration. In some additional embodiments, the microprocessor can prompt the user via the user interface to obtain a single point glucose value for calibration at predetermined intervals. In some additional embodiments, the user interface can prompt the user to obtain a single point glucose monitor value for calibration based upon certain events, such as meals, exercise, large excursions in glucose levels, faulty or interrupted data readings, or the like. In some embodiments, certain acceptability parameters can be set for reference values received from the single point glucose monitor. For example, in one embodiment, the receiver only accepts reference glucose data between about 40 and about 400 mg/dL.
In some embodiments, the microprocessor 82 monitors the continuous glucose sensor data stream to determine a preferable time for medicament delivery, including type, amount, and time. In some embodiments, the microprocessor is programmed to detect impending clinical risk and may request data input, a reference glucose value from the single point glucose monitor, or the like, in order to confirm a therapy recommendation. In some embodiments, the microprocessor is programmed to process continuous glucose data and medicament therapies to adaptive adjust to an individual's metabolic patterns. In some embodiments, the microprocessor is programmed to project glucose trends based on data from the integrated system (for example, medicament delivery information, user input, or the like). In some embodiments, the microprocessor is programmed to calibrate the continuous glucose sensor based on the integrated single point glucose monitor. Numerous other programming may be incorporated into the microprocessor, as is appreciated by one skilled in the art, as is described in cited patents and patent applications here, and as is described with reference to flowcharts of
It is noted that one advantage of integrated system of the preferred embodiments can be seen in the time stamp of the sensor glucose data, medicament delivery data, and reference glucose data. Namely, typical implementations of the continuous glucose sensor 12, wherein the medicament delivery 16 and/or single point glucose monitor 18 is not integral with the receiver 14, the reference glucose data or medicament delivery data can be obtained at a time that is different from the time that the data is input into the receiver 14. Thus, the user may not accurately input the “time stamp” of the delivery or (for example, the time or obtaining reference glucose value or administering the medicament) at the time of reference data input into the receiver. Therefore, the accuracy of the calibration of the continuous sensor, prediction of glucose values, therapy recommendations, and other processing is subject to human error (for example, due to inconsistencies in entering the actual time of the single point glucose test). In contrast, the preferred embodiments of the integrated system advantageously do no suffer from this potential inaccuracy when the time stamp is automatically and accurately obtained at the time of the event. Additionally, the processes of obtaining reference data and administering the medicament may be simplified and made convenient using the integrated receiver because of fewer loose parts (for example, cable, test strips, etc.) and less required manual data entry.
A battery 92 is operably connected to the microprocessor 82 and provides power for the receiver. In one embodiment, the battery is a standard AAA alkaline battery, however any appropriately sized and powered battery can be used. In some embodiments, a plurality of batteries can be used to power the system. In some embodiments, a power port (not shown) is provided permit recharging of rechargeable batteries. A quartz crystal 94 is operably connected to the microprocessor 168 and maintains system time for the computer system as a whole.
A PC communication (com) port 90 may be provided to enable communication with systems, for example, a serial communications port, allows for communicating with another computer system (for example, PC, PDA, server, or the like). In one exemplary embodiment, the receiver is able to download historical data to a physician's PC for retrospective analysis by the physician. The PC communication port 90 can also be used to interface with other medical devices, for example pacemakers, implanted analyte sensor patches, infusion devices, telemetry devices, or the like.
A user interface 96 comprises a keyboard 98, speaker 100, vibrator 102, backlight 104, liquid crystal display (LCD) 106, and/or one or more buttons 108. The components that comprise the user interface 96 provide controls to interact with the user. The keyboard 98 can allow, for example, input of user information about himself/herself, such as mealtime, exercise, insulin administration, and reference glucose values. The speaker 100 can provide, for example, audible signals or alerts for conditions such as present and/or predicted hyper- and hypoglycemic conditions. The vibrator 102 can provide, for example, tactile signals or alerts for reasons such as described with reference to the speaker, above. The backlight 104 can be provided, for example, to aid the user in reading the LCD in low light conditions. The LCD 106 can be provided, for example, to provide the user with visual data output. In some embodiments, the LCD is a touch-activated screen. The buttons 108 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.
The user interface 96, which is operably connected to the microprocessor 82 serves to provide data input and output for both the continuous glucose sensor, delivery mechanism, and/or for the single point glucose monitor.
In some embodiments, prompts or messages can be displayed on the user interface to guide the user through the initial calibration and sample measurement procedures for the single point glucose monitor. Additionally, prompts can be displayed to inform the user about necessary maintenance procedures, such as “Replace Sensing Membrane” or “Replace Battery.” Even more, the glucose concentration value measured from the single point glucose monitor can be individually displayed.
In some embodiments, prompts or messages can be displayed on the user interface to convey information to the user, such as malfunction, outlier values, missed data transmissions, or the like, for the continuous glucose sensor. Additionally, prompts can be displayed to guide the user through calibration of the continuous glucose sensor. Even more, calibrated sensor glucose data can be displayed, which is described in more detail with reference co-pending U.S. patent application Ser. No. 10/633,367 and U.S. provisional patent application 60/528,382, both of which are incorporated herein by reference in their entirety.
In some embodiments, prompts or messages about the medicament delivery device can be displayed on the user interface to inform or confirm to the user type, amount, and time of medicament delivery. In some embodiments, the user interface provides historical data and analytes pattern information about the medicament delivery, and the patient's metabolic response to that delivery, which may be useful to a patient or doctor in determining the level of effect of various medicaments.
Electronics 110 associated with the delivery device 16 (namely, the semi-automated and automated delivery devices) are operably connected to the microprocessor 82 and include a microprocessor 112 for processing data associated with the delivery device 16 and include at least a wired or wireless connection (for example, RF transceiver) 114 for transmission of data between the microprocessor 82 of the receiver 14 and the microprocessor 112 of the delivery device 16. Other electronics associated with any of the delivery devices cited herein, or other known delivery devices, may be implemented with the delivery device electronics 110 described herein, as is appreciated by one skilled in the art.
In some embodiments, the microprocessor 112 comprises programming for processing the delivery information in combination with the continuous sensor information. In some alternative embodiments, the microprocessor 82 comprises programming for processing the delivery information in combination with the continuous sensor information. In some embodiments, both microprocessors 82 and 112 mutually processor information related to each component.
In some embodiments, the medicament delivery device 16 further includes a user interface (not shown), which may include a display and/or buttons, for example. U.S. Pat. Nos. 6,192,891, 5,536,249, and 6,471,689 describe some examples of incorporation of a user interface into a medicament delivery device, as is appreciated by one skilled in the art.
Electronics 116 associated with the single point glucose monitor 18 are operably connected to the microprocessor 120 and include a potentiostat 118 in one embodiment that measures a current flow produced at the working electrode when a biological sample is placed on the sensing membrane, such as described above. The current is then converted into an analog signal by a current to voltage converter, which can be inverted, level-shifted, and sent to an A/D converter. The microprocessor can set the analog gain via its a control port (not shown). The A/D converter is preferably activated at one-second intervals. The microprocessor looks at the converter output with any number of pattern recognition algorithms known to those skilled in the art until a glucose peak is identified. A timer is then preferably activated for about 30 seconds at the end of which time the difference between the first and last electrode current values is calculated. This difference is then divided by the value stored in the memory during instrument calibration and is then multiplied by the calibration glucose concentration. The glucose value in milligram per deciliter, millimoles per liter, or the like, is then stored in the microprocessor, displayed on the user interface, used to calibrate of the glucose sensor data stream, downloaded, etc.
Programming and Processing (Draw Flow Diagrams)
Although computing and processing of data is increasingly complex and reliable, there are circumstances by which the therapy recommendations necessitate human intervention. Some examples include when a user is about to alter his/her metabolic state, for example due to behavior such as exercise, meal, pending manual medicament delivery, or the like. In such examples, the therapy recommendations determined by the programming may not have considered present or upcoming behavior, which may change the recommended therapy. Numerous such circumstances can be contrived, suffice it to say that a validation may be advantageous in order to ensure that therapy recommendations are appropriately administered.
At block 132, 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 may be in wired or wireless communication with the sensor. The sensor data point(s) may be raw or smoothed, such as described in co-pending U.S. patent application Ser. No. 10/648,849, entitled “SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM,” which is incorporated herein by reference in its entirety.
At block 134, a medicament calculation module, which is a part of a processor module, calculates a recommended medicament therapy based on the received sensor data. A variety of algorithms may be used to calculate a recommended therapy as is appreciated by one skilled in the art.
At block 136, a validation module, which is a part of the processor module, optionally validates the recommended therapy. The validation may include a request from the user, or from another component of the integrated system 10, for additional data to ensure safe and accurate medicament recommendation or delivery. In some embodiments, the validation requests and/or considers additional input, such as time of day, meals, sleep, calories, exercise, sickness, or the like. In some embodiments, the validation module is configured to request this information from the user. In some embodiments, the validation module is responsive to a user inputting such information.
In some embodiments, when the integrated system 10 is in fully automated mode, the validation module is triggered when a potential risk is evaluated. For example, when a clinically risky discrepancy is evaluated, when the acceleration of the glucose value is changing or is low (indicative of a significant change in glucose trend), when it is near a normal meal, exercise or sleep time, when a medicament delivery is expected based on an individual's dosing patterns, and/or a variety of other such situations, wherein outside influences (meal time, exercise, regular medicament delivery, or the like) may deem consideration in the therapy instructions. These conditions for triggering the validation module may be pre-programmed and/or may be learned over time, for example, as the processor module monitors and patterns an individual's behavior patterns.
In some embodiments, when the integrated system 10 is in semi-automated mode, the system may be programmed to request additional information from the user regarding outside influences unknown to the integrated system prior to validation. For example, exercise, food or medicament intake, rest, or the like may input into the receiver for incorporation into a parameter of the programming (algorithms) that processing the therapy recommendations.
At block 138, the receiver confirms and sends (for example, displays, transmits and/or delivers) the therapy recommendations. In manual integrations, the receiver may simply confirm and display the recommended therapy, for example. In semi-automated integrations, the receiver may confirm, transmit, and optionally delivery instructions to the delivery device regarding the recommended therapy, for example. In automated integrations the receiver may confirm and ensure the delivery of the recommended therapy, for example. It is noted that these examples are not meant to be limiting and there are a variety of methods by which the receiver may confirm, display, transmit, and/or deliver the recommended therapy within the scope of the preferred embodiments.
At block 142, a medicament data receiving module, which may be programmed within the receiver 14 and/or medicament delivery device 16, receives medicament delivery data, including time, amount, and/or type. In some embodiments, the user is prompted to input medicament delivery information into the user interface. In some embodiments, the medicament delivery device 16 sends the medicament delivery data to the medicament data-receiving module.
At block 144, 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 may be in wired or wireless communication with the sensor.
At block 146, the processor module, which may be programmed into the receiver 14 and/or the delivery device 16 is programmed to monitor the sensor data from the sensor data module 142 and medicament delivery from the medicament delivery module 144 to determine an individual's metabolic profile, including their response to various times, amounts, and/or types of medicaments. The processor module uses any pattern recognition-type algorithm as is appreciated by one skilled in the art to quantify the individual's metabolic profile.
At block 148, a medicament calculation module, which is a part of a processor module, calculates the recommended medicament based on the sensor glucose data, medicament delivery data, and/or individual's metabolic profile. In some embodiments, the recommended therapy is validated such as described with reference to
At block 150, the process of monitoring and evaluation a patient's metabolic profile is repeated with new medicament delivery data, wherein the processor monitors the sensor data with the associated medicament delivery data to determine the individual's metabolic response in order to adaptively adjust, if necessary, to newly determined metabolic profile or patterns. This process may be continuous throughout the life of the integrated system, may be initiated based on conditions met by the continuous glucose sensor, may be triggered by a patient or doctor, or may be provided during a start-up or learning phase.
While not wishing to be bound by theory, it is believed that by adaptively adjusting the medicament delivery based on an individual's metabolic profile, including response to medicaments, improved long-term patient care and overall health can be achieved.
At block 154, 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 may be in wired or wireless communication with the sensor.
At block 156, the medicament data receiving module, which may be programmed within the receiver 14 and/or medicament delivery device 16, receives medicament delivery data, including time, amount, and/or type.
At block 158, the processor module evaluates medicament delivery data with substantially time corresponding glucose sensor data to determine individual metabolic patterns associated with medicament delivery. “Substantially time corresponding data” refers to that time period during which the medicament is delivered and its period of release in the host.
At block 160, the processor module estimates glucose values responsive to individual metabolic patterns associated with the medicament delivery. Namely, the individual metabolic patterns associated with the medicament delivery are incorporated into the algorithms that estimate present and future glucose values, which are believed to increase accuracy of long-term glucose estimation.
In one exemplary implementation of the preferred embodiments, the continuous glucose sensor (and its receiver) comprises programming to track a patient during hypoglycemic or near-hypoglycemic conditions. In this implementation, the processor includes programming that sends instructions to administer a hypoglycemic treating medicament, such as glucagon, via an implantable pump or the like, when the glucose level and rate of change surpass a predetermined threshold (for example, 80 mg/dL and 2 mg/dL/min). In this situation, the sensor waits a predetermined amount of time (for example, 40 minutes), while monitoring the glucose level, rate of change of glucose, and/or acceleration/deceleration of glucose in the patient, wherein if the rate of change and/or acceleration shows a changing trend away from hypoglycemia (for example, decreased deceleration of glucose levels to non-hypoglycemia, then the patient need not be alarmed. In this way, the automated glucagon delivery device can proactively preempt hypoglycemic conditions without alerting or awaking the patient.
In another exemplary implementation of the preferred embodiments, a continuous glucose sensor is integrated with a continuous medicament delivery device (for example, an insulin pump) and a bolus medicament delivery device (for example, and insulin pen). In this embodiment, the integration takes exploits the benefits of automated and semi-automated device, for example, providing an automated integration with an infusion pump, while provide semi-automated integration with an insulin pen as necessary.
In yet another exemplary implementation of the preferred embodiments, a medicament delivery device is provided that includes reservoirs of both fast acting insulin and slow acting insulin. The medicament delivery device is integrated with the receiver as described elsewhere herein, however in this implementation, the receiver determines an amount of fast acting insulin and an amount of slow acting insulin, wherein the medicament delivery device is configured to mix slow- and fast-acting insulin in the amounts provided. In this way, the receiver and medicament delivery device can work together in a feedback loop to iteratively optimize amounts of slow and fast acting insulin for a variety of situations (for example, based on glucose level, rate of change, acceleration, and behavioral factors such as diet, exercise, time of day, etc.) adapted to the individual patient's metabolic profile.
In yet another exemplary implementation of the preferred embodiments, an integrated hypo- and hyper-glycemic treating system is provided. In this implementation, a manual-, semi-automated, or automated integration of an insulin delivery device is combined with a manual-, semi-automated, or automated integration of a glucose or glucagon delivery device. These devices are integrated with the receiver for the continuous glucose sensor in any manner described elsewhere herein. While not wishing to be bound by theory, it is believed that the combination of a continuous glucose sensor, integrated insulin device, and integrated glucose or glucagon device provides a simplified, comprehensive, user friendly, convenient, long-term and continuous method of monitoring, treating, and optimizing comprehensive care for diabetes.
Methods and devices that can be suitable for use in conjunction with aspects of the preferred embodiments are disclosed in copending applications including U.S. application Ser. No. 10/695,636 filed Oct. 28, 2003 and entitled, “SILICONE COMPOSITION FOR BIOCOMPATIBLE MEMBRANE”; U.S. patent application Ser. No. 10/648,849 entitled, “SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM,” filed Aug. 22, 2003; U.S. patent application Ser. No. 10/646,333 entitled, “OPTIMIZED SENSOR GEOMETRY FOR AN IMPLANTABLE GLUCOSE SENSOR,” filed Aug. 22, 2003; U.S. patent application Ser. No. 10/647,065 entitled, “POROUS MEMBRANES FOR USE WITH IMPLANTABLE DEVICES,” filed Aug. 22, 2003; U.S. patent application Ser. Nos. 10/633,367, 10/632,537, 10/633,404, and 10/633,329, each entitled, “SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA,” filed Aug. 1, 2003; U.S. patent application Ser. No. 09/916,386 filed Jul. 27, 2001 and entitled “MEMBRANE FOR USE WITH IMPLANTABLE DEVICES”; U.S. patent application Ser. No. 09/916,711 filed Jul. 27, 2001 and entitled “SENSING REGION FOR USE WITH IMPLANTABLE DEVICE”; U.S. patent application Ser. No. 09/447,227 filed Nov. 22, 1999 and entitled “DEVICE AND METHOD FOR DETERMINING ANALYTE LEVELS”; U.S. patent application Ser. No. 10/153,356 filed May 22, 2002 and entitled “TECHNIQUES TO IMPROVE POLYURETHANE MEMBRANES FOR IMPLANTABLE GLUCOSE SENSORS”; U.S. application Ser. No. 09/489,588 filed Jan. 21, 2000 and entitled “DEVICE AND METHOD FOR DETERMINING ANALYTE LEVELS”; U.S. patent application Ser. No. 09/636,369 filed Aug. 11, 2000 and entitled “SYSTEMS AND METHODS FOR REMOTE MONITORING AND MODULATION OF MEDICAL DEVICES”; and U.S. patent application Ser. No. 09/916,858 filed Jul. 27, 2001 and entitled “DEVICE AND METHOD FOR DETERMINING ANALYTE LEVELS,” as well as issued patents including U.S. Pat. No. 6,001,067 issued Dec. 14, 1999 and entitled “DEVICE AND METHOD FOR DETERMINING ANALYTE LEVELS”; U.S. Pat. No. 4,994,167 issued Feb. 19, 1991 and entitled “BIOLOGICAL FLUID MEASURING DEVICE”; and U.S. Pat. No. 4,757,022 filed Jul. 12, 1988 and entitled “BIOLOGICAL FLUID MEASURING DEVICE.” All of the above patents and patent applications are incorporated in their entirety herein by reference.
The above description provides several methods and materials of the 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 application or practice of the invention provided herein. Consequently, it is not intended that this invention be limited to the specific embodiments provided herein, but that it cover all modifications and alternatives coming within the true scope and spirit of the invention as embodied in the attached claims. All patents, applications, and other references cited herein are hereby incorporated by reference in their entirety.
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. 13/559,454 filed Jul. 26, 2012, which is a continuation of U.S. application Ser. No. 13/180,396 filed Jul. 11, 2011, now U.S. Pat. No. 8,460,231, which is a continuation of U.S. application Ser. No. 12/536,852 filed Aug. 6, 2009, now U.S. Pat. No. 7,976,492, which is a divisional of U.S. application Ser. No. 10/789,359 filed Feb. 26, 2004, now U.S. Pat. No. 7,591,801. Each of the aforementioned applications is incorporated by reference herein in its entirety, and each is hereby expressly made a part of this specification.
| Number | Name | Date | Kind |
|---|---|---|---|
| 2719797 | Rosenblatt et al. | Oct 1955 | A |
| 3210578 | Sherer | Oct 1965 | A |
| 3219533 | Mullins | Nov 1965 | A |
| 3381371 | Russell | May 1968 | A |
| 3826244 | Salcman et al. | Jul 1974 | A |
| 3837339 | Aisenberg | Sep 1974 | A |
| 3898984 | Mandel et al. | Aug 1975 | A |
| 3943918 | Lewis | Mar 1976 | A |
| 3957613 | Macur | May 1976 | A |
| 3979274 | Newman | Sep 1976 | A |
| 4052754 | Homsy | Oct 1977 | A |
| 4240438 | Updike et al. | Dec 1980 | A |
| 4245634 | Albisser et al. | Jan 1981 | A |
| 4253469 | Aslan | Mar 1981 | A |
| 4319578 | Enger | Mar 1982 | A |
| 4374013 | Enfors | Feb 1983 | A |
| 4403984 | Ash et al. | Sep 1983 | A |
| 4442841 | Uehara et al. | Apr 1984 | A |
| 4477314 | Richter et al. | Oct 1984 | A |
| 4494950 | Fischell | Jan 1985 | A |
| 4535786 | Kater | Aug 1985 | A |
| 4554927 | Fussell | Nov 1985 | A |
| 4583976 | Ferguson | Apr 1986 | A |
| 4655880 | Liu | Apr 1987 | A |
| 4703756 | Gough et al. | Nov 1987 | A |
| 4731726 | Allen | Mar 1988 | A |
| 4750496 | Reinhart et al. | Jun 1988 | A |
| 4757022 | Shults et al. | Jul 1988 | A |
| 4805624 | Yao et al. | Feb 1989 | A |
| 4805625 | Wyler | Feb 1989 | A |
| 4831070 | McInally et al. | May 1989 | A |
| 4832034 | Pizziconi | May 1989 | A |
| 4841974 | Gumbriecht et al. | Jun 1989 | A |
| 4852573 | Kennedy | Aug 1989 | A |
| 4858615 | Meinema | Aug 1989 | A |
| 4883057 | Broderick | Nov 1989 | A |
| 4890621 | Hakky | Jan 1990 | A |
| 4919141 | Zier et al. | Apr 1990 | A |
| 4927516 | Yamaguchi et al. | May 1990 | A |
| 4944299 | Silvian | Jul 1990 | A |
| 4950246 | Muller | Aug 1990 | A |
| 4953552 | DeMarzo | Sep 1990 | A |
| 4974929 | Curry | Dec 1990 | A |
| 4988341 | Columbus et al. | Jan 1991 | A |
| 4992794 | Brouwers | Jan 1991 | A |
| 5019974 | Beckers | May 1991 | A |
| 5034112 | Murase et al. | Jul 1991 | A |
| 5050612 | Matsumura | Sep 1991 | A |
| 5077476 | Rosenthal | Dec 1991 | A |
| 5097834 | Skrabal | Mar 1992 | A |
| 5101814 | Palti | Apr 1992 | A |
| 5108819 | Heller et al. | Apr 1992 | A |
| 5137028 | Nishimura | Aug 1992 | A |
| 5160418 | Mullen | Nov 1992 | A |
| 5165407 | Wilson et al. | Nov 1992 | A |
| 5190041 | Palti | Mar 1993 | A |
| 5208147 | Kagenow et al. | May 1993 | A |
| 5249576 | Golberger et al. | Oct 1993 | A |
| 5262305 | Heller et al. | Nov 1993 | A |
| 5264104 | Gregg et al. | Nov 1993 | A |
| 5266179 | Nankai et al. | Nov 1993 | A |
| 5269891 | Colin | Dec 1993 | A |
| 5281319 | Kaneko et al. | Jan 1994 | A |
| 5282848 | Schmitt | Feb 1994 | A |
| 5284140 | Allen et al. | Feb 1994 | A |
| 5284570 | Savage et al. | Feb 1994 | A |
| 5299571 | Mastrototaro | Apr 1994 | A |
| 5307263 | Brown | Apr 1994 | A |
| 5312361 | Zadini et al. | May 1994 | A |
| 5314471 | Brauker et al. | May 1994 | A |
| 5316008 | Suga et al. | May 1994 | A |
| 5322063 | Allen et al. | Jun 1994 | A |
| 5324322 | Grill et al. | Jun 1994 | A |
| 5330634 | Wong et al. | Jul 1994 | A |
| 5331555 | Hashimoto et al. | Jul 1994 | A |
| 5337747 | Neftel | Aug 1994 | A |
| 5343869 | Pross et al. | Sep 1994 | A |
| 5352351 | White | Oct 1994 | A |
| 5354449 | Band et al. | Oct 1994 | A |
| 5376070 | Purvis et al. | Dec 1994 | A |
| 5390671 | Lord et al. | Feb 1995 | A |
| 5391250 | Cheney, II et al. | Feb 1995 | A |
| 5411647 | Johnson et al. | May 1995 | A |
| 5411866 | Luong | May 1995 | A |
| 5429602 | Hauser | Jul 1995 | A |
| 5429735 | Johnson et al. | Jul 1995 | A |
| 5448992 | Kupershmidt | Sep 1995 | A |
| 5462051 | Oka et al. | Oct 1995 | A |
| 5466356 | Schneider et al. | Nov 1995 | A |
| 5469846 | Khan | Nov 1995 | A |
| 5474552 | Palti | Dec 1995 | A |
| 5476776 | Wilkins | Dec 1995 | A |
| 5482008 | Stafford et al. | Jan 1996 | A |
| 5482473 | Lord et al. | Jan 1996 | A |
| 5484404 | Schulman et al. | Jan 1996 | A |
| 5494562 | Maley et al. | Feb 1996 | A |
| 5497772 | Schulman et al. | Mar 1996 | A |
| 5502396 | Desarzens et al. | Mar 1996 | A |
| 5507288 | Bocker et al. | Apr 1996 | A |
| 5513636 | Palti | May 1996 | A |
| 5518601 | Foos et al. | May 1996 | A |
| 5527288 | Gross | Jun 1996 | A |
| 5531679 | Schulman et al. | Jul 1996 | A |
| 5531878 | Vadgama et al. | Jul 1996 | A |
| 5568806 | Cheney, II et al. | Oct 1996 | A |
| 5569186 | Lord et al. | Oct 1996 | A |
| 5575293 | Miller et al. | Nov 1996 | A |
| 5582184 | Ericson et al. | Dec 1996 | A |
| 5584813 | Livingston et al. | Dec 1996 | A |
| 5586553 | Halili et al. | Dec 1996 | A |
| 5589133 | Suzuki | Dec 1996 | A |
| 5611900 | Worden | Mar 1997 | A |
| 5660163 | Schulman et al. | Aug 1997 | A |
| 5660565 | Williams | Aug 1997 | A |
| 5665065 | Colman et al. | Sep 1997 | A |
| 5674289 | Fournier et al. | Oct 1997 | A |
| 5676820 | Wang et al. | Oct 1997 | A |
| 5682884 | Hill | Nov 1997 | A |
| 5695623 | Michel et al. | Dec 1997 | A |
| 5696314 | McCaffrey et al. | Dec 1997 | A |
| 5711861 | Ward et al. | Jan 1998 | A |
| 5733259 | Valcke | Mar 1998 | A |
| 5743262 | Lepper, Jr. et al. | Apr 1998 | A |
| 5749832 | Vadgama et al. | May 1998 | A |
| 5749907 | Mann | May 1998 | A |
| 5781455 | Hyodo et al. | Jul 1998 | A |
| 5791344 | Schulman et al. | Aug 1998 | A |
| 5800420 | Gross | Sep 1998 | A |
| 5806517 | Gerhardt et al. | Sep 1998 | A |
| 5807375 | Gross et al. | Sep 1998 | A |
| 5814599 | Mitragotri et al. | Sep 1998 | A |
| 5820622 | Gross et al. | Oct 1998 | A |
| 5822715 | Worthington et al. | Oct 1998 | A |
| 5836989 | Shelton | Nov 1998 | A |
| 5840148 | Campbell et al. | Nov 1998 | A |
| 5848991 | Gross | Dec 1998 | A |
| 5882494 | Van Antwerp | Mar 1999 | A |
| 5895235 | Droz | Apr 1999 | A |
| 5904708 | Goedeke | May 1999 | A |
| 5919216 | Houben et al. | Jul 1999 | A |
| 5925021 | Castellano et al. | Jul 1999 | A |
| 5931814 | Alex et al. | Aug 1999 | A |
| 5933136 | Brown | Aug 1999 | A |
| 5954643 | Van Antwerp et al. | Sep 1999 | A |
| 5954954 | Houck et al. | Sep 1999 | A |
| 5957854 | Besson et al. | Sep 1999 | A |
| 5961451 | Reber et al. | Oct 1999 | A |
| 5963132 | Yoakum | Oct 1999 | A |
| 5964993 | Blubaugh et al. | Oct 1999 | A |
| 5971922 | Arita et al. | Oct 1999 | A |
| 5995860 | Sun et al. | Nov 1999 | A |
| 5997501 | Gross | Dec 1999 | A |
| 6001067 | Shults et al. | Dec 1999 | A |
| 6011984 | Van Antwerp et al. | Jan 2000 | A |
| 6027445 | Von Bahr | Feb 2000 | A |
| 6036924 | Simons et al. | Mar 2000 | A |
| 6059946 | Yukawa et al. | May 2000 | A |
| 6081736 | Colvin et al. | Jun 2000 | A |
| 6083523 | Dionne et al. | Jul 2000 | A |
| 6091975 | Daddona et al. | Jul 2000 | A |
| 6093172 | Funderburk et al. | Jul 2000 | A |
| 6117290 | Say | Sep 2000 | A |
| 6122536 | Sun et al. | Sep 2000 | A |
| 6123827 | Wong et al. | Sep 2000 | A |
| 6129891 | Rolander et al. | Oct 2000 | A |
| 6135978 | Houben et al. | Oct 2000 | A |
| 6163720 | Gyory et al. | Dec 2000 | A |
| 6169155 | Alvarez et al. | Jan 2001 | B1 |
| 6175752 | Say et al. | Jan 2001 | B1 |
| 6180416 | Kurnik et al. | Jan 2001 | B1 |
| 6192891 | Gravel et al. | Feb 2001 | B1 |
| 6208894 | Schulman et al. | Mar 2001 | B1 |
| 6233471 | Berner et al. | May 2001 | B1 |
| 6234964 | Iliff | May 2001 | B1 |
| 6248067 | Causey, III et al. | Jun 2001 | B1 |
| 6272364 | Kurnik | Aug 2001 | B1 |
| 6272480 | Tresp et al. | Aug 2001 | B1 |
| 6275717 | Gross et al. | Aug 2001 | B1 |
| 6284478 | Heller et al. | Sep 2001 | B1 |
| 6299583 | Eggers et al. | Oct 2001 | B1 |
| 6302855 | Lav et al. | Oct 2001 | B1 |
| 6312388 | Marcovecchio et al. | Nov 2001 | B1 |
| 6326160 | Dunn et al. | Dec 2001 | B1 |
| 6379317 | Kintzig et al. | Apr 2002 | B1 |
| 6406066 | Uegane | Jun 2002 | B1 |
| 6416651 | Miller | Jul 2002 | B1 |
| 6424847 | Mastrototaro et al. | Jul 2002 | B1 |
| 6464849 | Say et al. | Oct 2002 | B1 |
| 6475750 | Han et al. | Nov 2002 | B1 |
| 6477395 | Schulman et al. | Nov 2002 | B2 |
| 6510329 | Heckel | Jan 2003 | B2 |
| 6512939 | Colvin et al. | Jan 2003 | B1 |
| 6534711 | Pollack | Mar 2003 | B1 |
| 6544212 | Galley et al. | Apr 2003 | B2 |
| 6546269 | Kurnik | Apr 2003 | B1 |
| 6549796 | Sohrab | Apr 2003 | B2 |
| 6553241 | Mannheimer et al. | Apr 2003 | B2 |
| 6553244 | Lesho et al. | Apr 2003 | B2 |
| 6558320 | Causey | May 2003 | B1 |
| 6558321 | Burd et al. | May 2003 | B1 |
| 6558351 | Steil et al. | May 2003 | B1 |
| 6558955 | Kristal 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 |
| 6565509 | Say et al. | May 2003 | B1 |
| 6571128 | Lebel et al. | May 2003 | B2 |
| 6572545 | Knobbe et al. | Jun 2003 | B2 |
| 6575905 | Knobbe et al. | Jun 2003 | B2 |
| 6577899 | Lebel et al. | Jun 2003 | B2 |
| 6589229 | Connelly et al. | Jul 2003 | B1 |
| 6591125 | Buse et al. | Jul 2003 | B1 |
| 6605072 | Struys et al. | Aug 2003 | B2 |
| 6612984 | Kerr | Sep 2003 | B1 |
| 6613379 | Ward et al. | Sep 2003 | B2 |
| 6618934 | Feldman et al. | Sep 2003 | B1 |
| 6620138 | Marrgi et al. | Sep 2003 | B1 |
| 6633772 | Ford et al. | Oct 2003 | B2 |
| 6635014 | Starkweather et al. | Oct 2003 | B2 |
| 6641533 | Causey et al. | Nov 2003 | B2 |
| 6648821 | Lebel et al. | Nov 2003 | B2 |
| 6654625 | Say et al. | Nov 2003 | B1 |
| 6673022 | Bobo et al. | Jan 2004 | B1 |
| 6673596 | Sayler et al. | Jan 2004 | B1 |
| 6694191 | Starkweather et al. | Feb 2004 | B2 |
| 6699383 | Lemire et al. | Mar 2004 | B2 |
| 6702972 | Markle | Mar 2004 | B1 |
| 6721587 | Gough | Apr 2004 | B2 |
| 6731976 | Penn et al. | May 2004 | B2 |
| 6740072 | Starkweather et al. | May 2004 | B2 |
| 6740075 | Lebel et al. | May 2004 | B2 |
| 6742635 | Neel et al. | Jun 2004 | B2 |
| 6743635 | Neel et al. | Jun 2004 | B2 |
| 6750055 | Connelly et al. | Jun 2004 | B1 |
| 6773565 | Kunimoto et al. | Aug 2004 | B2 |
| 6802957 | Jung et al. | Oct 2004 | B2 |
| 6809653 | Mann et al. | Oct 2004 | B1 |
| 6810290 | Lebel et al. | Oct 2004 | B2 |
| 6813519 | Lebel et al. | Nov 2004 | B2 |
| 6832200 | Greeven et al. | Dec 2004 | B2 |
| 6862465 | Shults et al. | Mar 2005 | B2 |
| 6875195 | Choi | Apr 2005 | B2 |
| 6893552 | Wang et al. | May 2005 | B1 |
| 6895263 | Shin et al. | May 2005 | B2 |
| 6931327 | Goode et al. | Aug 2005 | B2 |
| 6936006 | Sabra | Aug 2005 | B2 |
| 6936029 | Mann et al. | Aug 2005 | B2 |
| 6965791 | Hitchcock et al. | Nov 2005 | B1 |
| 6998247 | Monfre et al. | Feb 2006 | B2 |
| 7011630 | Desai et al. | Mar 2006 | B2 |
| 7025743 | Mann et al. | Apr 2006 | B2 |
| 7029444 | Shin et al. | Apr 2006 | B2 |
| 7044911 | Drinan et al. | May 2006 | B2 |
| 7058437 | Buse et al. | Jun 2006 | B2 |
| 7060059 | Keith et al. | Jun 2006 | B2 |
| 7074307 | Simpson et al. | Jul 2006 | B2 |
| 7081195 | Simpson et al. | Jul 2006 | B2 |
| 7098803 | Mann et al. | Aug 2006 | B2 |
| 7134999 | Brauker et al. | Nov 2006 | B2 |
| 7162290 | Levin | Jan 2007 | B1 |
| 7225535 | Feldman et al. | Jun 2007 | B2 |
| 7267665 | Steil et al. | Sep 2007 | B2 |
| 7276029 | Goode et al. | Oct 2007 | B2 |
| 7278983 | Ireland et al. | Oct 2007 | B2 |
| 7282029 | Poulsen et al. | Oct 2007 | B1 |
| 7291114 | Mault | Nov 2007 | B2 |
| 7295867 | Berner et al. | Nov 2007 | B2 |
| 7344500 | Talbot et al. | Mar 2008 | B2 |
| 7367942 | Grage et al. | May 2008 | B2 |
| 7417164 | Suri | Aug 2008 | B2 |
| 7519408 | Rasdal et al. | Apr 2009 | B2 |
| 7569030 | Lebel et al. | Aug 2009 | B2 |
| 7591801 | Brauker et al. | Sep 2009 | B2 |
| 7640048 | Dobbles et al. | Dec 2009 | B2 |
| 7647237 | Malave et al. | Jan 2010 | B2 |
| 7657297 | Simpson et al. | Feb 2010 | B2 |
| 7670288 | Sher | Mar 2010 | B2 |
| 7901394 | Ireland et al. | Mar 2011 | B2 |
| 7946985 | Mastrototaro et al. | May 2011 | B2 |
| 8512276 | Talbot et al. | Aug 2013 | B2 |
| 8808228 | Blister et al. | Aug 2014 | B2 |
| 20010007950 | North et al. | Jul 2001 | A1 |
| 20010016682 | Berner et al. | Aug 2001 | A1 |
| 20010041830 | Varalli et al. | Nov 2001 | A1 |
| 20020026111 | Ackerman | Feb 2002 | A1 |
| 20020042561 | Schulman et al. | Apr 2002 | A1 |
| 20020043471 | Ikeda et al. | Apr 2002 | A1 |
| 20020045808 | Ford et al. | Apr 2002 | A1 |
| 20020060692 | Broemmelsiek | May 2002 | A1 |
| 20020065453 | Lesho et al. | May 2002 | A1 |
| 20020084196 | Liamos et al. | Jul 2002 | A1 |
| 20020099997 | Piret | Jul 2002 | A1 |
| 20020119711 | Van Antwerp et al. | Aug 2002 | A1 |
| 20020123048 | Gau | Sep 2002 | A1 |
| 20020161288 | Shin et al. | Oct 2002 | A1 |
| 20020188185 | Sohrab | Dec 2002 | A1 |
| 20030023171 | Sato et al. | Jan 2003 | A1 |
| 20030028089 | Galley | Feb 2003 | A1 |
| 20030060692 | Ruchti et al. | Mar 2003 | A1 |
| 20030060753 | Starkweather et al. | Mar 2003 | A1 |
| 20030060765 | Campbell et al. | Mar 2003 | A1 |
| 20030078481 | McIvor et al. | Apr 2003 | A1 |
| 20030097082 | Purdy et al. | May 2003 | A1 |
| 20030114836 | Estes et al. | Jun 2003 | A1 |
| 20030119208 | Yoon et al. | Jun 2003 | A1 |
| 20030130616 | Steil et al. | Jul 2003 | A1 |
| 20030134347 | Heller et al. | Jul 2003 | A1 |
| 20030176183 | Drucker et al. | Sep 2003 | A1 |
| 20030187338 | Say et al. | Oct 2003 | A1 |
| 20030188427 | Say et al. | Oct 2003 | A1 |
| 20030208113 | Mault et al. | Nov 2003 | A1 |
| 20030211625 | Cohan | Nov 2003 | A1 |
| 20030212346 | Yuzhakov et al. | Nov 2003 | A1 |
| 20030212347 | Sohrab | Nov 2003 | A1 |
| 20030235817 | Bartkowiak et al. | Dec 2003 | A1 |
| 20040011671 | Shults et al. | Jan 2004 | A1 |
| 20040015134 | Lavi et al. | Jan 2004 | A1 |
| 20040044272 | Moerman et al. | Mar 2004 | A1 |
| 20040068230 | Estes et al. | Apr 2004 | A1 |
| 20040074785 | Holker | Apr 2004 | A1 |
| 20040078219 | Kaylor | Apr 2004 | A1 |
| 20040122297 | Stehmann et al. | Jun 2004 | A1 |
| 20040122353 | Shahmirian | Jun 2004 | A1 |
| 20040152187 | Haight et al. | Aug 2004 | A1 |
| 20040162678 | Hetzel et al. | Aug 2004 | A1 |
| 20040167801 | Say et al. | Aug 2004 | A1 |
| 20040173472 | Jung et al. | Sep 2004 | A1 |
| 20040186365 | Jin et al. | Sep 2004 | A1 |
| 20040204687 | Morgensen | Oct 2004 | A1 |
| 20040254433 | Bandis | Dec 2004 | A1 |
| 20050026689 | Marks | Feb 2005 | A1 |
| 20050027180 | Goode et al. | Feb 2005 | A1 |
| 20050027182 | Siddiqui et al. | Feb 2005 | A1 |
| 20050027463 | Goode et al. | Feb 2005 | A1 |
| 20050031689 | Shults et al. | Feb 2005 | A1 |
| 20050033132 | Shults et al. | Feb 2005 | A1 |
| 20050043598 | Goode et al. | Feb 2005 | A1 |
| 20050051427 | Brauker et al. | Mar 2005 | A1 |
| 20050051440 | Simpson et al. | Mar 2005 | A1 |
| 20050054909 | Petisce et al. | Mar 2005 | A1 |
| 20050056552 | Simpson et al. | Mar 2005 | A1 |
| 20050090607 | Tapsak et al. | Apr 2005 | A1 |
| 20050112169 | Brauker et al. | May 2005 | A1 |
| 20050113653 | Fox et al. | May 2005 | A1 |
| 20050113744 | Donoghue et al. | May 2005 | A1 |
| 20050121322 | Say | Jun 2005 | A1 |
| 20050143635 | Kamath et al. | Jun 2005 | A1 |
| 20050143675 | Neel et al. | Jun 2005 | A1 |
| 20050154271 | Rasdal et al. | Jul 2005 | A1 |
| 20050177398 | Watanabe et al. | Aug 2005 | A1 |
| 20050182451 | Griffin et al. | Aug 2005 | A1 |
| 20050187720 | Goode et al. | Aug 2005 | A1 |
| 20050192557 | Brauker et al. | Sep 2005 | A1 |
| 20050203360 | Brauker et al. | Sep 2005 | A1 |
| 20050239154 | Feldman et al. | Oct 2005 | A1 |
| 20050242479 | Petisce et al. | Nov 2005 | A1 |
| 20050245795 | Goode et al. | Nov 2005 | A1 |
| 20050245799 | Brauker et al. | Nov 2005 | A1 |
| 20050245904 | Estes et al. | Nov 2005 | A1 |
| 20050261563 | Zhou et al. | Nov 2005 | A1 |
| 20060015020 | Neale et al. | Jan 2006 | A1 |
| 20060015024 | Brister et al. | Jan 2006 | A1 |
| 20060020186 | Brister et al. | Jan 2006 | A1 |
| 20060036141 | Kamath et al. | Feb 2006 | A1 |
| 20060036143 | Brister et al. | Feb 2006 | A1 |
| 20060036144 | Brister et al. | Feb 2006 | A1 |
| 20060040402 | Brauker et al. | Feb 2006 | A1 |
| 20060079809 | Goldberger et al. | Apr 2006 | A1 |
| 20060173406 | Hayes et al. | Aug 2006 | A1 |
| 20060183984 | Dobbles et al. | Aug 2006 | A1 |
| 20060183985 | Brister et al. | Aug 2006 | A1 |
| 20060195029 | Shults et al. | Aug 2006 | A1 |
| 20060222566 | Brauker et al. | Oct 2006 | A1 |
| 20060258929 | Goode et al. | Nov 2006 | A1 |
| 20070016381 | Kamath et al. | Jan 2007 | A1 |
| 20070027385 | Brister et al. | Feb 2007 | A1 |
| 20070032706 | Kamath et al. | Feb 2007 | A1 |
| 20070038044 | Dobbles et al. | Feb 2007 | A1 |
| 20070066873 | Kamath et al. | Mar 2007 | A1 |
| 20070066956 | Finkel | Mar 2007 | A1 |
| 20070100222 | Mastrototaro et al. | May 2007 | A1 |
| 20070106135 | Sloan et al. | May 2007 | A1 |
| 20070112298 | Mueller et al. | May 2007 | A1 |
| 20070173761 | Kanderian et al. | Jul 2007 | A1 |
| 20070179434 | Weinert et al. | Aug 2007 | A1 |
| 20070203410 | Say et al. | Aug 2007 | A1 |
| 20070203966 | Brauker et al. | Aug 2007 | A1 |
| 20070208244 | Brauker et al. | Sep 2007 | A1 |
| 20070208245 | Brauker et al. | Sep 2007 | A1 |
| 20070208246 | Brauker et al. | Sep 2007 | A1 |
| 20070235331 | Simpson et al. | Oct 2007 | A1 |
| 20070293742 | Simonsen et al. | Dec 2007 | A1 |
| 20080021666 | Goode et al. | Jan 2008 | A1 |
| 20080097289 | Steil et al. | Apr 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 |
| 20080194935 | Brister 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 |
| 20080262469 | Brister et al. | Oct 2008 | A1 |
| 20080269723 | Mastrototaro et al. | Oct 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 |
| 20080306433 | Dobbles et al. | Dec 2008 | A1 |
| 20080306435 | Kamath et al. | Dec 2008 | A1 |
| 20080306444 | Brister et al. | Dec 2008 | A1 |
| 20090018418 | Markle et al. | Jan 2009 | A1 |
| 20090018426 | Markle et al. | Jan 2009 | A1 |
| 20090061528 | Suri | Mar 2009 | A1 |
| 20090076356 | Simpson | Mar 2009 | A1 |
| 20090076360 | Brister et al. | Mar 2009 | A1 |
| 20090081803 | Gamsey et al. | Mar 2009 | A1 |
| 20090099434 | Liu et al. | Apr 2009 | A1 |
| 20090156924 | Shariati et al. | Jun 2009 | A1 |
| 20090177143 | Markle et al. | Jul 2009 | A1 |
| 20090192366 | Mensinger et al. | Jul 2009 | A1 |
| 20090192722 | Shariati et al. | Jul 2009 | A1 |
| 20090192751 | Kamath et al. | Jul 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 |
| 20090264719 | Markle et al. | Oct 2009 | A1 |
| 20090264856 | Lebel et al. | Oct 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 |
| 20100010324 | Brauker 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 |
| 20100022855 | Brauker et al. | Jan 2010 | A1 |
| 20100030053 | Goode, Jr. et al. | Feb 2010 | A1 |
| 20100030484 | 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 |
| 20100076283 | Simpson et al. | Mar 2010 | A1 |
| 20110270158 | Brauker et al. | Nov 2011 | A1 |
| 20120059673 | Cohen et al. | Mar 2012 | A1 |
| 20120097289 | Chun et al. | Apr 2012 | A1 |
| 20120186581 | Brauker et al. | Jul 2012 | A1 |
| 20120190953 | Brauker et al. | Jul 2012 | A1 |
| 20120191063 | Brauker et al. | Jul 2012 | A1 |
| 20120215201 | Brauker et al. | Aug 2012 | A1 |
| 20120220979 | Brauker et al. | Aug 2012 | A1 |
| 20120227737 | Mastrototaro et al. | Sep 2012 | A1 |
| 20120238852 | Brauker et al. | Sep 2012 | A1 |
| 20120259278 | Hayes et al. | Oct 2012 | A1 |
| 20120296311 | Brauker et al. | Nov 2012 | A1 |
| Number | Date | Country |
|---|---|---|
| 0 098 592 | Jan 1984 | EP |
| 127 958 | Dec 1984 | EP |
| 0 286 118 | Oct 1988 | EP |
| 320 109 | Jun 1989 | EP |
| 0 353 328 | Feb 1990 | EP |
| 3 390 390 | Oct 1990 | EP |
| 0 396 788 | Nov 1990 | EP |
| 0 441 394 | Aug 1991 | EP |
| 0 534 074 | Mar 1993 | EP |
| 0 563 795 | Oct 1993 | EP |
| 0 838 230 | Apr 1998 | EP |
| 0 880 936 | Dec 1998 | EP |
| 0 967 788 | Dec 1999 | EP |
| 1 078 258 | Feb 2001 | EP |
| 1 102 194 | May 2001 | EP |
| 1 266 607 | Dec 2002 | EP |
| 1 338 295 | Aug 2003 | EP |
| 1 498 067 | Jan 2005 | EP |
| 2 226 086 | Aug 2010 | EP |
| 2 228 642 | Sep 2010 | EP |
| 2656423 | Jun 1991 | FR |
| 2760962 | Sep 1998 | FR |
| 2149918 | Jun 1985 | GB |
| 62083649 | Apr 1987 | JP |
| 07-083871 | Mar 1995 | JP |
| 2002-189015 | Jul 2002 | JP |
| WO 1989-02720 | Apr 1989 | WO |
| WO 1990-00738 | Jan 1990 | WO |
| WO 1990-10861 | Sep 1990 | WO |
| WO 1992-13271 | Aug 1992 | WO |
| WO 1993-14693 | Aug 1993 | WO |
| WO 1995-07109 | Mar 1995 | WO |
| WO 1995-13838 | May 1995 | WO |
| WO 1996-14026 | May 1996 | WO |
| WO 1996-25089 | Aug 1996 | WO |
| WO 1997-01986 | Jan 1997 | WO |
| WO 1997-06727 | Feb 1997 | WO |
| WO 1997-28737 | Aug 1997 | WO |
| WO 1998-24358 | Jun 1998 | WO |
| WO 1999-56613 | Apr 1999 | WO |
| WO 1999-48419 | Sep 1999 | WO |
| WO 1999-58973 | Nov 1999 | WO |
| WO 1999-59657 | Nov 1999 | WO |
| WO 2000-019887 | Apr 2000 | WO |
| WO 2000-032098 | Jun 2000 | WO |
| WO 2000-033065 | Jun 2000 | WO |
| WO 2000-049941 | Aug 2000 | WO |
| WO 2000-059373 | Oct 2000 | WO |
| WO 2000-074753 | Dec 2000 | WO |
| WO 2000-078210 | Dec 2000 | WO |
| WO 2001-012158 | Feb 2001 | WO |
| WO 2001-020019 | Mar 2001 | WO |
| WO 2001-052727 | Jul 2001 | WO |
| WO 2001-088534 | Nov 2001 | WO |
| WO 2002-024065 | Mar 2002 | WO |
| WO 2003-022327 | Mar 2003 | WO |
| WO 2003022327 | Mar 2003 | WO |
| WO 2004-009161 | Jan 2004 | WO |
| WO 2004009161 | Jan 2004 | WO |
| WO 2005-011489 | Feb 2005 | WO |
| WO 2005-026689 | Oct 2005 | WO |
| WO 2005-093629 | Oct 2005 | WO |
| WO 2006-017358 | Feb 2006 | WO |
| WO 2006-021430 | Mar 2006 | WO |
| Entry |
|---|
| US 7,530,950, 05/2009, Brister et al. (withdrawn) |
| Aalders et al. 1991. Development of a wearable glucose sensor; studies in healthy volunteers and in diabetic patients. The International Journal of Artificial Organs 14(2):102-108. |
| Abe et al. 1992. Characterization of glucose microsensors for intracellular measurements. Analytical Chemistry 64(18):2160-2163. |
| Abel et al. 1984. Experience with an implantable glucose sensor as a prerequisite of an artificial beta cell. Biomedica et Biochimica Acta 43(5):577-584. |
| Abel et al. 2002. Biosensors for in vivo glucose measurement: can we cross the experimental stage. Biosensors & Bioelectronics 17:1059-1070. |
| Alcock & Turner, 1994. Continuous Analyte Monitoring to Aid Clinical Practice. IEEE Engineering in Med. & Biol. Mag. 13:319-325. |
| American Diabetes Association, Jan. 2007. Position Statement: Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 30(Supp. 1):S42-S47. |
| American Diabetes Association, Jan. 2007. Position Statement: Standards of Medical Care in Diabetes—2007. Diabetes Care 30(Supp. 1):S4-S41. |
| American Diabetes Association, Jan. 2007. Summary of Revisions for the 2007 Clinical Practice Recommendations. Diabetes Care 30(Supp. 1): S3. |
| American Heritage Dictionary, 4th Edition. 2000. Houghton Mifflin Company, p. 82. |
| Amin et al. 2003. Hypoglycemia prevalence in prepubertal children with type 1 diabetes on standard insulin regimen: Use of continuous glucose monitoring system. Diabetes Care 26(3):662-667. |
| Answers.com. “xenogenic.” The American Heritage Stedman's Medical Dictionary. Houghton Mifflin Company, 2002. Answers.com Nov. 7, 2006 http:--www. Answers.com-topic-xenogenic. |
| Armour et al. Dec. 1990. Application of Chronic Intravascular Blood Glucose Sensor in Dogs. Diabetes 39:1519-1526. |
| Atanasov et al. 1994. Biosensor for continuous glucose monitoring. Biotechnology and Bioengineering 43:262-266. |
| Atanasov et al. 1997. Implantation of a refillable glucose monitoring-telemetry device. Biosensors & Bioelectronios 12:669-680. |
| Aussedat et al. 1997. A user-friendly method for calibrating a subcutaneous glucose sensor-based hypoglycaemic alarm. Biosensors & Bioelectronics 12(11):1061-1071. |
| Aussedat et al. 2000. Interstitial glucose concentration and glycemia: Implications for continuous subcutaneous glucose monitoring. Am J Physiol Endocrinol Metab 278: E716-E728. |
| Bailey et al. 2007. Reduction in hemoglobin A1c with real-time continuous glucose monitoring: results from a 12-week observational study. Diabetes Technology & Therapeutics 9(3):203-210. |
| Baker et al. 1996. Dynamic delay and maximal dynamic error in continuous biosensors. Analytical Chemistry 68(8):1292-1297. |
| Bani Amer, M. M. 2002. An accurate amperometric glucose sensor based glucometer with eliminated cross-sensitivity. J Med Eng Technol 26(5):208-213. |
| Bard et al. 1980. Electrochemical Methods. John Wiley & Sons, pp. 173-175. |
| Beach et al. 1999. Subminiature implantable potentiostat and modified commercial telemetry device for remote glucose monitoring. IEEE Transactions on Instrumentation and Measurement 48(6):1239-1245. |
| Bellucci et al. Jan. 1986. Electrochemical behaviour of graphite-epoxy composite materials (GECM) in aqueous salt solutions. Journal of Applied Electrochemistry, 16(1): 15-22. |
| Berger et al. 1988. Proceedings of the Annual Symposium on Computer Applications in Medical Care, pp. 52-57. Computer Programs to Assist the Physician in the analysis of . . . . |
| Bessman et al., 1973. Progress toward a glucose sensor for the artificial pancreas. Proceedings of a Workshop on Ion-Selective Microelectrodes, Jun. 4-5, 1973, Boston, MA. 189-197. |
| Biermann et al. 2008. How would patients behave if they were continually informed of their blood glucose levels? A simulation study using a “virtual” patient. Diabetes Technology & Therapeutics, 10:178-187. |
| Bindra et al. 1991. Design and In Vitro Studies of a Needle-Type Glucose Sensor for Subcutaneous Monitoring. Analytical Chemistry 63:1692-96. |
| Bisenberger et al. 1995. A triple-step potential waveform at enzyme multisensors with thick-film gold electrodes for detection of glucose and sucrose. Sensors and Actuators B 28:181-189. |
| Bland et al. 1986. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307-310. |
| Bland et al. 1990. A note on the use of intraclass correlation coefficient in the evaluation of agreement between two methods of measurement. Comput. Biol. Med. 20(5):337-340. |
| Bobbioni-Harsch et al. 1993. Lifespan of subcutaneous glucose sensors and their performances during dynamic glycaemia changes in rats. J. Biomed. Eng. 15:457-463. |
| Bode et al. 1999. Continuous glucose monitoring used to adjust diabetes therapy improves glycosylated hemoglobin: A pilot study. Diabetes Research and Clinical Practice 46:183-190. |
| Bode et al. 2000. Using the continuous glucose monitoring system to improve the management of type 1 diabetes. Diabetes Technology & Therapeutics 2(Suppl 1):S43-48. |
| Bode, B. W. 2000. Clinical utility of the continuous glucose monitoring system. Diabetes Technology & Therapeutics 2(Suppl 1):S35-41. |
| Boedeker Plastics, Inc. 2009. Polyethylene Specifications Data Sheet, http:--www.boedeker.com-polye_p.htm [Aug. 19, 2009 3:36:33 PM]. |
| Boland et al. 2001. Limitations of conventional methods of self-monitoring of blood glucose. Diabetes Care 24(11): 1858-1862. |
| Bolinder et al. 1992. Microdialysis measurement of the absolute glucose concentration in subcutaneous adipose tissue allowing glucose monitoring in diabetic patients. Diabetologia 35:1177-1180. |
| Bowman, L.; Meindl, J. D. 1986. The packaging of implantable integrated sensors. IEEE Trans Biomed Eng BME33(2):248-255. |
| Brauker et al. Jun. 27, 1996, Local Inflammatory Response Around Diffusion Chambers Containing Xenografts. Transplantation 61(12):1671-1677. |
| Braunwald, 2008. Biomarkers in heart failure. N. Engl. J. Med., 358: 2148-2159. |
| Bremer et al. 1999. Is blood glucose predictable from previous values? A solicitation for data. Diabetes 48:445-451. |
| Bremer et al. 2001. Benchmark data from the literature for evaluation of new glucose sensing technologies. Diabetes Technology & Therapeutics 3(3):409-418. |
| Brooks et al. 1987-88. Development of an on-line glucose sensor for fermentation monitoring. Biosensors 3:45-56 (1987-88). |
| Bruckel et al. 1989. In vivo measurement of subcutaneous glucose concentrations with an enzymatic glucose sensor and a wick method. Klin Wochenschr 67:491-495. |
| Cai et al. 2004. A wireless, remote query glucose biosensor based on a pH-sensitive polymer. Analytical Chemistry 76(4):4038-4043. |
| Campanella et al. 1993. Biosensor for direct determination of glucose and lactate in undiluted biological fluids. Biosensors & Bioelectronics 8:307-314. |
| Candas et al. 1994. An adaptive plasma glucose controller based on a nonlinear insulin-glucose model IEEE Transactions on Biomedical Engineering 41(2): 116-124. |
| Cass et al. 1984. Ferrocene-mediated enzyme electrodes for amperometric determination of glucose. Analytical Chemistry 36:667-71 (1984). |
| Cassidy et al., Apr. 1993. Novel electrochemical device for the detection of cholesterol or glucose. Analyst, 118:415-418. |
| Chase et al. 2001. Continuous subcutaneous glucose monitoring in children with type 1 diabetes. Pediatrics 107:222-226. |
| Chase et al. 2005. Targeted Glycemic Reduction in Critical Care Using Closed-Loop Control. Diabetes Technology & Therapeutics 7(2): 274-282. |
| Chia et al. 2004. Glucose sensors: toward closed loop insulin delivery. Endocrinol Metab Clin North Am 33:175-95. |
| Choleau et al. 2002. 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 17:647-654. |
| Ciba® Irgacure 2959 Photoinitiator Product Description, Ciba Specialty Chemicals Inc., Basel, Switzerland. |
| Claremont et al. 1986. Subcutaneous implantation of a ferrocene-mediated glucose sensor in pigs. Diabetologia 29:817-821. |
| Claremont et al. Jul. 1986. Potentially-implantable, ferrocene-mediated glucose sensor, J. Biomed. Eng. 8:272-274. |
| Clark et al. 1987. Configurational cyclic voltammetry: increasing the specificity and reliability of implanted electrodes. IEEE—Ninth Annual Conference of the Engineering in Medicine and Biology Society, pp. 0782-0783. |
| Clark et al. 1988. Long-term stability of electroenzymatic glucose sensors implanted in mice. Trans Am Soc Artif Intern Organs 34:259-265. |
| Clark et al., 1981. One-minute electrochemical enzymic assay for cholesterol in biological materials. Clin. Chem. 27(12): 1978-1982. |
| CLSI. Performance metrics for continuous interstitial glucose monitoring; approved guideline, CLSI document POCT05-A. Wayne, PA: Clinical and Laboratory Standards Institute: 2008 28(33), 72 pp. |
| Colangelo et al. 1967. Corrosion rate measurements in vivo. Journal of Biomedical Materials Research, 1:405-414. |
| Colowick et al. 1976. Methods in Enzymology, vol. XLIV, Immobilized Enzymes. New York: Academic Press. |
| Cox et al. 1985. Accuracy of perceiving blood glucose in IDDM. Diabetes Care 8(6):529-536. |
| Csoregi et al. 1994. Amperometric microbiosensors for detection of hydrogen peroxide and glucose based on peroxidase-modified carbon fibers. Electroanalysis 6:925-933. |
| Csoregi et al., 1994. Design, characterization, and one-point in vivo calibration of a subcutaneously implanted glucose electrode. Analytical Chemistry 66(19):3131-3138. |
| Danielsson et al. 1988. Enzyme thermistors. Methods in Enzymology, 137:181-197. |
| Dassau et al. 2009. In silico evaluation platform for artificial pancreatic (3-cell development—a dynamic simulator for closed loop control with hardware-in-the-loop, Diabetes Technology & Therapeutics, 11 (3): 1-8, 2009. |
| Davies, et al. 1992. Polymer membranes in clinical sensor applications. I. An overview of membrane function. Biomaterials 13(14):971-978. |
| Davis et al. 1983. Bioelectrochemical fuel cell and sensor based on a quinoprotein, alcohol dehydrogenase. Enzyme Microb. Technol., vol. 5. September. 383-388. |
| de Vos et al., 2002. Considerations for successful transplantation of encapsulated pancreatic islets, Diabetologia 45: 159-173. |
| Direct 30-30® meter (Markwell Medical) (Catalog). |
| Dixon et al. 2002. Characterization in vitro and in vivo of the oxygen dependence of an enzyme-polymer biosensor for monitoring brain glucose. Journal of Neuroscience Methods 119:135-142. |
| DuPont1 Dimension AR® (Catalog), 1998. |
| Durliat et al. 1976. Spectrophotometric and electrochemical determinations of L(+)-lactate in blood by use of lactate dehydrogenase from yeast. Clin. Chem. 22(11): 1802-1805. |
| Edwards Lifesciences. Accuracy for your and your patients. Marketing materials, 4 pp. 2002. |
| El Degheidy et al. 1986. Optimization of an implantable coated wire glucose sensor. J. Biomed Eng. 8: 121-129. |
| El-Khatib et al. 2007. Adaptive closed-loop control provides blood-glucose regulation using dual subcutaneous insulin and glucagon infusion in diabetic swine. Journal of Diabetes Science and Technology, 1(2):181-192. |
| El-Sa'ad et al. 1990. Moisture Absorption by Epoxy Resins: the Reverse Thermal Effect. Journal of Materials Science 25:3577-3582. |
| Ernst et al. 2002. Reliable glucose monitoring through the use of microsystem technology. Analytica Bioanalytical Chemistry 373:758-761. |
| Fabietti et al. 2007. Clinical validation of a new control-oriented model of insulin and glucose dynamcs in subjects with type 1 diabetes. Diabetes Technology & Therapeutics 9(4):327-338. |
| Fahy et al. 2008. An analysis: hyperglycemic intensive care patients need continuous glocuse monitoring—easier said than done. Journal of Diabetes Science and Technology, 2(2):201-204, Mar. 2008. |
| Fare et al. 1998. Functional characterization of a conducting polymer-based immunoassay system. Biosensors & Bioelectronics 13(3-4):459-470. |
| Feldman et al. 2003. A continuous glucose sensor based on wired enzyme technology—results from a 3-day trial in patients with type-1 diabetes. Diabetes Technology & Therapeutics 5(5):769-779. |
| Fischer et al. 1987. Assessment of subcutaneous glucose concentration: validation of the wick technique as a reference for implanted electrochemical sensors in normal and diabetic dogs. Diabetologia 30:940-945. |
| Fischer et al. 1989. Oxygen Tension at the Subcutaneous Implantation Site of Glucose Sensors. Biomed. Biochem 11-12:965-972. |
| Fischer et al. 1995. Hypoglycaemia-warning by means of subcutaneous electrochemical glucose sensors: an animal stud. Horm. Metab. Rese. 27:53. |
| Freedman et al. 1991. Statistics, Second Edition, W.W. Norton & Company, p. 74. |
| Frohnauer et al. 2001. Graphical human insulin time-activity profiles using standardized definitions. Diabetes Technology & Therapeutics 3(3):419-429. |
| Frost et al. 2002. Implantable chemical sensors for real-time clinical monitoring: Progress and challenges. Current Opinion in Chemical Biology 6:633-641. |
| Gabbay et al. 2008. Optical coherence tomography-based continuous noninvasive glucose monitoring in patients with diabetes. Diabetes Technology & Therapeutics 10:188-193. |
| Ganesan et al. 2005. Gold layer-based dual crosslinking procedure of glucose oxidase with ferrocene monocarboxylic acid provides a stable biosensor. Analytical Biochemistry 343:188-191. |
| Ganesh et al. 2008. Evaluation of the VIA® blood chemistry monitor for glucose in healthy and diabetic volunteers, Journal of Diabetes Science and Technology 2(2): 182-193. |
| Garg et al. 2004. Improved Glucose Excursions Using an Implantable Real-Time continuous Glucose Sensor in Adults with Type I Diabetes. Diabetes Care 27:734-738. |
| Garg, Satish K., 2002. New Insulin Analogues. Diabetes Technology & Therapeutics 7(5): 813-817. |
| Gerritsen et al. 1999. Performance of subcutaneously implanted glucose sensors for continuous monitoring. The Netherlands Journal of Medicine 54:167-179. |
| Gerritsen, M. 2000. Problems associated with subcutaneously implanted glucose sensors. Diabetes Care 23(2): 143-145. |
| Gilligan et al. 1994. Evaluation of a subcutaneous glucose sensor out to 3 months in a dog model. Diabetes Care 17(8):882-887. |
| Gilligan et al. 2004. Feasibility of continuous long-term glucose monitoring from a subcutaneous glucose sensor in humans. Diabetes Technology & Therapeutics 6:378-386. |
| Godsland et al. 2001. 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, 1-9. |
| Gouda et al., Jul. 4, 2003. Thermal inactivation of glucose oxidase. The Journal of Biological Chemistry 278(27):24324-24333. |
| Gough et al. 2000. Immobilized glucose oxidase in implantable glucose sensor technology. Diabetes Technology & Therapeutics 2(3):377-380. |
| Gough et al. 2003. Frequency characterization of blood gluaose dynamics. Annals of Biomedical Engineering 31:91-97. |
| Gough, May 2001, The implantable glucose sensor: An example of bioengineering design. Introduction to Bioengineering, Chapter 3, pp. 57-66. |
| Gross et al. 2000. Efficacy and reliability of the continuous glucose monitoring system. Diabetes Technology & Therapeutics 2(Suppl 1):S19-26. |
| Gross et al. 2000. Performance evaluation of the MiniMed® continuous glucose monitoring system during patient home use. Diabetes Technology & Therapeutics 2(1):49-56. |
| Guerci et al. 2003. Clinical performance of CGMS in type 1 diabetic patents treated by continuous subcutaneous insulin infusion using insulin analogs. Diabetes Care 26:582-589. |
| Hagvik, Joakim. Mar. 2007. Glucose Measurement: Time for a Gold Standard. J Diabetes Science & Technology 1(2): 169-172. |
| Hall et al. 1998. Electrochemical oxidation of hydrogen peroxide at platinum electrodes. Part I: An adsorption-controlled mechanism. Electrochimica Acta, 43(5-6):579-588. |
| Hall et al. 1998. Electrochemical oxidation of hydrogen peroxide at platinum electrodes. Part II: Effect of potential. Electrochimica Acta 43(14-15):2015-2024. |
| Hall et al. 1999. Electrochemical oxidation of hydrogen peroxide at platinum electrodes. Part III: Effect of temperature. Electrochimica Acta, 44:2455-2462. |
| Hall et al. 1999. Electrochemical oxidation of hydrogen peroxide at platinum electrodes. Part IV: Phosphate buffer dependence. Electrochimica Acta, 44:4573-4582. |
| Hall et al. 2000. Electrochemical oxidation of hydrogen peroxide at platinum electrodes. Part V: Inhibition by chloride. Electrochimica Acta, 45:3573-3579. |
| Hamilton Syringe Selection Guide. 2006. Syringe Selection, www.hamiltoncompany.com. |
| Hashiguchi et al. 1994. 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 17(5):387-396. |
| Heinemann et al., 2004, Review: Measurement of Insulin Absorption and Insulin Action Diabetes Technology & Therapautics 6(5): 698-718. |
| Heinemann, Lutz. 2002. Review: Variability of Insulin Absorption and Insulin Action. Diabetes Technology & Therapeutics 4(5): 673-682. |
| Heinemann, Lutz. Mar. 2007. Measurement Quality of Blood Glucose Meters: Is there a need for an institution with an unbiased view? J Diabetes Science & Technology 1(2): 178-180. |
| Heller 1990. Electrical wiring of redox enzymes. Acc. Chem. Res. 23:128-134. |
| Heller, A. 1992. Electrical Connection of Enzyme Redox Centers to Electrodes. J. Phys. Chem. 96:3579-3587. |
| Heller, A. 1999, Implanted electrochemical glucose sensors for the management of diabetes, Annu Rev Biomed Eng 1:153-175. |
| Heller, A. 2003. Plugging metal connectors into enzymes. Nature Biotechnology 21:631-2. |
| Hicks, 1985. In Situ Monitoring. Clinical Chemistry, 31 (12):1931-1935. |
| Hitchman, M. L. 1978. Measurement of Dissolved Oxygen. In Elving et al. (Eds.) Chemical Analysis vol. 49, Chap, 3, pp. 34-49, 59-123, New York: John Wiley & Sons. |
| Hoel, Paul G. 1976. Elementary Statistics, Fourth Edition, John Wiley & Sons, Inc.. pp. 113-114. |
| Hovorka et al. 2004. Closing the Loop: The Adicol Experience. Diabetes Technology & Therapeutics 6(3): 307-318. |
| Hrapovic et al. 2003. Picoamperometric detection of glucose at ultrasmall platinum-based biosensors: preparation and characterization. Analytical Chemistry 75:3308-3315. |
| http:--www.merriam-webster.com-dictionarv. definition for “aberrant,” Aug. 19, 2008, p. 1. |
| Hu, et al. 1993. A needle-type enzyme-based lactate sensor for in vivo monitoring. Analytica Chimica Acta 281:503-511. |
| Huang et al. 1997. A 0.5mV passive telemetry IC for biomedical applications. Swiss Federal Institute of Technology 4 pp. |
| Huang et al. Aug. 1975. Electrochemical Generation of Oxygen. 1: The Effects of Anions and Cations on Hydrogen Chemisorption and Aniodic Oxide Film Formation on Platinum Electrode. 2: The Effects of Anions and Cations on Oxygen Generation on Platinum . . . U.S. Department of Commerce National Technical Information Service, Case Western Reserve University, Cleveland, OH, Electrochemistyr Research Lab. NTIS N76253623. |
| Hunsley et al. Mar. 2007. Whole Blood Glucose Standard is Key to Accurate Insulin Dosages. J Diabetes Science & Technology 1(2): 173-177. |
| Hunter, I., Jones, L., Kanigan, T., Brenan, C., Sanbol, L. Sosnowski, L. 2000. Minimally Invasive Glucose Sensor and Insulin Delivery System. MIT Home Automation and Healthcare Consortium, Progress Report No. 25. |
| Ishikawa et al. 1998. Initial evaluation of a 290-mm diameter subcutaneous glucose sensor: Glucose monitoring with a biocompatibie, flexible-wire, enzyme-based amperometric microsensor in diabetic and nondiabetic humans. J. Diabetes and its Complications 12:295-301. |
| Jaffari et al. 1995. Recent advances in amperometric glucose biosensors for in vivo monitoring. Physiol. Meas. 16 (1995) 1-15. |
| Jensen et al. 1997. Fast wave forms for pulsed electrochemical detection of glucose by incorporation of reductive desorption of oxidation products. Analytical Chemistry 69(9): 1776-1781. |
| Jeutter, D. C. 1982. A transcutaneous implanted battery recharging and biotelemeter power switching system. IEEE Trans Biomed Eng 29:314-321. |
| Jobst et al., 1996. Thin-Film Microbiosensors for Glucose-Lactate Monitoring: Analytical Chemistry 8(18): 3173-3179. |
| Johnson 1991. Reproducible electrodeposition of biomolecules for the fabrication of miniature electroenzymatic biosensors. Sensors and Actuators B 5:85-89. |
| Johnson et al. 1992. In vivo evaluation of an electroenzymatic glucose sensor implanted in subcutaneous tissue. Biosensors & Bioelectronics, 7:709-714. |
| Jones et al. 2005. Optimal Insulin Pump Dosing and Postprandial Glycemia Following a Pizza Meal Using the Continuous Glucose Monitoring System. Diabetes Technology & Therapeutics 7(2): 233-240. |
| Jovanovic, L. 2000. The role of continuous glucose monitoring in gestational diabetes mellitus. Diabetes Technology & Therapeutics, 2(Suppl 1) S67-71. |
| Kacaniklic May-Jun. 1994. Amperometric Biosensors for Detection of L- and D-Amino Acids Based on Coimmobilized Peroxidase and L- and D-Amino Acid Oxidases in Carbon Paste Electrodes. Electroanalysis 6(5-6):381-390. |
| Kamath et al. 2008. Calibration of a continuous glucose monitor: effect of glucose rate of change. Eighth Annual Diabetes Technology Meeting, Nov. 13-15 2008, p. A88. |
| Kang et al. 2003. In vitro and short-term in vivo characteristics of a Kel-F thin film modified glucose sensor. Anal Sci 19:1481-1486. |
| Kaufman et al. 2001. A pilot study of the continuous glucose monitoring system. Diabetes Care 24(12):2030-2034. |
| Kaufman. 2000. Role of the continuous glucose monitoring system in pediatric patients. Diabetes Technology & Therapeutics 2(1):S-49-S-52. |
| Kawagoe et al. 1991. Enzyme-modified organic conducting salt microelectrode. Analytical Chemistry 63:2961-2965. |
| Keedy et al. 1991. Determination of urate in undiluted whole blood by enzyme electrode. Biosensors & Bioelectronics, 6: 491-499. |
| Kerner et al. 1988. A potentially implantable enzyme electrode for amperometric measurement of glucose. Horm Metab Res Suppl. 20:8-13. |
| Kerner et al. 1993. The function of a hydrogen peroxide-detecting electroenzymatic glucose electrode is markedly impaired in human sub-cutaneous tissue and plasma. Biosensors & Bioelectronics 8:473-482 (1993). |
| Kerner, W. 2001 . Implantable glucose sensors: Present status and future developments. Exp. Clin. Endocrinol. Diabetes 109(Suppl 2):S341-346. |
| Kiechle, F.L. 2001. The impact of continuous glucose monitoring on hospital point-of-care testing programs. Diabetes Technology & Therapeutics 3:647-649. |
| Kizilel et al. 2005. Review: The Bioartificial Pancreas: Progress and Challenges. Diabetes Technology & Therapeutics 7(6): 968-985. |
| Klonoff, David C. 2002. Editorial: Current, Emerging, and Future Trends in Metabolic Monitoring. Diabetes Technology & Therapeutics 4(5): 582-588. |
| Klueh et al. 2003. Use of Vascular Endothelia Cell Growth Factor Gene Transfer to Enhance Implantable Sensor Function in Vivo. Biosensor Function and Vegf-Gene Transfer, pp. 1072-1086. |
| Ko, Wen H. 1985. Implantable Sensors for Closed-Loop Prosthetic Systems, Futura Pub. Co., Inc., Mt. Kisco, NY, Chapter 15:197-210. |
| Kondo et al. 1982. A miniature glucose sensor, implantable in the blood stream. Diabetes Care. 5(3):218-221. |
| Koschinsky et al. 1998. New approach to technical and clinical evaluation of devices for selfmonitoring of blood glucose. Diabetes Care 11(8): 619-619. |
| Koschinsky et al. 2001. Sensors for glucose monitoring: Technical and clinical aspects. Diabetes Metab. Res. Rev. 17:113-123. |
| Koschinsky et al. 2003. Review: Glucose Sensors and the Alternate Site Testing-like Phenomenon: Relationship Between Rapid Blood Glucose Changes and Glucose Sensor Signals. Diabetes Technology & Therapeutics 5(5): 829-842. |
| Kost et al. 1985. Glucose-sensitive membranes containing glucose oxidase: activity, swelling, and permeability studies. Journal of Biomedical Materials Research 19:1117-1133. |
| Koudelka et al. 1989. In vivo response of microfabricated glucose sensors to glycemia changes in normal rats. Biomedica et Biochimica Acta 48(11-12):953-956. |
| Koudelka et al. 1991. In-vivo behaviour of hypodermically implanted microfabricated glucose sensors. Biosensors & Bioelectronics 6:31-36. |
| Kraver et al. 2001. A mixed-signal sensor interface microinstrument. Sensors and Actuators A 91:266-277. |
| Kruger et al. 2000. Psychological motivation and patient education: A role for continuous glucose monitoring. Diabetes Technology & Therapeutics 2(Suppl 1):S93-97. |
| Kulys et al., 1994. Carbon-paste biosensors array for long-term glucose measurement. Biosensors & Beioelectronics 9:491-500. |
| Kunjan et al. 2008. Automated blood sampling and glucose sensing in critical care settings. Journal of Diabetes Science and Technology 2(3):194-200. |
| Kurnik et al. 1999. Application of the mixtures of experts algorithm for signal processing in a noninvasive glucose monitoring system. Sensors and Actuators B 60:19-26. |
| Kurtz et al. 2005. 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 . . . Hypertension 45:299-310. |
| Ladd et al., 1996. Structure Determination by X-ray Crystallography, 3rd ed. Plenum, 1996, Ch. 1, pp. xxi-xxiv and 1-58. |
| Lee et al. May 2007. Combined Insulin Pump Therapy with Real-time Continuous Glucose Monitoring Significantly Improves Glycemic Control Compared to Multiple Daily Injection Therapy in Pump Naive Patients with Type 1 Diabetes; Single Center Pilot Study Experience. J Diabetes Science & Technology 1(3): 400-404. |
| Lehmann et al. May 1994. Retrospective valication of a physiological model of glucose-iunsulin interaaction in tyhpe 1 diabetes mellitus. Med. Eng. Phys. 16:193-202. |
| Lerner et al. 1984. An implantable electrochemical glucose sensor. Ann. N. Y. Acad. Sci. 428:263-278. |
| Lewandowski et al. 1988. Evaluation of a miniature blood glucose sensor. Trans Am Soc Artif Intern Organs 34:255-258. |
| Leypoldt et al. 1984. Model of a two-substrate enzyme electrode for glucose. Analytical Chemistry 56:2896-2904. |
| Linke et al. 1994. Amperometric biosensor for in vivo glucose sensing based on glucose oxidase immobilized in a redox hydrogel. Biosensors & Bioelectronics 9:151-158. |
| Lowe, 1984. Biosensors. Trends in Biotechnology, 2(3):59-65. |
| Luong et al. 2004. Solubilization of Multiwall Carbon Nanotubes by 3-Aminopropyltriethoxysilane Towards the Fabrication of Electrochemical Biosensors with Promoted Electron Transfer. Electronanalysis 16( 1-2): 132-139. |
| Lyandres et al. 2008. Progress toward an in vivo surface-enhanced raman spectroscopy glucose sensor. Diabetes Technology & Therapeutics 10(4): 257-265. |
| Lynch et al. 2001. Estimation-based model predictive control of blood glucose in type I diabetics: A simulation study. Proceedings of the IEEE 27th Annual Northeast Bioengineering Conference, pp. 79-80. |
| Maidan et al. 1992. Elimination of Electrooxidizable Interferent-Produced Currents in Amperometric Biosensors. Analytical Chemistry, 64:2889-2896. |
| Makale et al. 2003. Tissue window chamber system for validation of implanted oxygen sensors. Am. J. Physiol. Heart Circ. Physiol. 284:H2288-2294. |
| Malin et al. 1999. Noninvasive Prediction of Glucose by Near-Infrared Diffuse Reflectance Spectroscopy. Clinical Chemistry 45:9, 1651-1658. |
| Maran et al. 2002. Continuous subcutaneous glucose monitoring in diabetic patients: A multicenter analysis. Diabetes Care 25(2):347-352. |
| March, W. F. 2002. Dealing with the delay. Diabetes Technology & Therapeutics 4(1):49-50. |
| Marena et al. 1993. The artifical endocrine pancreas in clinical practice and research. Panminerva Medica 35(2):67-74. |
| Martin, R. F. 2000. General Deming regression for estimating systematic bias and its confidence interval in method-comparison studies. Clinical Chemistry 46(1):100-104. |
| Mascini et al. 1989. Glucose electrochemical probe with extended linearity for whole blood. J Pharm Biomed Anal 7(12): 1507-1512. |
| Mastrototaro et al. 1991. An electroenzymatic glucose sensor fabricated on a flexible substrate. Sensors and Actuators B, 5:139-44 (1991). |
| Mastrototaro et al. 2003. Reproducibility of the continuous glucose monitoring system matches previous reports and the intended use of the product. Diabetes Care 26:256; author reply p. 257. |
| Mastrototaro, J. J. 2000. The MiniMed continuous glucose monitoring system. Diabetes Technology & Therapeutics 2(Suppl 1 ):S13-8. |
| Matsumoto et al. 1998. A micro-planar amperometric glucose sensor unsusceptible to interference species. Sensors and Actuators B 49:68-72. |
| Matthews et al. 1988. An amperometric needle-type glucose sensor testing in rats and man. Diabetic Medicine 5:248-252. |
| Mazze et al. 2008. Characterizing glucose exposure for individuals with normal glucose tolerance using continuous glucose monitoring and ambulatory glucose profile analysis. Diabetes Technology & Therapeutics 10:149-159. |
| McCartney et al. 2001. Near-infrared fluorescence lifetime assay for serum glucose based on allophycocyanin-labeled concanavalin A. Anal Biochem 292:216-221. |
| McGrath et al. 1995. The use of differential measurements with a glucose biosensor for interference compensation during glucose determinations by flow injection analysis. Biosensors & Bioelectronics 10:937-943. |
| McKean, et al. Jul. 7, 1988. A Telemetry Instrumentation System for Chronically Implanted Glucose and Oxygen Sensors. Transactions on Biomedical Engineering 35:526-532. |
| Memoli et al. 2002. A comparison between different immobilised glucoseoxidase-based electrodes. J Pharm Biomed Anal 29:1045-1052. |
| Merriam-Webster Online Dictionary, Definition of “acceleration”. http:--www.merriam-webster.com-dictionary-Acceleration Jan. 11, 2010. |
| Merriam-Webster Online Dictionary. Definition of “system”. http:--www.merriam-webster.com-dictionary-System Jan. 11, 2010. |
| Merriam-Webster Online Dictionary. The term “nominal.” http:--www.m-w.com-dictionary-nominal. |
| Meyerhoff et al. 1992. On line continuous monitoring of subcutaneous tissue glucose in men by combining portable glucosensor with microdialysis. Diabetologia 35:1087-1092. |
| Moatti-Sirat et al. 1992. Towards continuous glucose monitoring: in vivo evaluation of a miniaturized glucose sensor implanted for several days in rat subcutaneous tissue. Diabetologia 35:224-230. |
| Moatti-Sirat et al. 1994. Reduction of acetaminophen interference in glucose sensors by a composite Nafion membrane: demonstration in rats and man. Diabetologia 37(6):610-616, Jun. 1994. |
| Moatti-Sirat, D et al. 1992. Evaluating in vitro and in vivo the interference of ascorbate and acetaminophen on glucose detection by a needle-type glucose sensor. Biosensors and Bioelectronics 7:345-352. |
| Monsod et al. 2002. Do sensor glucose levels accurately predict plasma glucose concentrations during hypoglycemia and hyperinsulinemia? Diabetes Care 25(5):889-893. |
| Morff et al. 1990. Microfabrication of reproducible, economical, electroenzymatic glucose sensors. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 12(2):0483-0484. |
| Mosbach et al. 1975. Determination of heat changes in the proximity of immobilized enzymes with an enzyme termistor and its use for the assay of metabolites. Biochimica et Biophysica Acta. (Enzymology) 403:256-265. |
| Motonaka et al. 1993. Determination of cholesterol and cholesterol ester with novel enzyme microsensors. Analytical Chemistry 65:3258-3261. |
| Moussy et al. 1993. Performance of subcutaneously implanted needle-type glucose sensors employing a novel trilayer coating. Analytical Chemistry 85: 2072-2077. |
| Moussy, Francis, Nov. 2002. Implantable Glucose Sensor: Progress and Problems. Sensors 1:270-273. |
| Murphy, et al. 1992. Polymer membranes in clinical sensor applications, II. The design and fabrication of permselective hydrogels for electrochemical devices. Biomaterials 13(14):979-990. |
| Muslu. 1991. Trickling filter performance. Applied Biochemistry and Biotechnology 37:211-224. |
| Nafion® 117 Solution Product Description, Product No. 70160, Sigma-Aldrich Corp., St. Louis, MO. |
| NewsRx Aug. 3, 2003. Medical Letter on the CDC & FDA via NewsRx,com. “Glucose Monitoring: FDA OKs new device to manage diabetes”. |
| Ohara et al. 1994. “Wired” enzyme electrodes for amperometric determination of glucose or lactate in the presence of interfering substances. Analytical Chemistry 66:2451-2457. |
| Ohara, et al. Dec. 1993. Glucose electrodes based on cross-linked bis(2,2′-bipyridine)chloroosmium(+-2+) complexed poly(I-vinylimidazole) films, Analytical Chemisty, 65:3512-3517. |
| Okuda et al. 1971. Mutarotase effect on micro determinations of D-glucose and its anomers with (3-D-glucose oxidase. Analytical Biochemistry 43:312-315. |
| Oxford English Dictionary Online, Definition of “impending”. http:--www.askoxford.com-results-?view=dev dict&field-12668446 Impending&branch= 1-11-2010. |
| Palmisano et al. 2000. Simultaneous monitoring of glucose and lactate by an interference and crosstalk free dual electrode amperometric biosensor based on electropolymerized thin films. Biosensors & Bioelectronics 15:531-539. |
| Patel et al. 2003. Amperometric glucose sensors based on ferrocene containing polymeric electron transfer systems—a preliminary report, Biosensors & Bioelectronics 18:1073-6. |
| Peacock et al. 2008. Cardiac troponin and outcome in acute heart failure. N. Engl. J. Med., 358: 2117-2126. |
| Pfeiffer et al. 1992. On line continuous monitoring of subcutaneous tissue glucose is feasible by combining portable glucosensor with microdialysis. Horm. Metab. Res. 25:121-124. |
| Pfeiffer, E.F. 1990. The glucose sensor: the missing link in diabetes therapy. Horm Metab Res Suppl. 24:154-164. |
| Pichert et al. 2000. Issues for the coming age of continuous glucose monitoring. Diabetes Educator 26(6):969-980. |
| Pickup et al. 1987-88. Implantable glucose sensors: choosing the appropriate sensor strategy. Biosensors 3:335-346 (1987-88). |
| Pickup et al. 1989. In vivo molecular sensing in diabetes mellitus: an implantable glucose sensor with direct electron transfer. Diabetologia 32:213-217 (1989). |
| Pickup et al. 1989. Potentially-implantable, amperometric glucose sensors with mediated electron transfer: improving the operating stability. Biosensors 4:109-119. |
| Pickup et al. 1993. Developing glucose sensors for in vivo use. Elsevier Science Publishers Ltd (UK), TIBTECH vol. 11: 285-291. |
| Pickup et al, 1993. Responses and Calibration of Amperometric Glucose Sensors Implanted in the Subcutaneous Tissue of Man. ACTA Diabetologia pp. 143-148. |
| Pinner et al. 1959. Cross-linking of cellulose acetate by ionizing radiation. Nature, 184:1303-1304. |
| Pishko et al. 1991. Amperometric glucose microelectrodes prepared through immobilization of glucose oxidase in redox hydrogels. Analytical Chemistry 63:2268-72. |
| Pitzer et al. 2001. Detection of hypoglycemia with the GlucoWatch biographer. Diabetes Care 24(5):881-885. |
| Poitout et al. 1993. 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 36:658-663. |
| Poitout et al. 1994. Development of a glucose sensor for glucose monitoring in man: the disposable implant concept. Clinical Materials 15:241-246. |
| Poitout, et al. 1991. In Vitro and In Vivo Evaluation in Dogs of a Miniaturized Glucose Sensor. ASAIO Transactions, 37:M298-M300. |
| Poitout, et al. 1991. In Vitro and In Vivo Evaluation in Dogs of a Miniaturized Glucose Sensor. ASAIO Transactions 37:M298-M300. |
| Postlethwaite et al. 1996. Interdigitated array electrode as an alternative to the rotated ring-disk electrode for determination of the reaction products of dioxygen reduction. Analytical Chemistry 68:2951-2958. |
| Prabhu et al. 1981. Electrochemical studies of hydrogen peroxide at a platinum disc electrode. Electrochimica Acta 26(6):725-729. |
| Quinn et al. 1995. Kinetics of glucose delivery to subcutaneous tissue in rats measured with 0.3-mm amperometric microsensors. The American Physiological Society E155-E161. |
| Quinn et al. 1997. Biocompatible, glucose-permeable hydrogel for in situ coating of implantable biosensors. Biomaterials 18:1665-1670. |
| Rabahetal., 1991. Electrochemical wear of graphite anodes during electrolysis of brine. Carbon 29(2)165-171. |
| Rafael, Ehab 1999. Cell Transplantation and Immunoisolation: Studies on a macroencapsulation device, Departments of Transplantation Surgery and Pathology, Karolinska Institutet, Huddinge Hospital, Stockholm, Sweden (1999) pp. 1-82. |
| Reach et al. 1986. A Methed for Evaluating in vivo the Functional Characteristics of Glucose Sensors. Biosensors 2:211-220. |
| Reach et al. 1992. Can continuous glucose monitoring be used for the treatment of diabetes? Analytical Chemistry 64(5) :381-386. |
| Reach, G. 2001. Which threshold to detect hypoglycemia? Value of receiver-operator curve analysis to find a compromise between sensitivity and specificity. Diabetes Care 24(5):803-804. |
| Reach, Gerard. 2001. Letters to the Editor Re: Diabetes Technology & Therapeutics, 2000;2:49-56. Diabetes Technology & Therapeutics 3(1): 129-130. |
| Rebrin et al. 1989. Automated feedback control of subcutaneous glucose concentration in diabetic dogs. Diabetologia 32:573-76 (1989). |
| Rebrin et al. 1992. Subcutaneous glucose monitoring by means of electrochemical sensors: fiction or reality? J. Biomed. Eng. 14:33-40. |
| Renard, Eric, 2002. Current Opinion in Pharmacology 2:708-716. Implantable closed-loop glucose sensing and insulin delivery: the future for insulin pump therapy. |
| Reusch, 2004, Chemical Reactivity. Organometallic Compounds. Virtual Textbook of Organic Chem. pp. 1-16, http:--www.cem.msu.edu-˜reusch-VirtualText-orgmetal.htm. |
| Rhodes et al. 1994. Prediction of pocket-portable and implantable glucose enzyme electrode performance from combined species permeability and digital simulation analysis. Analytical Chemistry 66(9): 1520-1529. |
| Rigla et al. 2008. Real-time continuous glucose monitoring together with telemedical assitance improves glycemic control and glucose stability in pump-treated patients. Diabetes Technology & Therapeutics, 10:194-199. |
| Rinken et al. 1998. Calibration of glucose biosensors by using pre-steady state kinetic data. Biosensors & Bioelectronics 13:801-807. |
| Ristic et al. 2003. Review: Effects of Rapid-acting Insulin Analogs on Overall Glycemic Control in Type 1 and Type 2 Diabetes Mellitus. Diabetes Technology & Therapeutics 5(1): 57-66. |
| Rivers et al. 2001. Central venous oxygen saturation monitoring in the critically ill patient. Current Opinion in Critical Care 7:204-211, 2001. |
| Sakakida et al. 1992. Development of Ferrocene-Mediated Needle-Type Glucose Sensor as a Measure of True Subcutaneous Tissue Glucose Concentrations. Artif. Organs Today 2(2): 145-158. |
| Sakakida et al. 1993. Ferrocene-Mediated Needle Type Glucose Sensor Covered with Newly Designed Biocompatible Membrane. Sensors and Actuators B 13-14:319-322. |
| Salardi et al. 2002. The glucose area under the profiles obtained with continuous glucose monitoring system relationships with HbA1c in pediatric type 1 diabetic patients. Diabetes Care 25(10): 1840-1844. |
| Samuels, M.P. 2004. The effects of flight and altitude. Arch Dis Child, 89; 448-455. |
| San Diego Plastics, Inc. 2009. Polyethylene Data Sheet, http:--www.sdplastics.com-polyeth.html. |
| Sansen et al. 1990. A smart sensor for the voltammetric measurement of oxygen or glucose concentrations. Sensors and Actuators B 1:298-302. |
| Sansenetal. 1985. Glucose sensor with telemetry system. In Ko, W. H. (Ed.). Implantable Sensors for Closed Loop Prosthetic Systems. Chap. 12, pp. 167-175, Mount Kisco, NY: Futura Publishing Co. |
| Schmidt et al. 1993. Glucose concentration in subcutaneous extracellular space. Diabetes Care 16(5):695-700. |
| Schmidtke et al. 1998. Measurement and modeling of the transient difference between blood and subcutaneous glucose concentrations in the rat after injection of insulin. Proc Natl Acad Sci USA 1998, 95, 294-299. |
| Schoemaker et al. 2003. The SCGM1 system: Subcutaneous continuous glucose monitoring based on microdialysis technique. Diabetes Technology & Therapeutics 5(4):599-608. |
| Schoonen et al. 1990 Development of a potentially wearable glucose sensor for patients with diabetes mellitus: design and in-vitro evaluation. Biosensors & Bioelectronics 5:37-46. |
| Selam, J. L. 1997. Management of diabetes with glucose sensors and implantable insulin pumps. From the dream of the 60s to the realities of the 90s. ASAIO J 43:137-142. |
| Service et al. 1970. Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes, 19: 644-655. |
| Service et al. 1987, Measurements of glucose control. Diabetes Care, 10: 225-237. |
| Service, R. F. 2002. Can sensors make a home in the body? Science 297:962-3. |
| Sharkawy et al. 1996. Engineering the tissue which encapsulates subcutaneous implants. I. Diffusion properties. J Biomed Mater Res, 37:401-412. |
| Shaw et al. 1991. In vitro testing of a simply constructed, highly stable glucose sensor suitable for implantation in diabetic patients. Biosensors & Bioelectronics 6:401-406 (1991). |
| Shichiri et al. 1982. Wearable artificial endocrine pancreas with needle-type glucose sensor. Lancet 2:1129-1131. |
| Shichiri et al. 1983. Glycaemic Control in Pancreatectomized Dogs with a Wearable Artificial Endocrine Pancreas. Diabetologia 24:179-184. |
| Shichiri et al. 1985. Needle-type Glucose Sensor for Wearable Artificial Endocrine Pancreas, in Implantable Sensors for Closed-Loop Prosthetic Systems, Ed. Ko, Futura Publishing Company, Inc., Mount Kisco, NY, pp. 197-210. |
| Shichiri et al. 1986. Telemetry Glucose Monitoring Device with Needle-Type Glucose Sensor: A Useful Tool for Blood Glucose Monitoring in Diabetic Individuals. Diabetes Care 9(3):298-301. |
| Shichiri et al., 1989. Membrane Design for Extending the Long-Life of an Implantable Glucose Sensor. Diab. Nutr. Metab. 2:309-313. |
| Shults et al. 1994. A telemetry-instrumentation system for monitoring multiple subcutaneously implanted glucose sensors. I EEE Transactions on Biomedical Engineering 41(10):937-942. |
| Skyler, J. S. 2000. The economic burden of diabetes and the benefits of improved glycemic control: The potential role of a continuous glucose monitoring system. Diabetes Technology & Therapeutics 2(Suppl 1):S7-12. |
| Slater-Maclean et al. 2008. Accuracy of glycemic measurements in the critically ill. Diabetes Technology & Therapeutics 10:169-177. |
| Smith et al. 1991. A Comparison of Islet Transplantation and Subcutaneous Insulin Injections for the Treatment of Diabetes Mellitus. Comput Biol Med. 21(6): 417-427. |
| Sokol et al. 1980,, Immobilized-enzyme rate-determination method for glucose analysis. Clinical Chomistry 26(1):89-92. |
| Sriyudthsak et al. 1996. Enzyme-epoxy membrane based glucose analyzing system and medical applications. Biosensors & Bioelectronics 11:735-742. |
| Steil et al. 2003. Determination of plasma glucose during rapid glucose excursions with a subcutaneous glucose sensor. Diabetes Technology & Therapeutics 5(1 ):27-31. |
| Stern et al., 1957. Electrochemical polarization: 1. A theoretical analysis of the shape of polarization curves. Journal of the Electrochemical Society 104(1 ):56-63. |
| Sternberg et al. 1988. Study and Development of Multilayer Needle-type Enzyme-based Glucose Microsensors. Biosensors 4:27-40. |
| Sternberg et al, 1996. Does fall in tissue glucose precede fall in blood glucose? Diabetologia 39:609-612. |
| Street et al. Dec. 2004. Islet Graft Assessment in the Edmonton Protocol: Implications for Predicting Long-Term Clinical Outcome. Diabetes, 53: 3107-3114. |
| Sumino T. et al. 1998. Preliminary study of continuous glucose monitoring with a microdialysis technique. Proceedings of the IEEE, 20(4):1775-1778. |
| Takegami et al. 1992. Pervaporation of ethanol water mixtures using novel hydrophobic membranes containing polydimethylsiloxane, Journal of Membrane Science, 75(93-105). |
| Tanenberg et al. 2000. Continuous glucose monitoring system: A new approach to the diagnosis of diabetic gastroparesis. Diabetes Technology & Therapeutics, 2(Suppl 1):S73-80. |
| Tatsuma et al. 1991. Oxidase-peroxidase bilayer-modified electrodes as sensors for lactate, pyruvate, cholesterol and uric acid. Analytica Chimica Acta, 242:85-89. |
| Thennadil et al. 2001. Comparison of Glucose Concentration in Interstitial Fluid, and Capillary and Venous Blood During Rapid Changes in Blood Glucose Levels. Diabetes Technology & Therapeutics 3(3): 357-365. |
| Thome et al. 1995.—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. 27:53. |
| Thome-Duret et al. 1996. Modification of the sensitivity of glucose sensor implanted into subcutaneous tissue. Diabetes Metabolism 22:174-178. |
| Thome-Duret et al. 1996. Use of a subcutaneous glucose sensor to detect decreases in glucose concentration prior to observation in blood. Analytical Chemistry 68:3822-3826. |
| Thome-Duret et al. 1998. Continuous glucose monitoring in the free-moving rat. Metabolism 47:799-803. |
| Thompson et al. 1986. In Vivo Probes: Problems and Perspectives. Department of Chemistry, University of Toronto, Canada, pp. 255-261, 1986. |
| Tierney et al. 2000. Effect of acetaminophen on the accuracy of glucose measurements obtained with the GlucoWatch biographer. Diabetes Technology & Therapeutics 2:199-207. |
| Tierney et al. 2000. The GlucoWatch® biographer: A frequent, automatic and noninvasive glucose monitor. Ann. Med. 32:632-641. |
| Tilbury et al. 2000. Receiver operating characteristic analysis for intelligent medical systems—A new approach for finding confidence intervals. IEEE Transactions on Biomedical Engineering 47(7):952-963. |
| Torjman et al. 2008. Glucose monitoring in acute care: technologies on the horizon. Journal of Deabetes Science and Technology 2(2):178-181. |
| Trajanoski et al. 1998. Neural predictive controller for insulin delivery using the subcutaneous route. IEEE Transactions on Biomedical Engineering 45(9):1122-1134. |
| Trecroci, D. 2002. A Glimpse into the Future—Continuous Monitoring of Glucose with a Microfiber. Diabetes Interview 42-43. |
| Tse and Gough. 1987. Time-Dependent Inactivation of Immobilized Glucose Oxidase and Catalase. Biotechnol. Bioeng. 29:705-713. |
| Turner and Pickup 1985, Diabetes mellitus: biosensors for research and management. Biosensors 1:85-115(1985). |
| Turner et al. 1984. Carbon Monoxide: Acceptor Oxidoreductase from Pseudomonas Thermocarboxydovorans Strain C2 and its use in a Carbon Monoxide Sensor. Analytica Chimica Acta, 163: 161-174. |
| Unger et al. 2004. Glucose control in the hospitalized patient. Emergency Medicine 36(9): 12-18. |
| Updike et al. 1967. The enzyme electrode. Nature 214:986-988. |
| Updike et al. 1979. Continuous glucose monitor based on an immobilized enzyme electrode detector. J Lab Clin Med, 93(4):518-527. |
| Updike et al. 1982. Implanting the glucose enzyme electrode: Problems, progress, and alternative solutions. Diabetes Care 5(3):207-212. |
| Updike et al. 1988. Laboratory Evaluation of New Reusable Blood Glucose Sensor Diabetes Care 11:801-807. |
| Updike et al. 1994. Enzymatic glucose sensor: Improved long-term performance in vitro and in vivo. ASAIO Journal 40(2): 157-163. |
| Updike et al. 1997, Principles of long-term fully implanted sensors with emphasis on radiotelemetric monitoring of blood glucose form inside a subcutaneous foreign body capsule (FBC). In Fraser, ed., Biosensors in the Body. New York. John Wiley & Sons. |
| Updike et al. 1997. Principles of long-term fully implanted sensors with emphasis on radiotelemetric monitoring of blood glucose form inside a subcutaneous foreign body capsule (FBC). In Fraser, ed., Biosensors in the Body. New York. John Wiley & Sons, pp. 117-137. |
| Updike et al. 2000. A subcutaneous glucose sensor with improved longevity, dynamic range, and stability of calibration. Diabetes Care 23(2):208-214. |
| Utah Medical Products Inc., Blood Pressure Transducers product specifications. 6 pp. 2003-2006, 2003. |
| Vadgama, P. Nov. 1981. Enzyme electrodes as practical biosensors. Journal of Medical Engineering & Technology 5(6):293-298. |
| Vadgama. 1988. Diffusion limited enzyme electrodes. NATO ASI Series: Series C, Math and Phys. Sci. 226:359-377. |
| Van den Berghe 2004. Tight blood glucose control with insulin in “real-life” intensive care. Mayo Clin Proc 79(8):977-978. |
| Velho et al. 1989. In vitro and in vivo stability of electrode potentials in needle-type glucose sensors. Influence of needle material. Diabetes 38:164-171. |
| Velho et al. 1989. Strategies for calibrating a subcutaneous glucose sensor. Biomedica et Biochimica Acta 48(11-12):957-964. |
| Vesper et al. 2006. Assessment of Trueness of a Glucose Monitor Using Interstitial Fluid and Whole Blood as Specimen Matrix. Diabetes Technology & Therapeutics 8(1): 76-80. |
| von Woedtke et al. 1989. In situ calibration of implanted electrochemical glucose sensors. Biomedica et Biochimica Acta 48(11-12):943-952. |
| Wagner et al. 1998. Continuous amperometric monitoring of glucose in a brittle diabetic chimpanzee with a miniature subcutaneous electrode. Proc. Natl. Acad. Sci. A 95:6379-6382. |
| Wang et al. 1994. Highly Selective Membrane-Free, Mediator-Free Glucose Biosensor, Analytical Chemistry 66:3600-3603. |
| Wang et al. 1997. Improved ruggedness for membrane-based amperometric sensors using a pulsed amperometric method. Analytical Chemistry, 69:4482-4489. |
| Ward et al. 2000. Rise in background current over time in a subcutaneous glucose sensor in the rabbit: Relevance to calibration and accuracy. Biosensors & Bioelectronics 15:53-61. |
| Ward et al. 2000. Understanding Spontaneous Output Fluctuations of an Amperometric Glucose Sensor: Effect of Inhalation Anesthesia and of a Nonenzyme Containing Electrode. ASAIO Journal 540-546. |
| Ward et al. 2002. A new amperometric glucose microsensor: In vitro and short-term in vivo evaluation. Biosensors & Bioelectronics 17:181-189. |
| Wardetal. 1999. Assessment of chronically implanted subcutaneous glucose sensors in dogs: The effect of surrounding fluid masses. ASAIO Journal 45:555-561. |
| Wentholt et al. 2007. Relationship between Interstitial and Blood Glucose in Type 1 Diabetes Patients: Delay and the Push-pull Phenomenon Revisited. Diabetes Technology & Therapeutics 9(2):169-175. |
| Wientjes, K. J. C. 2000. Development of a glucose sensor for diabetic patients (Ph.D. Thesis). |
| Wikipedia 2006. “Intravenous therapy,” http:--en.wikipedia.org-wiki-Intravenous_therapy, Aug. 15, 2006, 6 pp. |
| Wiley Electrical and Electronics Engineering Dictionary. 2004. John Wiley & Sons, Inc. pp. 141, 142, 548, 549. |
| Wilkins et al. 1988. The coated wire electrode glucose sensor. Horm Metab Res Suppl., 20:50-55. |
| Wilkins et al. 1995. Glucose monitoring: state of the art and future possibilities. Med Eng Phys 18:273-288. |
| Wilkins et al. 1995. Integrated implantable device for long-term glucose monitoring, Biosensors & Bioelectronics 10:485-494. |
| Wilson et al. 1992. Progress toward the development of an implantable sensor for glucose. Clinical Chemistry 38(9):1613-1617. |
| Wilson et al. 2000. Enzyme-based biosensors for in vivo measurements. Chem. Rev., 100:2693-2704. |
| Wolpert, Howard A. 2003. A Clinician's Perspective on Some of the Challenges in “Closing the Loop”. Diabetes Technology & Therapeutics 5(5):843-846. |
| Wood, W. et al. Mar. 1990. Hermetic Sealing with Epoxy. Mechanical Engineering 1-3. |
| Woodward. 1982. How Fibroblasts and Giant Cells Encapsulate Implants: Considerations in Design of Glucose Sensor. Diabetes Care 5:278-281. |
| Worsley et al. 2008. Measurement of glucose in blood with a phenylboronic acid optical sensor. Journal of Diabetes Science and Technology, 2(2):213-220, Mar. 2008. |
| Wright et al. 1999. Bioelectrochemical dehalogenations via direct electrochemistry of poly(ethylene oxide)-modified myoglobin. Electrochemistry Communications 1:603-611. |
| Wu et al. 1999. In situ electrochemical oxygen generation with an immunoisolation device. Annals New York Academy of Sciences, pp. 105-125. |
| Yamasaki et al. 1989. Direct measurement of whole blood glucose by a needle-type sensor. Clinica Chimica Acta. 93:93-98. |
| Yamasaki, Yoshimitsu. Sep. 1984. The development of a needle-type glucose sensor for wearable artificial endocrine pancreas. Medical Journal of Osaka University 35(1-2):25-34. |
| Yang et al 1996. A glucose biosensor based on an oxygen electrode: In-vitro performances in a model buffer solution and in blood plasma. Biomedical Instrumentation & Technology 30:55-61. |
| Yang et al. 1998. Development of needle-type glucose sensor with high selectivity. Science and Actuators B 46:249-256. |
| Yang, et al. 2004. A Comparison of Physical Properties and Fuel Cell Performance of Nafion and Zirconium Phosphate-Nafion Composite Membranes. Journal of Membrane Science 237:145-161. |
| Ye et al. 1993. High Current Density ‘Wired ’ Quinoprotein Glucose Dehydrogenase Electrode. Analytical Chemistry 65:238-241. |
| Zamzow et al. 1990. Development and evaluation of a wearable blood glucose monitor. ASAIO Transactions 36:M588-M591. |
| Zethelius et al. 2008. Use of multiple biomarkers to improve the prediction of death from cardiovascular causes. N. Engl. J. Med., 358: 2107-2116. |
| Zhang et al 1993. Electrochemical oxidation of H2O2 on Pt and Pt + Ir electrodes in physiological buffer and its applicability to H202-based biosensors. J. Electroanal. Chem., 345:253-271. |
| Zhang et al. 1993. In vitro and in vivo evaluation of oxygen effects on a glucose oxidase based implantable glucose sensor. Analytica Chimica Acta, 281:513-520. |
| Zhang et al. 1994. Elimination of the acetaminophen interference in an implantable glucose sensor. Analytical Chemistry 66(7): 1183-1188. |
| Zhu et al. 1994. Fabrication and characterization of glucose sensors based on a microarray H2O2 electrode. Biosensors & Bioelectronics 9: 295-300. |
| Zhu et al. 2002. Planar amperometric glucose sensor based on glucose oxidase immobilized by chitosan film on prussian blue layer. Sensors 2:127-136. |
| EP 05723951.9: EPO Communication dated Jan. 28, 2011. |
| EP 05723951.9: EPO Communication dated Oct. 10, 2008. |
| EP 05723951.9: EPOCommunication dated Nov. 21, 2007. |
| EP 05723951.9: European Examination Report dated Feb. 20, 2012w. |
| EP 05723951.9: Response filed Jun. 28, 2012. |
| EP 10163654.6: EPO Summons dated Oct. 11, 2012 to Attend Oral Hearing. |
| EP 10163654.6: EPO Communication dated Aug. 3, 2010. |
| EP 10163675.1: EPO Communication dated Aug. 3, 2010. |
| EP 10163675.1: EPO Communication dated Mar. 17, 2011. |
| EP 98908875.2: European Search Report dated Apr. 29, 2004. |
| JP 2007-500777: JPO Communication dated Aug. 17, 2010. |
| JP 2007-500777: JPO Decision on Appeal, dated Jul. 24, 2012. |
| PCT/US2005/006301: International Preliminary Report on Patentability dated Sep. 8, 2006. |
| PCT/US2005/006301: International Search Report and Written Opinion dated Jun. 22, 2005. |
| PCT/US2007/080848: International Preliminary Report on Patentability dated Apr. 22, 2010. |
| PCT/US2007/080848: International Search Report and Written Opinion dated Aug. 28, 2008. |
| U.S. Control No. 95/001038 re Inter Partes Reexamination of U.S. Pat. No. 7,276,029: Office Action dated Jun. 17, 2008. |
| U.S. Control No. 95/001039 re Inter Partes Reexamination of U.S. Pat. No. 6,931,327: Office Action dated May 29, 2008. |
| U.S. Control No. 95/001818 re Inter Partes Reexamination of U.S. Pat. No. 7,591,801: Partial Electronic File History, including Reexamination Request dated Nov. 11, 2011, Office Actions dated Nov. 25, 2011, Dec. 21, 2011, Aug. 23, 2012, Oct. 3, 2012, Dec. 19, 2012 and Feb. 8, 2013, Third Party Submissions dated Jan. 23, 2012, Feb. 21, 2012 and Apr. 19, 2012, and Patent Owner Responses filed Feb. 6, 2012, Mar. 20, 2012, Jul. 17, 2012, and Oct. 31, 2012. |
| U.S. Appl. No. 09/636,369: Office Action dated Sep. 30, 2002. |
| U.S. Appl. No. 10/632,537: Office Action dated Oct. 20, 2004. |
| U.S. Appl. No. 10/632,537: Office Action dated Dec. 21, 2004. |
| U.S. Appl. No. 10/633,329: Office Action dated Feb. 4, 2008. |
| U.S. Appl. No. 10/633,329: Office Action dated Oct. 5, 2006. |
| U.S. Appl. No. 10/633,329: Office Action dated Jun. 12, 2008. |
| U.S. Appl. No. 10/633,329: Office Action dated Mar. 26, 2007. |
| U.S. Appl. No. 10/633,329: Office Action dated Jul. 30, 2007. |
| U.S. Appl. No. 10/633,367: Office Action dated Jul. 15, 2008. |
| U.S. Appl. No. 10/633,404: Office Action dated Feb. 12, 2007. |
| U.S. Appl. No. 10/789,359, granted on Sep. 22, 2009 as U.S. Pat. No. 7,591,801: Office Action dated Oct. 3, 2008. |
| U.S. Appl. No. 10/789,359, granted on Sep. 22, 2009 as U.S. Pat. No. 7,591,801: Office Action dated Mar. 20, 2008. |
| U.S. Appl. No. 10/789,359, granted on Sep. 22, 2009 as U.S. Pat. No. 7,591,801: Office Action dated Nov. 27, 2006. |
| U.S. Appl. No. 10/789,359, granted on Sep. 22, 2009 as U.S. Pat. No. 7,591,801: Partial Electronic File History, including Office Action dated Aug. 9, 2006, Nov. 27, 2006, Mar. 20, 2008, Oct. 3, 2008, Feb. 24, 2009, Mar. 30, 2009, Apr. 22, 2009, Apr. 23, 2009, and Jul. 15, 2009, and Applicant Responses filed Aug. 31, 2006, Feb. 6, 2007, May 28, 2008, Nov. 24, 2008, Mar. 31, 2009, and Apr. 22, 2009. |
| U.S. Appl. No. 10/838,909: Office Action dated Jun. 5, 2008. |
| U.S. Appl. No. 10/896,772: Office Action dated Jan. 11, 2005. |
| U.S. Appl. No. 10/896,772: Office Action dated Dec. 14, 2005. |
| U.S. Appl. No. 10/896,772: Office Action dated Jul. 19, 2005. |
| U.S. Appl. No. 10/896,772: Office Action dated May 22, 2006. |
| U.S. Appl. No. 10/991,966: Office Action dated Jul. 22, 2008. |
| U.S. Appl. No. 10/991,966: Office Action dated Nov. 28, 2007. |
| U.S. Appl. No. 11/007,635: Office Action dated Jan. 27, 2006. |
| U.S. Appl. No. 11/007,920: Office Action dated Jun. 24, 2008. |
| U.S. Appl. No. 11/034,344: Office Action dated Jan. 15, 2008. |
| U.S. Appl. No. 11/038,340: Office Action dated Jun. 17, 2008. |
| U.S. Appl. No. 11/077,714: Office Action dated Apr. 10, 2007. |
| U.S. Appl. No. 11/077,714: Office Action dated Jan. 10, 2008. |
| U.S. Appl. No. 11/077,714: Office Action dated Oct. 11, 2006. |
| U.S. Appl. No. 11/077,714: Office Action dated Apr. 16, 2009. |
| U.S. Appl. No. 11/077,714: Office Action dated Sep. 16, 2008. |
| U.S. Appl. No. 11/077,714: Office Action dated Jan. 27, 2010. |
| U.S. Appl. No. 11/077,714: Office Action dated Jul. 27, 2007. |
| U.S. Appl. No. 11/077,714: Office Action dated Dec. 31, 2009. |
| U.S. Appl. No. 11/077,740: Office Action dated Jun. 1, 2007. |
| U.S. Appl. No. 11/077,740: Office Action dated Nov. 1, 2007. |
| U.S. Appl. No. 11/077,740: Office Action dated Feb. 7, 2008. |
| U.S. Appl. No. 11/077,759: Office Action dated Jul. 10, 2008. |
| U.S. Appl. No. 11/077,759: Office Action dated May 17, 2007. |
| U.S. Appl. No. 11/077,759: Office Action dated May 26, 2009. |
| U.S. Appl. No. 11/077,759: Office Action dated Mar. 31, 2008. |
| U.S. Appl. No. 11/077,765: Office Action dated May 16, 2008. |
| U.S. Appl. No. 11/077,765: Office Action dated Sep. 19, 2008. |
| U.S. Appl. No. 11/077,765: Office Action dated Dec. 31, 2007. |
| U.S. Appl. No. 11/078,072: Office Action dated Sep. 2, 2009. |
| U.S. Appl. No. 11/078,072: Office Action dated Feb. 18, 2010. |
| U.S. Appl. No. 11/078,232: Office Action dated Jan. 5, 2010. |
| U.S. Appl. No. 11/078232: Office Action dated Mar. 5, 2009. |
| U.S. Appl. No. 11/078,232: Office Action dated May 5, 2008. |
| U.S. Appl. No. 11/078,232: Office Action dated Nov. 12, 2008. |
| U.S. Appl. No. 11/078,232: Office Action dated Jul. 21, 2009. |
| U.S. Appl. No. 11/157,365: Office Action dated Jan. 7, 2009. |
| U.S. Appl. No. 11/157,365: Office Action dated Jan. 21, 2010. |
| U.S. Appl. No. 11/157,365: Office Action dated Jul. 21, 2009. |
| U.S. Appl. No. 11/157,365: Office Action dated Jun. 26, 2008. |
| U.S. Appl. No. 11/333,837: Office Action dated Nov. 28, 2008. |
| U.S. Appl. No. 11/333,837: Office Action dated Jun. 29, 2009. |
| U.S. Appl. No. 11/334,876: Office Action dated May 2, 2008. |
| U.S. Appl. No. 11/334,876: Office Action dated Oct. 4, 2006. |
| U.S. Appl. No. 11/334,876: Office Action dated Aug. 25, 2009. |
| U.S. Appl. No. 11/334,876: Office Action dated Sep. 25, 2007. |
| U.S. Appl. No. 11/334,876: Office Action dated Aug. 26, 2008. |
| U.S. Appl. No. 11/360,252: Office Action dated Jul. 23, 2009. |
| U.S. Appl. No. 11/360,252: Office Action dated Jan. 29, 2009. |
| U.S. Appl. No. 11/360,252: Office Action dated Jun. 30, 2008. |
| U.S. Appl. No. 11/360,819: Office Action dated Aug. 11, 2008. |
| U.S. Appl. No. 11/360,819: Office Action dated Dec. 26, 2008. |
| U.S. Appl. No. 11/360,819: Office Action dated Oct. 29, 2009. |
| U.S. Appl. No. 12/113,508: Office Action dated Feb. 23, 2010. |
| U.S. Appl. No. 12/536,852: Partial Electronic File History, Office Actions dated Jun. 25, 2010, Oct. 18, 2010 and Feb. 25, 2011, and Applicant Responses filed Aug. 3, 2010, Dec. 8, 2010 and May 11, 2011. |
| American Diabetes Association, Diabetes Care 30(Supp. 1):S3 (Jan. 2007): Summary of Revisions for the 2007 Clinical Practice Recommendations. |
| American Diabetes Association, Diabetes Care 30(Supp. 1 ):S4 (Jan. 2007): Standards of Medical Care in Diabetes—2007. |
| American Diabetes Association, Diabetes Care 30(Suppl. 1):S42 (Jan. 2007): Diagnosis and Classification of Diabetes Mellitus. |
| Aussedat et al., Am. J. Physiol. Endocrinol, Metab. 278:E716-E728 (2000): Interstitial Glucose Concentration and Glycernia: Implications for Continuous Subcutaneous Glucose M. |
| Chase et al., Diabetes Technology & Therapeutics 7:274 (Nov. 2, 2005): Targeted Glycemic Reduction in Critical Care Using Closed-Loop Control. |
| El-Khatib et al., J. Diabetes Sci. & Technology 1(2):181 (Mar. 2007): Adaptive Closed-Loop Control Provides Blood-Glucose Regulation Using Dual Subcutaneous Insulin and Gluc. |
| Frohnauer et al., Diabetes Technology & Therapeutics 3(3):419 (2001): Graphical Human Insulin Time-Activity Profiles Using Standardized Definitions. |
| Garg et al., Diabetes Care 27(3):734 (Mar. 2004): Improved Glucose Excursions Using an Implantable Real-Time Continuous Glucose Sensor in Adults with Type 1 Diabetes. |
| Garg, Satish K., Diabetes Technology & Therapeutics 7(5):813 (2005): New Insulin Analogues. |
| Hagvik, Joakim, J. Diabetes Sci. & Technology 1(2):169 (Mar. 2007): Glucose Measurement: Time for a Gold Standard. |
| Heinemann et al., Diabetes Technology & Therapeutics 6(5):698 (2004) (Review) Measurement of Insulin Absorption and Insulin Action. |
| Heinemann, Lutz, Diabetes Technology & Therapeutics 4(5):(2002): (Review) Variability of Insulin Absorption and Insulin Action. |
| Heinemann, Lutz, J. Diabetes Sci. & Technology 1(2):178 (Mar. 2007): Measurement Quality of Blood Glucose Meters: Is There a Need for an Institution with an Unbiased View? |
| Hovorka et al., Diabetes Technology & Therapeutics 6(3):307 (2004): Closing the Loop: The Adicol Experience. |
| Hunsley et al., J. Diabetes Sci. & Technology 1(2):173 (Mar. 2007): Whole Blood Glucose Standard is Key to Accurate Insulin Dosages. |
| Jones et al., Diabetes Technology & Therapeutics 7(2):233 (2005): Optimal Insulin Pump Dosing and Postprandial Glycemia Following a Pizza Meal Using the Continuous Glucose Mo. |
| Kizilel et al., Diabetes Technology & Therapeutics 7(6):968 (2005): (Review) The Bioartificial Pancrease: Progress and Challenges. |
| Klonoff, David C., Diabetes Technology & Therpeutics 4(5):582 (2002): (Editorial) Current, Emerging, and Future Trends in Metabolic Monitoring. |
| Koschinsky et al., Diabetes Technology & Therapeutics 5(5):829 (2003): (Review) Glucose Sensors and the Alternate Site Testing-Like Phenomenon: Relationship Between Rapid BI. |
| Lee et al., J. Diabetes Sci. & Technology 1(3):400 (May 2007): Combined Insulin Pump Therapy with Real-Time Continuous Glucose Monitoring Significantly Improves Glycemic Cont. |
| Ristic et al., Diabetes Technology & Therapeutics 5(1):57 (2003): (Review) Effects of Rapid-Acting Insulin Analogs on Overall Glycemic Control in Type 1 and Type 2 Diabetes M. |
| Thennadil et al., Diabetes Technology & Therapeutics 3(3):357 (2001): Comparison fo Glucose Concentration in Interstitial Fluid, and Capillary and Venous Blood During Rapid C. |
| Vesper et al., Diabetes Technology & Therapeutics 8(1):76 (2006): Assessment of Trueness of a Glucose Monitor Using Interstitial Fluid and Whole Blood as Specimen Matrix. |
| Wentholt et al., Diabetes Technology & Therapeutics 9(2):169 (2007): Relationship Between Interstitial and Blood Glucose in Type 1 Diabetes Patients: Delay and the Push-Pull. |
| Wolpert, Howard A., Diabetes Technology & Therapeutics 5(5):843 (2003): (Commentary) A Clinician's Perspective on Some of the Challenges in “Closed Loop”. |
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