Integrated delivery device for continuous glucose sensor

Abstract
Systems and methods for integrating a continuous glucose sensor, including a receiver, a medicament delivery device, and optionally a single point glucose monitor are provided. Manual integrations provide for a physical association between the devices wherein a user (for example, patient or doctor) manually selects the amount, type, and/or time of delivery. Semi-automated integration of the devices includes integrations wherein an operable connection between the integrated components aids the user (for example, patient or doctor) in selecting, inputting, calculating, or validating 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. Automated integration between the devices includes integrations wherein an operable connection between the integrated components provides for full control of the system without required user interaction.
Description
FIELD OF THE INVENTION

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.


BACKGROUND OF THE INVENTION

Diabetes mellitus is a disorder in which the pancreas cannot create sufficient insulin (Type I or insulin dependent) and/or in which insulin is not effective (Type 2 or non-insulin dependent). In the diabetic state, the victim suffers from high blood sugar, which 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.


SUMMARY OF THE INVENTION

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 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 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 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 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.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a block diagram of an integrated system of the preferred embodiments, including a continuous glucose sensor, a receiver for processing and displaying sensor data, a medicament delivery device, and an optional single point glucose-monitoring device.



FIG. 2 is a perspective view of a continuous glucose sensor in one embodiment.



FIG. 3 is a block diagram of the electronics associated with a continuous glucose sensor in one embodiment.



FIGS. 4A and 4B are perspective views of an integrated system 10 in one embodiment, wherein a receiver is integrated with a medicament delivery device in the form of a manual syringe, and optionally includes a single point glucose monitor.



FIGS. 5A to 5C are perspective views of an integrated system in one embodiment, wherein a receiver is integrated with a medicament delivery device in the form of one or more transdermal patches housed within a holder, and optionally includes a single point glucose monitor.



FIGS. 6A and 6B are perspective views of an integrated system in one embodiment, wherein a receiver is integrated with a medicament delivery device in the form of a pen or jet-type injector, and optionally includes a single point glucose monitor.



FIGS. 7A to 7C are perspective views of an integrated system in one embodiment, wherein a sensor and delivery pump, which are implanted or transdermally inserted into the patient, are operably connected to an integrated receiver, and optionally include a single point glucose monitor.



FIG. 8 is a block diagram that illustrates integrated system electronics in one embodiment.



FIG. 9 is a flow chart that illustrates the process of validating therapy instructions prior to medicament delivery in one embodiment.



FIG. 10 is a flow chart that illustrates the process of providing adaptive metabolic control using an integrated sensor and medicament delivery device in one embodiment.



FIG. 11 is a flow chart that illustrates the process of glucose signal estimation using the integrated sensor and medicament delivery device in one embodiment.





DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

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.


Definitions


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



FIG. 1 is a block diagram of an integrated system 10 of the preferred embodiments, including a continuous glucose sensor 12, a receiver 14 for processing and displaying sensor data, a medicament delivery device 16, and optionally a single point glucose-monitoring device 18. The integrated diabetes management system 10 of the preferred embodiments provides improved convenience and accuracy thus affording a diabetic patient 8 with improved convenience, functionality, and safety in the care of their disease.



FIG. 1 shows a continuous glucose sensor 12 that measures a concentration of glucose or a substance indicative of the concentration or presence of the glucose. In some embodiments, the glucose sensor 12 is an invasive, minimally invasive, or non-invasive device, for example a subcutaneous, transdermal, or intravascular device. In some embodiments, the sensor 12 may analyze a plurality of intermittent biological samples. The glucose sensor may use any method of glucose-measurement, including enzymatic, chemical, physical, electrochemical, spectrophotometric, polarimetric, calorimetric, radiometric, or the like. In alternative embodiments, the sensor 12 may be any sensor capable of determining the level of an analyte in the body, for example oxygen, lactase, insulin, hormones, cholesterol, medicaments, viruses, or the like. The glucose sensor 12 uses any known method to provide an output signal indicative of the concentration of the glucose. The output signal is typically a raw data stream that is used to provide a useful value of the measured glucose concentration to a patient or doctor, for example.


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



FIG. 2 is a perspective view of one embodiment of a continuous glucose sensor 12. In this embodiment, a body 20 and a sensing region 22 house the electrodes and sensor electronics (FIG. 3). The three electrodes within the sensing region are operably connected to the sensor electronics (FIG. 3) and are covered by a sensing membrane and a biointerface membrane (not shown), which are described in more detail below.


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 (FIG. 3) is employed to monitor the electrochemical reaction at the electroactive surface(s). The potentiostat applies a constant potential to the working and reference electrodes to determine a current value. The current that is produced at the working electrode (and flows through the circuitry to the counter electrode) is substantially proportional to the amount of H2O2 that diffuses to the working electrode. Accordingly, a raw signal can be produced that is representative of the concentration of glucose in the user's body, and therefore can be utilized to estimate a meaningful glucose value.


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 READ 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.



FIG. 3 is a block diagram that illustrates the electronics associated with a continuous glucose sensor 12 in one embodiment. In this embodiment, a potentiostat 24 is shown, which is operably connected to electrodes (FIG. 2) to obtain a current value, and includes a resistor (not shown) that translates the current into voltage. An A/D converter 26 digitizes the analog signal into “counts” for processing. Accordingly, the resulting raw data stream in counts is directly related to the current measured by the potentiostat 24.


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. FIGS. 9 to 11 describe some processes that may be programmed into the receiver. Additionally, the receiver 14 of the preferred embodiments works together with the other components of the system (for example, the medicament delivery device 16 and the single point glucose monitor 18) to provide enhanced functionality, convenience, and safety, such as described in more detail herein. FIGS. 4 to 7 are illustrates of a few exemplary integrated systems of the preferred embodiments, each of which include the receiver, such as described in more detail herein.


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 FIG. 8. The receiver 46 comprises systems (for example, electronics) necessary to receive, process, and display sensor data from the glucose sensor 12, such as described in more detail with reference to FIG. 8. The receiver 14 processes data from the continuous glucose sensor 12 and additionally processes data associated with at least one of the medicament delivery device 16, single point glucose meter 16, and user 8.


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 FIGS. 4 to 7, however suffice it to say that each of the components of the integrated system may be manually, semi-automatically, or automatically integrated with each other, and each component may be in physical and/or data communication with another component, which may include wireless connection, wired connection (for example, via cables or electrical contacts), or the like.


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. Nos. 5,234,906, 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.



FIGS. 4A and 4B are perspective views of a integrated system 10 in one embodiment, wherein a receiver 14 is integrated with a medicament delivery device 16 in the form of a manual syringe 54, and optionally includes a single point glucose monitor 18, which will be described in more detail elsewhere herein. The receiver 14 receives, processes, and displays data from the continuous glucose monitor 12, such as described in more detail above, and may also receive, process, and display data manually entered by the user. 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. The medicament delivery device 16 is in the form of a syringe 54, which may comprise any known syringe configuration, such as described in more detail above. In some embodiments, the syringe 54 includes a housing, which is designed to hold a syringe as well as a plurality of types and amounts of medicament, for example fast-acting insulin, slow-acting insulin, and glucagon. In some embodiments, the syringe is detachably connectable to the receiver 14, and the receiver 14 provides and receives information to and from the patient associated with the time, type, and amount of medicament administered. In some embodiments, the syringe is stored in a holder that is integral with or detachably connected to the receiver 14. In some embodiments, the syringe 54 may be detachable connected directly to the receiver, provided in a kit with the receiver, or other configuration, which provides easy association between the syringe and the receiver.


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 FIGS. 5A to 5C describe a medicament (for example, glucagon) useful for treating hypoglycemia, it is understood that transdermal patches that release a medicament (for example, insulin) useful for treating hyperglycemia are also contemplated within the scope of the preferred embodiments.



FIGS. 5A to 5C are perspective views of an integrated system 10 in one embodiment, wherein a receiver 14 is integrated with a medicament delivery device 16 in the form of one or more transdermal patches 58 housed within a holder 56, and optionally includes a single point glucose monitor 18, which will be described in more detail elsewhere herein. The receiver 14 receives, processes, and displays data from the continuous glucose monitor 12, such as described in more detail above. The medicament delivery device 16 is in the form of one or more transdermal patches 58 held in a holder 56, which may comprise any known patch configuration.


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 FIGS. 5A to 5C, other medicaments (for example, insulin pen, insulin pump, such as described with reference to FIGS. 6 and 7) may be integrated into the system in combination with the medicament patch illustrated herein. While not wishing to be bound by theory, it is believed that by combining medicaments that aid the diabetic patient in different ways (for example, medicaments for treating hyper- and hypo-glycemic events, or, fast-acting and slow-acting medicaments), a simplified comprehensive solution for treating diabetes may be provided.


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 FIGS. 4 and 5, wherein the inhaler or spray is manually administered by a patient, and wherein the patient manually enters data into the continuous receiver about the time, amount, and types of therapy. However, it is also possible that the inhaler or spray device used for administering the medicament may also comprise a microprocessor and operable connection to the receiver (for example, RF), such that data is sent and received between the receiver and inhaler or spray device, making it a semi-automated integration, which is described in more detail with reference to the integrated insulin pen below, for example.


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.



FIGS. 6A and 6B are perspective views of an integrated system 10 in one embodiment, wherein a receiver 14 is integrated with a medicament delivery device 16 in the form of a pen or jet-type injector, hereinafter referred to as a pen 60, and optionally includes a single point glucose monitor 18, which will be described in more detail elsewhere herein. The receiver 14 receives, processes, and displays data from the continuous glucose monitor 12, such as described in more detail above. The medicament delivery pen 60 of the preferred embodiments, includes any pen-type injector, such as is appreciated by one skilled in the art. A few examples of medicament pens that may be used with the preferred embodiments, include U.S. Pat. Nos. 5,226,895, 4,865,591, 6,192,891, and 5,536,249, all of which are incorporated herein by reference in their entirety.



FIG. 6A is a perspective view of an integrated system 10 in embodiment. The integrated system 10 is shown in an attached state, wherein the various elements are held by a mechanical means, as is appreciated by one skilled in the art. The components 14, 16, and 18(optional) are also in operable connection with each other, which may include a wired or wireless connection. In some embodiments, the components include electrical contacts that operably connect the components together when in the attached state. In some embodiments, the components are operably connected via wireless connection (for example, RF), and wherein the components may or may not be detachably connectable to each other. FIG. 6B show the components in an unattached state, which may be useful when the patient would like to carry minimal components and/or when the components are integrated via a wireless connection, for example.


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 FIG. 8. In some embodiments, the pen 60 includes programming that receives instructions sent from the receiver 14 regarding type and amount of medicament to administer. In some embodiments, wherein the pen includes more than one type of medicament, the receiver provides the necessary instructions to determine which type or types of medicament to administer, and may provide instructions necessary for mixing the one or more medicaments. In some embodiments, the receiver provides the glucose trend information (for example, concentration, rate-of-change, acceleration, or other user input information) and pen 60 includes programming necessary to determine appropriate medicament delivery.


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 FIGS. 9 to 11 for processes that may be implemented herein.


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.



FIGS. 7A to 7C are perspective views of an integrated system in one embodiment, wherein a sensor and delivery pump, which are implanted or transdermally inserted into the patient, are operably connected to an integrated receiver, and optionally include a single point glucose monitor. FIG. 7A is a perspective view of a patient 8, in which is implanted or transdermally inserted a sensor 12 and a pump 70. FIGS. 7B and 7C are perspective views of the integrated receiver and optional single point glucose monitor in attached and unattached states. The pump 70 may be of any configuration known in the art, for example, such as cited above.


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 FIGS. 7A to 7C. However, the fully automated sensing and delivery system can run with or without user interaction. Published Patent Application US 2003/0028089 provides some systems and methods for providing control of insulin, which may be used with the preferred embodiments, and is incorporated herein by reference in its entirety.


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 (FIGS. 4 to 7), the single point glucose monitor includes a meter for measuring glucose within a biological sample including a sensing region that has a sensing membrane impregnated with an enzyme, similar to the sensing membrane described with reference to U.S. Pat. Nos. 4,994,167 and 4,757,022, which are incorporated herein in their entirety by reference. However, in alternative embodiments, the single point glucose monitor can use other measurement techniques such as optical, for example. It is noted that the meter is optional in that a separate meter can be used and the glucose data downloaded or input by a user into the receiver. However the illustrated embodiments show an integrated system that exploits the advantages associated with integration of the single point glucose monitor with the receiver 14 and delivery device 16.



FIGS. 4 to 7 are perspective views of integrated receivers including a single point glucose monitor. It is noted that the integrated single point glucose monitor may be integral with, detachably connected to, and/or operably connected (wired or wireless) to the receiver 14 and medicament delivery device 16. The single point glucose monitor 18 integrates rapid and accurate measurement of the amount of glucose in a biological fluid and its associated processing with the calibration, validation, other processes associated with the continuous receiver 14, such as described in more detail with reference to U.S. provisional patent application, 60/523,840, entitled “INTEGRATED RECEIVER FOR CONTINUOUS ANALYTE SENSOR,” which is incorporated herein by reference in its entirety.


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



FIG. 8 is a block diagram that illustrates integrated system electronics in one embodiment. One embodiment is described wherein the microprocessor within the receiver performs much of the processing, however it is understood that all or some of the programming and processing described herein can be accomplished within continuous glucose sensor, receiver, single point glucose monitor, and/or delivery device, or any combination thereof. Similarly, displays, alarms, and other user interface functions may be incorporated into any of the individual components of the integrated delivery device.


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 FIG. 3). Once received, a microprocessor 82 processes the signals, such as described below.


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. FIGS. 9 and 10 describe more detail about programming that is preferably processed by the microprocessor 82. In some alternative embodiments, memory storage components comparable to ROM and RAM can be used instead of or in addition to the preferred hardware, such as SRAM, EEPROM, dynamic RAM, non-static RAM, rewritable ROMs, flash memory, or the like.


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 FIGS. 9 to 11.


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)



FIG. 9 is a flow chart that illustrates the process 130 of validating therapy instructions prior to medicament delivery in one embodiment. In some embodiments, the therapy recommendations include a suggestion on the user interface of time, amount, and type of medicament to delivery. In some embodiments, therapy instructions includes calculating a time, amount, and/or type of medicament delivery to administer, and optionally transmitting those instructions to the delivery device. In some embodiments, therapy instructions include that portion of a closed loop system wherein the determination and delivery of medicament is accomplished, as is appreciated by one skilled in the art.


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.



FIG. 10 is a flow chart 140 that illustrates the process of providing adaptive metabolic control using an integrated system in one embodiment. In this embodiment, the integrated system is programmed to learn the patterns of the individual's metabolisms, including metabolic response to medicament delivery.


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 FIG. 9 above. In some embodiments, the recommended therapy is manually, semi-automatically, or automatically delivered to the patient.


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.



FIG. 11 is a flow chart 152 that illustrates the process of glucose signal estimation using the integrated sensor and medicament delivery device in one embodiment. It is noted that glucose estimation and/or prediction are described in co-pending patent application Ser. No. 10/633,367 and provisional patent application 60/528,382, both of which have been incorporated herein by reference in their entirety. However, the preferred embodiments described herein, further incorporated additional data of medicament delivery in estimating or predicting glucose trends.


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.


EXAMPLES

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.

Claims
  • 1. A method of operating a medicament delivery device capable of administering a medicament to a patient, the method comprising: obtaining, by a receiver associated with the medicament delivery device, measured analyte values indicative of an analyte concentration of the patient provided by an analyte sensor;identifying, by the receiver, occurrence of a learned pattern of the patient based on the measured analyte values of the analyte concentration over time;providing, by the receiver, a user interface indicating the identified pattern; andin response to receiving a user validation that is required under conditions that are learned based on the identified pattern, adjusting, by the receiver, operation of the medicament delivery device to administer the medicament to the patient based on the identified pattern.
  • 2. The method of claim 1, further comprising: determining, by the receiver, a personalized therapy recommendation for a bolus injection, the personalized therapy recommendation determined based at least in part on a meal; andoperating, by the receiver, the medicament delivery device to administer the bolus injection of the medicament to the patient.
  • 3. The method of claim 1, wherein adjusting the operation of the medicament delivery device is based on a meal.
  • 4. The method of claim 1, wherein adjusting the operation of the medicament delivery device is based on exercise.
  • 5. The method of claim 1, wherein the occurrence of the learned pattern is identified based on historical measured analyte values having the learned pattern.
  • 6. The method of claim 1, wherein the operation of the medicament delivery device is carried out, at least in part, within a closed loop.
  • 7. The method of claim 1, wherein determination of the medicament administered is carried out within a closed loop.
  • 8. The method of claim 1, wherein administering the medicament by the medicament delivery device is carried out within a closed loop.
  • 9. The method of claim 1, wherein the receiver includes programming that learns patterns.
  • 10. The method of claim 1, wherein the learned pattern is learned using pattern recognition.
  • 11. A system comprising: a medicament delivery device to administer medicament to a patient;an analyte sensor to provide measurements of analyte values indicative of an analyte concentration of the patient;a data storage component to store measured analyte values indicative of the analyte concentration of the patient over time;a receiver operably connected to the medicament delivery device, the analyte sensor, and the data storage component to: identify, by the receiver, occurrence of a learned pattern of the patient based on the measured analyte values of the analyte concentration over time; andin response to receiving a user validation that is required under conditions that are learned based on the identified pattern, adjust operation of the medicament delivery device to administer the medicament to the patient based on the identified pattern.
  • 12. The system of claim 11, wherein the receiver is further configured to provide a user interface indicating the identified pattern.
  • 13. The system of claim 11, wherein the receiver is further configured to: determine a personalized therapy recommendation for a bolus injection, the personalized therapy recommendation determined based at least in part on a meal; andoperate the medicament delivery device to administer the bolus injection of the medicament to the patient.
  • 14. The system of claim 11, wherein the operation of the medicament delivery device is adjusted based on a meal.
  • 15. The system of claim 11, wherein the operation of the medicament delivery device is adjusted based on exercise.
  • 16. The system of claim 11, wherein the occurrence of the learned pattern is identified based on historical measured analyte values having the learned pattern.
  • 17. The system of claim 11, wherein the operation of the medicament delivery device is carried out, at least in part, within a closed loop of the system.
  • 18. The system of claim 11, wherein determination of the medicament administered is carried out within a closed loop of the system.
  • 19. One or more computer-readable storage media storing instructions that are executable by one or more processors to perform operations including: obtaining, by a receiver associated with a medicament delivery device, measured analyte values indicative of an analyte concentration of a patient provided by an analyte sensor;identifying, by the receiver, occurrence of a learned pattern of the patient based on the measured analyte values of the analyte concentration over time;providing, by the receiver, a user interface indicating the identified pattern; andin response to receiving a user validation that is required under conditions that are learned based on the identified pattern, adjusting, by the receiver, operation of the medicament delivery device to administer a medicament to the patient based on the identified pattern.
  • 20. The one or more computer-readable storage media of claim 19, wherein the operations further include: determining, by the receiver, a personalized therapy recommendation for a bolus injection, the personalized therapy recommendation determined based at least in part on a meal; andoperating, by the receiver, the medicament delivery device to administer the bolus injection of the medicament to the patient.
INCORPORATION BY REFERENCE TO RELATED APPLICATIONS

Any and all priority claims identified in the Application Data Sheet, or any correction thereto, are hereby incorporated by reference under 37 CFR 1.57. This application is a continuation of U.S. application Ser. No. 17/556,761, filed Dec. 20, 2021, which is a continuation of U.S. application Ser. No. 15/906,946, filed Feb. 27, 2018, which is a continuation of U.S. application Ser. No. 14/830,568, filed Aug. 19, 2015, now U.S. Pat. No. 9,937,293, which is a continuation of U.S. application Ser. No. 13/559,454 filed Jul. 26, 2012, now U.S. Pat. No. 9,155,843, 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.

US Referenced Citations (1469)
Number Name Date Kind
52641 Gates Feb 1866 A
62334 Holmes Feb 1867 A
65604 Reynolds Jun 1867 A
1954643 Neuhaus Apr 1934 A
2719797 Rosenblatt et al. Oct 1955 A
3210578 Sherer Oct 1965 A
3219533 Mullins Nov 1965 A
3381371 Russell May 1968 A
3506032 Eveleigh et al. Apr 1970 A
3556950 Dahms et al. Jan 1971 A
3610226 Albisser Oct 1971 A
3775182 Patton et al. Nov 1973 A
3780727 King Dec 1973 A
3826244 Salcman et al. Jul 1974 A
3837339 Aisenberg et al. Sep 1974 A
3838682 Clark et al. Oct 1974 A
3874850 Sorensen et al. Apr 1975 A
3898984 Mandel et al. Aug 1975 A
3910256 Clark et al. Oct 1975 A
3929971 Roy Dec 1975 A
3933593 Sternberg Jan 1976 A
3943918 Lewis Mar 1976 A
3957613 Macur May 1976 A
3964974 Banauch et al. Jun 1976 A
3979274 Newman Sep 1976 A
4008717 Kowarski Feb 1977 A
4016866 Lawton Apr 1977 A
4024312 Korpman May 1977 A
4040908 Clark, Jr. Aug 1977 A
4052754 Homsy Oct 1977 A
4055175 Clemens et al. Oct 1977 A
4073713 Newman Feb 1978 A
4076656 White et al. Feb 1978 A
4109505 Clark et al. Aug 1978 A
4119406 Clemens Oct 1978 A
4136250 Mueller et al. Jan 1979 A
4151845 Clemens May 1979 A
4172770 Semersky et al. Oct 1979 A
4176659 Rolfe Dec 1979 A
4197840 Beck et al. Apr 1980 A
4197852 Schindler et al. Apr 1980 A
4206755 Klein Jun 1980 A
4215703 Willson Aug 1980 A
4240438 Updike et al. Dec 1980 A
4240889 Yoda et al. Dec 1980 A
4245634 Albisser et al. Jan 1981 A
4253469 Aslan Mar 1981 A
4255500 Hooke Mar 1981 A
4259540 Sabia Mar 1981 A
4265249 Schindler et al. May 1981 A
4319578 Enger Mar 1982 A
4327725 Cortese et al. May 1982 A
4366040 Marsoner et al. Dec 1982 A
4369785 Rehkopf et al. Jan 1983 A
4374013 Enfors Feb 1983 A
4388166 Suzuki et al. Jun 1983 A
4403984 Ash et al. Sep 1983 A
4415666 D'Orazio et al. Nov 1983 A
4431004 Bessman et al. Feb 1984 A
4432366 Margules Feb 1984 A
4436094 Cerami Mar 1984 A
4442841 Uehara et al. Apr 1984 A
4454295 Wittmann et al. Jun 1984 A
4457339 Juan et al. Jul 1984 A
4477314 Richter et al. Oct 1984 A
4478222 Koning et al. Oct 1984 A
4486290 Cahalan et al. Dec 1984 A
4492575 Mabille Jan 1985 A
4494950 Fischell Jan 1985 A
4506680 Stokes Mar 1985 A
4519973 Cahalan et al. May 1985 A
RE31916 Oswin et al. Jun 1985 E
4526569 Bernardi Jul 1985 A
4534825 Koning et al. Aug 1985 A
4535786 Kater Aug 1985 A
4538616 Rogoff Sep 1985 A
4545382 Higgins et al. Oct 1985 A
4554927 Fussell Nov 1985 A
4565665 Fogt Jan 1986 A
4565666 Cahalan et al. Jan 1986 A
4568444 Nakamura et al. Feb 1986 A
4571292 Liu et al. Feb 1986 A
4573968 Parker Mar 1986 A
4577642 Stokes Mar 1986 A
4583976 Ferguson Apr 1986 A
4592824 Smith et al. Jun 1986 A
4600495 Fogt Jul 1986 A
4614514 Carr et al. Sep 1986 A
4619793 Lee Oct 1986 A
4625730 Fountain et al. Dec 1986 A
4626104 Pointon et al. Dec 1986 A
4632968 Yokota et al. Dec 1986 A
RE32361 Duggan Feb 1987 E
4655880 Liu Apr 1987 A
4663824 Kenmochi May 1987 A
4671288 Gough Jun 1987 A
4672970 Uchida et al. Jun 1987 A
4680268 Clark, Jr. Jul 1987 A
4685463 Williams Aug 1987 A
4685903 Cable et al. Aug 1987 A
4694861 Goodale et al. Sep 1987 A
4702732 Powers et al. Oct 1987 A
4703756 Gough et al. Nov 1987 A
4705503 Dorman et al. Nov 1987 A
4711245 Higgins et al. Dec 1987 A
4711251 Stokes Dec 1987 A
4721677 Clark, Jr. Jan 1988 A
4726381 Jones Feb 1988 A
4731726 Allen, III Mar 1988 A
4736748 Nakamura et al. Apr 1988 A
4747822 Peabody May 1988 A
4750496 Reinhart et al. Jun 1988 A
4753652 Langer et al. Jun 1988 A
4755168 Romanelli et al. Jul 1988 A
4757022 Shults et al. Jul 1988 A
4759828 Young et al. Jul 1988 A
4763648 Wyatt Aug 1988 A
4763658 Jones Aug 1988 A
4777953 Ash et al. Oct 1988 A
4781798 Gough Nov 1988 A
4784157 Halls et al. Nov 1988 A
4786394 Enzer et al. Nov 1988 A
4787398 Garcia et al. Nov 1988 A
4789467 Lindsay et al. Dec 1988 A
4791932 Margules Dec 1988 A
4803243 Fujimoto et al. Feb 1989 A
4805624 Yao et al. Feb 1989 A
4805625 Wyler Feb 1989 A
4807632 Liess et al. Feb 1989 A
4808089 Buchholtz et al. Feb 1989 A
4808292 Kessler et al. Feb 1989 A
4809704 Sogawa et al. Mar 1989 A
4810243 Howson Mar 1989 A
4810470 Burkhardt et al. Mar 1989 A
4815471 Stobie Mar 1989 A
4820281 Lawler, Jr. Apr 1989 A
4822336 DiTraglia Apr 1989 A
4823808 Clegg et al. Apr 1989 A
4828544 Lane et al. May 1989 A
4830013 Maxwell May 1989 A
4831070 McInally et al. May 1989 A
4832005 Takamiya et al. May 1989 A
4832034 Pizziconi et al. May 1989 A
4834101 Collison et al. May 1989 A
4838281 Rogers et al. Jun 1989 A
4841974 Gumbrecht et al. Jun 1989 A
4849458 Reed et al. Jul 1989 A
4852573 Kennedy Aug 1989 A
4854322 Ash et al. Aug 1989 A
4858615 Meinema Aug 1989 A
4867741 Portnoy Sep 1989 A
4871440 Nagata et al. Oct 1989 A
4874363 Abell Oct 1989 A
4883057 Broderick Nov 1989 A
4883467 Franetzki et al. Nov 1989 A
4889528 Nadai et al. Dec 1989 A
4889744 Quaid Dec 1989 A
4890620 Gough Jan 1990 A
4890621 Hakky Jan 1990 A
4900305 Smith et al. Feb 1990 A
4902294 Gosserez Feb 1990 A
4907857 Giuliani et al. Mar 1990 A
4908208 Lee et al. Mar 1990 A
4909786 Gijselhart et al. Mar 1990 A
4919114 Miyazaki Apr 1990 A
4919141 Zier et al. Apr 1990 A
4919649 Timothy et al. Apr 1990 A
4921477 Davis May 1990 A
4921480 Sealfon May 1990 A
4925444 Orkin et al. May 1990 A
4927407 Dorman May 1990 A
4927516 Yamaguchi et al. May 1990 A
4928694 Maxwell May 1990 A
4934369 Maxwell Jun 1990 A
4934375 Cole et al. Jun 1990 A
4944299 Silvian Jul 1990 A
4946439 Eggers Aug 1990 A
4950246 Muller Aug 1990 A
4951657 Pfister et al. Aug 1990 A
4951669 Maxwell et al. Aug 1990 A
4953552 DeMarzo Sep 1990 A
4957483 Gonser et al. Sep 1990 A
4963595 Ward et al. Oct 1990 A
4966579 Polaschegg Oct 1990 A
4967940 Blette et al. Nov 1990 A
4970145 Bennetto et al. Nov 1990 A
4973320 Brenner et al. Nov 1990 A
4974592 Branco Dec 1990 A
4974929 Curry Dec 1990 A
4975636 Desautels Dec 1990 A
4976687 Martin Dec 1990 A
4979509 Hakky Dec 1990 A
4984929 Rock et al. Jan 1991 A
4986671 Sun et al. Jan 1991 A
4988341 Columbus et al. Jan 1991 A
4989607 Keusch et al. Feb 1991 A
4992794 Brouwers Feb 1991 A
4994026 Fecondini Feb 1991 A
4994167 Shults et al. Feb 1991 A
4997627 Bergkuist et al. Mar 1991 A
5002055 Merki et al. Mar 1991 A
5002572 Picha Mar 1991 A
5006050 Cooke et al. Apr 1991 A
5006111 Inokuchi et al. Apr 1991 A
5007929 Quaid Apr 1991 A
5009251 Pike et al. Apr 1991 A
5019974 Beckers May 1991 A
5026348 Venegas Jun 1991 A
5030199 Barwick et al. Jul 1991 A
5030333 Clark, Jr. Jul 1991 A
5034112 Murase et al. Jul 1991 A
5035711 Aoki et al. Jul 1991 A
5041092 Barwick Aug 1991 A
5045057 Van Driessche et al. Sep 1991 A
5046496 Betts et al. Sep 1991 A
5048525 Maxwell Sep 1991 A
5050612 Matsumura Sep 1991 A
5055171 Peck Oct 1991 A
5055198 Shettigar Oct 1991 A
5059654 Hou et al. Oct 1991 A
5067491 Taylor, II et al. Nov 1991 A
5068536 Rosenthal Nov 1991 A
5070169 Robertson et al. Dec 1991 A
5077476 Rosenthal Dec 1991 A
5088981 Howson et al. Feb 1992 A
5089421 Dieffenbach Feb 1992 A
5096669 Lauks et al. Mar 1992 A
5097834 Skrabal Mar 1992 A
5098377 Borsanyi et al. Mar 1992 A
5101814 Palti Apr 1992 A
5108819 Heller et al. Apr 1992 A
5109850 Blanco et al. May 1992 A
5112301 Fenton, Jr. et al. May 1992 A
5116313 McGregor May 1992 A
5127405 Alcala et al. Jul 1992 A
5137028 Nishimura Aug 1992 A
5140985 Schroeder et al. Aug 1992 A
5145565 Kater et al. Sep 1992 A
5152746 Atkinson et al. Oct 1992 A
5153827 Coutre Oct 1992 A
5160418 Mullen Nov 1992 A
5161532 Joseph Nov 1992 A
5165406 Wong Nov 1992 A
5165407 Wilson et al. Nov 1992 A
5174291 Schoonen et al. Dec 1992 A
5176632 Bernardi Jan 1993 A
5176658 Ranford Jan 1993 A
5178142 Harjunmaa et al. Jan 1993 A
5182004 Kohno Jan 1993 A
5188591 Dorsey, III Feb 1993 A
5190041 Palti Mar 1993 A
5195963 Yafuso et al. Mar 1993 A
5198771 Fidler et al. Mar 1993 A
5208147 Kagenow et al. May 1993 A
5208313 Krishnan May 1993 A
5220917 Cammilli et al. Jun 1993 A
5220920 Gharib Jun 1993 A
5224929 Remiszewski Jul 1993 A
5225063 Gumbrecht et al. Jul 1993 A
5232434 Inagaki et al. Aug 1993 A
5235003 Ward et al. Aug 1993 A
5243982 Mostl et al. Sep 1993 A
5243983 Tarr et al. Sep 1993 A
5249576 Goldberger et al. Oct 1993 A
5251126 Kahn et al. Oct 1993 A
5254102 Ogawa Oct 1993 A
5262305 Heller et al. Nov 1993 A
5265594 Olsson et al. Nov 1993 A
5266179 Nankai et al. Nov 1993 A
5269891 Colin Dec 1993 A
5271736 Picha Dec 1993 A
5271815 Wong Dec 1993 A
5279294 Anderson et al. Jan 1994 A
5281319 Kaneko et al. Jan 1994 A
5282848 Schmitt Feb 1994 A
5284140 Allen et al. Feb 1994 A
5284570 Savage et al. Feb 1994 A
5285513 Kaufman et al. Feb 1994 A
5287753 Routh et al. Feb 1994 A
5298022 Bernardi Mar 1994 A
5299571 Mastrototaro Apr 1994 A
5302093 Owens et al. Apr 1994 A
5304468 Phillips et al. Apr 1994 A
5307263 Brown Apr 1994 A
5310469 Cunningham et al. May 1994 A
5311908 Barone et al. May 1994 A
5312361 Zadini et al. May 1994 A
5314471 Brauker et al. May 1994 A
5316008 Suga et al. May 1994 A
5316452 Bogen et al. May 1994 A
5318511 Riquier et al. Jun 1994 A
5322063 Allen et al. Jun 1994 A
5324322 Grill, Jr. et al. Jun 1994 A
5326356 Della Valle et al. Jul 1994 A
5326449 Cunningham Jul 1994 A
5330521 Cohen Jul 1994 A
5330634 Wong et al. Jul 1994 A
5331555 Hashimoto et al. Jul 1994 A
5335658 Bedingham Aug 1994 A
5337747 Neftel Aug 1994 A
5342409 Mullett Aug 1994 A
5342789 Chick et al. Aug 1994 A
5343869 Pross et al. Sep 1994 A
5344454 Clarke et al. Sep 1994 A
5345932 Yafuso et al. Sep 1994 A
5348788 White Sep 1994 A
5352348 Young et al. Oct 1994 A
5352351 White et al. Oct 1994 A
5354272 Swendson et al. Oct 1994 A
5354449 Band et al. Oct 1994 A
5356375 Higley Oct 1994 A
5356378 Doan Oct 1994 A
5356786 Heller et al. Oct 1994 A
5368028 Palti Nov 1994 A
5368224 Richardson et al. Nov 1994 A
5368562 Blomquist et al. Nov 1994 A
5372133 Hogen Esch Dec 1994 A
5372135 Mendelson et al. Dec 1994 A
5372709 Hood Dec 1994 A
5376070 Purvis et al. Dec 1994 A
5378229 Layer et al. Jan 1995 A
5380268 Wheeler Jan 1995 A
5380491 Carver, Jr. et al. Jan 1995 A
5380536 Hubbell et al. Jan 1995 A
5380665 Cusack et al. Jan 1995 A
5384028 Ito Jan 1995 A
5390671 Lord et al. Feb 1995 A
5391250 Cheney, II et al. Feb 1995 A
5397848 Yang et al. Mar 1995 A
5405510 Betts et al. Apr 1995 A
5411052 Murray May 1995 A
5411647 Johnson et al. May 1995 A
5411866 Luong et al. May 1995 A
5417206 Kaneyoshi May 1995 A
5421328 Bedingham Jun 1995 A
5421923 Clarke et al. Jun 1995 A
5423738 Robinson et al. Jun 1995 A
5423749 Merte et al. Jun 1995 A
5428123 Ward et al. Jun 1995 A
5429485 Dodge Jul 1995 A
5429602 Hauser Jul 1995 A
5429735 Johnson et al. Jul 1995 A
5431160 Wilkins Jul 1995 A
5431174 Knute Jul 1995 A
5431921 Thombre Jul 1995 A
5434412 Sodickson et al. Jul 1995 A
5437635 Fields et al. Aug 1995 A
5438984 Schoendorfer Aug 1995 A
5443508 Giampapa Aug 1995 A
5445610 Evert Aug 1995 A
5448992 Kupershmidt Sep 1995 A
5451260 Versteeg et al. Sep 1995 A
5453278 Chan et al. Sep 1995 A
5458631 Xavier Oct 1995 A
5462051 Oka et al. Oct 1995 A
5462064 D'Angelo et al. Oct 1995 A
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
5482446 Williamson et al. Jan 1996 A
5482473 Lord et al. Jan 1996 A
5484404 Schulman et al. Jan 1996 A
5491474 Suni et al. Feb 1996 A
5494562 Maley et al. Feb 1996 A
5496453 Uenoyama et al. Mar 1996 A
5497772 Schulman et al. Mar 1996 A
5502396 Desarzens et al. Mar 1996 A
5505828 Wong et al. Apr 1996 A
5507288 Bocker Apr 1996 A
5508203 Fuller et al. Apr 1996 A
5509888 Miller Apr 1996 A
5512046 Pusinelli et al. Apr 1996 A
5512055 Domb et al. Apr 1996 A
5512248 Van Apr 1996 A
5513636 Palti May 1996 A
5514253 Davis et al. May 1996 A
5515851 Goldstein May 1996 A
5518601 Foos et al. May 1996 A
5527288 Gross et al. Jun 1996 A
5531679 Schulman et al. Jul 1996 A
5531878 Vadgama et al. Jul 1996 A
5536249 Castellano et al. Jul 1996 A
5538511 Van Antwerp Jul 1996 A
5540828 Yacynych Jul 1996 A
5545220 Andrews et al. Aug 1996 A
5545223 Neuenfeldt et al. Aug 1996 A
5549547 Cohen et al. Aug 1996 A
5549548 Larsson Aug 1996 A
5549569 Lynn et al. Aug 1996 A
5549651 Lynn Aug 1996 A
5551850 Williamson et al. Sep 1996 A
5553616 Ham et al. Sep 1996 A
5554339 Cozzette et al. Sep 1996 A
5561615 Kuo et al. Oct 1996 A
5562614 O'Donnell Oct 1996 A
5562615 Nassif Oct 1996 A
5564439 Picha Oct 1996 A
5568806 Cheney, II et al. Oct 1996 A
5569186 Lord et al. Oct 1996 A
5569188 MacKool Oct 1996 A
5569219 Hakki et al. Oct 1996 A
5569462 Martinson et al. Oct 1996 A
5575293 Miller et al. Nov 1996 A
5575930 Tietje-Girault et al. Nov 1996 A
5577499 Teves Nov 1996 A
5582184 Erickson et al. Dec 1996 A
5582593 Hultman Dec 1996 A
5584813 Livingston et al. Dec 1996 A
5584876 Bruchman et al. Dec 1996 A
5586553 Halili et al. Dec 1996 A
5589133 Suzuki Dec 1996 A
5590651 Shaffer et al. Jan 1997 A
5593440 Brauker et al. Jan 1997 A
5609572 Lang Mar 1997 A
5611900 Worden et al. Mar 1997 A
5624409 Seale Apr 1997 A
5624537 Turner et al. Apr 1997 A
5626563 Dodge et al. May 1997 A
5628619 Wilson May 1997 A
5628890 Carter et al. May 1997 A
5637083 Bertrand et al. Jun 1997 A
5640470 Iyer et al. Jun 1997 A
5643195 Drevet et al. Jul 1997 A
5651767 Schulman et al. Jul 1997 A
5653756 Clarke et al. Aug 1997 A
5653863 Genshaw et al. Aug 1997 A
5658250 Blomquist et al. Aug 1997 A
5660163 Schulman et al. Aug 1997 A
5660565 Williams Aug 1997 A
5665061 Antwiler Sep 1997 A
5665065 Colman et al. Sep 1997 A
5667504 Baumann et al. Sep 1997 A
5673694 Rivers Oct 1997 A
5674289 Fournier et al. Oct 1997 A
5676651 Larson, Jr. et al. Oct 1997 A
5676820 Wang et al. Oct 1997 A
5681572 Seare, Jr. Oct 1997 A
5682884 Hill et al. Nov 1997 A
5683562 Schaffar et al. Nov 1997 A
5686829 Girault Nov 1997 A
5688239 Walker Nov 1997 A
5688244 Lang Nov 1997 A
5695623 Michel et al. Dec 1997 A
5696314 McCaffrey et al. Dec 1997 A
5697366 Kimball et al. Dec 1997 A
5697899 Hillman et al. Dec 1997 A
5704354 Preidel et al. Jan 1998 A
5706807 Picha Jan 1998 A
5711861 Ward et al. Jan 1998 A
5713888 Neuenfeldt et al. Feb 1998 A
5730654 Brown Mar 1998 A
5733259 Valcke et al. Mar 1998 A
5733336 Neuenfeldt et al. Mar 1998 A
5743262 Lepper, Jr. et al. Apr 1998 A
5749832 Vadgama et al. May 1998 A
5749907 Mann May 1998 A
5755692 Manicom May 1998 A
5756632 Ward et al. May 1998 A
5758643 Wong et al. Jun 1998 A
5763760 Gumbrecht et al. Jun 1998 A
5771890 Tamada Jun 1998 A
5773286 Dionne et al. Jun 1998 A
5776324 Usala Jul 1998 A
5779665 Mastrototaro et al. Jul 1998 A
5781455 Hyodo Jul 1998 A
5782880 Lahtinen et al. Jul 1998 A
5782912 Brauker et al. Jul 1998 A
5787900 Butler et al. Aug 1998 A
5791344 Schulman et al. Aug 1998 A
5791880 Wilson Aug 1998 A
5795453 Gilmartin Aug 1998 A
5795774 Matsumoto et al. Aug 1998 A
5798065 Picha Aug 1998 A
5800383 Chandler et al. Sep 1998 A
5800420 Gross et al. Sep 1998 A
5800529 Brauker et al. Sep 1998 A
5806517 Gerhardt et al. Sep 1998 A
5807274 Henning et al. Sep 1998 A
5807312 Dzwonkiewicz Sep 1998 A
5807375 Gross et al. Sep 1998 A
5807406 Brauker et al. Sep 1998 A
5810770 Chin et al. Sep 1998 A
5811487 Schulz, Jr. et al. Sep 1998 A
5814599 Mitragotri et al. Sep 1998 A
5820589 Torgerson et al. Oct 1998 A
5820622 Gross et al. Oct 1998 A
5822715 Worthington et al. Oct 1998 A
5836887 Oka et al. Nov 1998 A
5836989 Shelton Nov 1998 A
5837454 Cozzette et al. Nov 1998 A
5837728 Purcell Nov 1998 A
5840026 Uber, III et al. Nov 1998 A
5840148 Campbell et al. Nov 1998 A
5848991 Gross et al. Dec 1998 A
5851197 Marano et al. Dec 1998 A
5851229 Lentz et al. Dec 1998 A
5858365 Faller Jan 1999 A
5858747 Schinstine et al. Jan 1999 A
5861019 Sun et al. Jan 1999 A
5863400 Drummond et al. Jan 1999 A
5871514 Wiklund et al. Feb 1999 A
5873862 Lopez Feb 1999 A
5879713 Roth et al. Mar 1999 A
5882494 Van Antwerp Mar 1999 A
5895235 Droz Apr 1999 A
5897525 Dey et al. Apr 1999 A
5897578 Wiklund et al. Apr 1999 A
5899855 Brown May 1999 A
5904666 DeDECKER et al. May 1999 A
5904708 Goedeke May 1999 A
5911219 Aylsworth et al. Jun 1999 A
5913998 Butler et al. Jun 1999 A
5914026 Blubaugh, Jr. et al. Jun 1999 A
5917346 Gord Jun 1999 A
5919215 Wiklund et al. Jul 1999 A
5919216 Houben et al. Jul 1999 A
5921951 Morris Jul 1999 A
5925021 Castellano et al. Jul 1999 A
5928155 Eggers et al. Jul 1999 A
5928182 Kraus et al. Jul 1999 A
5928189 Phillips et al. Jul 1999 A
5928195 Malamud et al. Jul 1999 A
5931814 Alex et al. Aug 1999 A
5932175 Knute et al. Aug 1999 A
5933136 Brown Aug 1999 A
5935785 Reber et al. Aug 1999 A
5938636 Kramer et al. Aug 1999 A
5944661 Swette et al. Aug 1999 A
5947911 Wong et al. Sep 1999 A
5954643 Vanantwerp et al. Sep 1999 A
5954954 Houck et al. Sep 1999 A
5957854 Besson et al. Sep 1999 A
5957903 Mirzaee et al. Sep 1999 A
5961451 Reber et al. Oct 1999 A
5963132 Yoakum Oct 1999 A
5964745 Lyles et al. Oct 1999 A
5964993 Blubaugh, Jr. et al. Oct 1999 A
5965125 Mineau-Hanschke Oct 1999 A
5965380 Heller et al. Oct 1999 A
5971922 Arita et al. Oct 1999 A
5972369 Roorda et al. Oct 1999 A
5976085 Kimball et al. Nov 1999 A
5987352 Klein et al. Nov 1999 A
5995208 Sarge et al. Nov 1999 A
5995860 Sun et al. Nov 1999 A
5997501 Gross et al. Dec 1999 A
5999848 Gord et al. Dec 1999 A
6001067 Shults et al. Dec 1999 A
6001471 Bries et al. Dec 1999 A
6002954 Van Antwerp et al. Dec 1999 A
6007845 Domb et al. Dec 1999 A
6011984 Van Antwerp et al. Jan 2000 A
6014577 Henning et al. Jan 2000 A
6016448 Busacker et al. Jan 2000 A
6017435 Hassard et al. Jan 2000 A
6023629 Tamada Feb 2000 A
6024720 Chandler et al. Feb 2000 A
6027445 Von Bahr Feb 2000 A
6027479 Alei et al. Feb 2000 A
6032059 Henning et al. Feb 2000 A
6032667 Heinonen Mar 2000 A
6036924 Simons et al. Mar 2000 A
6043328 Domschke et al. Mar 2000 A
6045671 Wu et al. Apr 2000 A
6048691 Maracas Apr 2000 A
6049727 Crothall Apr 2000 A
6059946 Yukawa et al. May 2000 A
6063637 Arnold et al. May 2000 A
6066088 Davis May 2000 A
6066448 Wohlstadter et al. May 2000 A
6071391 Gotoh et al. Jun 2000 A
6077299 Adelberg et al. Jun 2000 A
6080583 von Bahr Jun 2000 A
6081735 Diab et al. Jun 2000 A
6081736 Colvin et al. Jun 2000 A
6083523 Dionne et al. Jul 2000 A
6083710 Heller et al. Jul 2000 A
6088608 Schulman et al. Jul 2000 A
6090087 Tsukada et al. Jul 2000 A
6091975 Daddona et al. Jul 2000 A
6093172 Funderburk et al. Jul 2000 A
6099511 Devos et al. Aug 2000 A
6103033 Say et al. Aug 2000 A
6103533 Hassard et al. Aug 2000 A
6107083 Collins et al. Aug 2000 A
6115634 Donders et al. Sep 2000 A
6117290 Say et al. Sep 2000 A
6120676 Heller et al. Sep 2000 A
6121009 Heller et al. Sep 2000 A
6122536 Sun et al. Sep 2000 A
6123827 Wong et al. Sep 2000 A
6127154 Mosbach et al. Oct 2000 A
6128519 Say Oct 2000 A
6129891 Rolander et al. Oct 2000 A
6134461 Say et al. Oct 2000 A
6135978 Houben et al. Oct 2000 A
6142939 Eppstein et al. Nov 2000 A
6144869 Berner et al. Nov 2000 A
6159186 Wickham et al. Dec 2000 A
6162201 Cohen et al. Dec 2000 A
6162611 Heller et al. Dec 2000 A
6163720 Gyory et al. Dec 2000 A
6164921 Moubayed et al. Dec 2000 A
6165154 Gray et al. Dec 2000 A
6167614 Tuttle et al. Jan 2001 B1
6168568 Gavriely Jan 2001 B1
6169155 Alvarez et al. Jan 2001 B1
6171276 Lippe et al. Jan 2001 B1
6175752 Say et al. Jan 2001 B1
6180416 Kurnik et al. Jan 2001 B1
6183437 Walker Feb 2001 B1
6187062 Oweis et al. Feb 2001 B1
6189536 Martinez et al. Feb 2001 B1
6191860 Klinger et al. Feb 2001 B1
6192891 Gravel et al. Feb 2001 B1
6201980 Darrow et al. Mar 2001 B1
6201993 Kruse et al. Mar 2001 B1
6206856 Mahurkar Mar 2001 B1
6208894 Schulman et al. Mar 2001 B1
6212416 Ward et al. Apr 2001 B1
6212424 Robinson Apr 2001 B1
6213739 Phallen et al. Apr 2001 B1
6214185 Offenbacher et al. Apr 2001 B1
6219574 Cormier et al. Apr 2001 B1
6223080 Thompson Apr 2001 B1
6223083 Rosar Apr 2001 B1
6230059 Duffin May 2001 B1
6231879 Li et al. May 2001 B1
6232783 Merrill May 2001 B1
6233080 Brenner et al. May 2001 B1
6234964 Iliff May 2001 B1
6241863 Monbouquette Jun 2001 B1
6248067 Causey, III et al. Jun 2001 B1
6248077 Elson et al. Jun 2001 B1
6248093 Moberg Jun 2001 B1
6254586 Mann et al. Jul 2001 B1
6256522 Schultz Jul 2001 B1
6259937 Schulman et al. Jul 2001 B1
6263222 Diab et al. Jul 2001 B1
6264825 Blackburn et al. Jul 2001 B1
6270478 Mernoee Aug 2001 B1
6271332 Lohmann et al. Aug 2001 B1
6272364 Kurnik Aug 2001 B1
6272382 Faltys et al. Aug 2001 B1
6272480 Tresp et al. Aug 2001 B1
6274285 Gries et al. Aug 2001 B1
6275717 Gross et al. Aug 2001 B1
6280408 Sipin Aug 2001 B1
6281015 Mooney et al. Aug 2001 B1
6284478 Heller et al. Sep 2001 B1
6293925 Safabash et al. Sep 2001 B1
6298254 Tamada Oct 2001 B2
6299578 Kurnik et al. Oct 2001 B1
6299583 Eggers et al. Oct 2001 B1
6300002 Webb et al. Oct 2001 B1
6302855 Lav et al. Oct 2001 B1
6309351 Kurnik et al. Oct 2001 B1
6309384 Harrington et al. Oct 2001 B1
6309884 Cooper et al. Oct 2001 B1
6312388 Marcovecchio et al. Nov 2001 B1
6315738 Nishikawa et al. Nov 2001 B1
6325978 Labuda et al. Dec 2001 B1
6326160 Dunn et al. Dec 2001 B1
6329161 Heller et al. Dec 2001 B1
6329929 Weijand et al. Dec 2001 B1
6330464 Colvin, Jr. et al. Dec 2001 B1
6343225 Clark, Jr. Jan 2002 B1
6356776 Berner et al. Mar 2002 B1
6358225 Butterfield Mar 2002 B1
6365670 Fry Apr 2002 B1
6366794 Moussy et al. Apr 2002 B1
6368274 Van Antwerp et al. Apr 2002 B1
6370941 Nakamura et al. Apr 2002 B2
6372244 Antanavich et al. Apr 2002 B1
6379301 Worthington et al. Apr 2002 B1
6379317 Kintzig et al. Apr 2002 B1
6383478 Prokop et al. May 2002 B1
6387709 Mason et al. May 2002 B1
6391019 Ito May 2002 B1
6400974 Lesho Jun 2002 B1
6402703 Kensey et al. Jun 2002 B1
6403944 MacKenzie et al. Jun 2002 B1
6406066 Uegane Jun 2002 B1
6407195 Sherman et al. Jun 2002 B2
6409674 Brockway et al. Jun 2002 B1
6413393 Van Antwerp et al. Jul 2002 B1
6416651 Millar Jul 2002 B1
6424847 Mastrototaro et al. Jul 2002 B1
6430437 Marro Aug 2002 B1
6447448 Ishikawa et al. Sep 2002 B1
6447542 Weadock Sep 2002 B1
6459917 Gowda et al. Oct 2002 B1
6461496 Feldman et al. Oct 2002 B1
6464849 Say et al. Oct 2002 B1
6466810 Ward et al. Oct 2002 B1
6467480 Meier et al. Oct 2002 B1
6471689 Joseph et al. Oct 2002 B1
6474360 Ito Nov 2002 B1
6475750 Han et al. Nov 2002 B1
6477392 Honigs et al. Nov 2002 B1
6477395 Schulman et al. Nov 2002 B2
6481440 Gielen et al. Nov 2002 B2
6484045 Holker et al. Nov 2002 B1
6484046 Say et al. Nov 2002 B1
6485449 Ito Nov 2002 B2
6488652 Weijand et al. Dec 2002 B1
6494830 Wessel Dec 2002 B1
6494879 Lennox et al. Dec 2002 B2
6497729 Moussy et al. Dec 2002 B1
6498043 Schulman et al. Dec 2002 B1
6498941 Jackson Dec 2002 B1
6501976 Sohrab Dec 2002 B1
6510239 Wieres et al. Jan 2003 B1
6510329 Heckel Jan 2003 B2
6512939 Colvin et al. Jan 2003 B1
6514718 Heller et al. Feb 2003 B2
6517508 Utterberg et al. Feb 2003 B1
6520326 McIvor et al. Feb 2003 B2
6520477 Trimmer Feb 2003 B2
6520937 Hart et al. Feb 2003 B2
6520997 Pekkarinen et al. Feb 2003 B1
6526298 Khalil et al. Feb 2003 B1
6527729 Turcott Mar 2003 B1
6534711 Pollack Mar 2003 B1
6536433 Cewers Mar 2003 B1
6537318 Ita et al. Mar 2003 B1
6541266 Modzelewski et al. Apr 2003 B2
6542765 Guy et al. Apr 2003 B1
6544212 Galley et al. Apr 2003 B2
6545085 Kilgour et al. Apr 2003 B2
6546268 Ishikawa et al. Apr 2003 B1
6546269 Kurnik Apr 2003 B1
6549796 Sohrab Apr 2003 B2
6551496 Moles et al. Apr 2003 B1
6553241 Mannheimer et al. Apr 2003 B2
6553244 Lesho et al. Apr 2003 B2
6554805 Hiejima Apr 2003 B2
6554822 Holschneider et al. Apr 2003 B1
6558320 Causey, III et al. May 2003 B1
6558321 Burd et al. May 2003 B1
6558347 Jhuboo et al. May 2003 B1
6558351 Steil et al. May 2003 B1
6558955 Kristal 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
6565535 Zaias et al. May 2003 B2
6565807 Patterson et al. May 2003 B1
6569195 Yang et al. May 2003 B2
6569521 Sheridan et al. May 2003 B1
6571128 Lebel et al. May 2003 B2
6572545 Knobbe et al. Jun 2003 B2
6572579 Raghavan et al. Jun 2003 B1
6574490 Abbink et al. Jun 2003 B2
6575905 Knobbe et al. Jun 2003 B2
6577899 Lebel et al. Jun 2003 B2
6579257 Elgas et al. Jun 2003 B1
6579498 Eglise Jun 2003 B1
6579690 Bonnecaze et al. Jun 2003 B1
6585644 Lebel et al. Jul 2003 B2
6585675 O'Mahony et al. Jul 2003 B1
6585763 Keilman et al. Jul 2003 B1
6587705 Kim et al. Jul 2003 B1
6589229 Connelly et al. Jul 2003 B1
6591125 Buse et al. Jul 2003 B1
6594514 Berner et al. Jul 2003 B2
6595756 Gray et al. Jul 2003 B2
6595919 Berner et al. Jul 2003 B2
6602221 Saravia et al. Aug 2003 B1
6605072 Struys et al. Aug 2003 B2
6607509 Bobroff et al. Aug 2003 B2
6609071 Shapiro et al. Aug 2003 B2
6612984 Kerr, II Sep 2003 B1
6613379 Ward et al. Sep 2003 B2
6615061 Khalil et al. Sep 2003 B1
6615078 Burson et al. Sep 2003 B1
6618603 Varalli et al. Sep 2003 B2
6618934 Feldman et al. Sep 2003 B1
6620138 Marrgi et al. Sep 2003 B1
6633772 Ford et al. Oct 2003 B2
6635014 Starkweather et al. Oct 2003 B2
6641533 Causey, III et al. Nov 2003 B2
6642015 Vachon et al. Nov 2003 B2
6645181 Lavi et al. Nov 2003 B1
6648821 Lebel et al. Nov 2003 B2
6653091 Dunn et al. Nov 2003 B1
6654625 Say et al. Nov 2003 B1
6656114 Poulsen et al. Dec 2003 B1
6656157 Duchon et al. Dec 2003 B1
6663615 Madou et al. Dec 2003 B1
6673022 Bobo et al. Jan 2004 B1
6673596 Sayler et al. Jan 2004 B1
6679865 Shekalim Jan 2004 B2
6679872 Turovskiy et al. Jan 2004 B2
6683535 Utke Jan 2004 B1
6684904 Ito Feb 2004 B2
6685668 Cho et al. Feb 2004 B1
6687522 Tamada Feb 2004 B2
6689089 Tiedtke et al. Feb 2004 B1
6689265 Heller et al. Feb 2004 B2
6694191 Starkweather et al. Feb 2004 B2
6695860 Ward et al. Feb 2004 B1
6699188 Wessel Mar 2004 B2
6699218 Flaherty et al. Mar 2004 B2
6699383 Lemire et al. Mar 2004 B2
6702249 Ito Mar 2004 B2
6702857 Brauker et al. Mar 2004 B2
6702972 Markle Mar 2004 B1
6711424 Fine et al. Mar 2004 B1
6712796 Fentis et al. Mar 2004 B2
6721587 Gough Apr 2004 B2
6723086 Bassuk et al. Apr 2004 B2
6731976 Penn et al. May 2004 B2
6736783 Blake et al. May 2004 B2
6740072 Starkweather May 2004 B2
6740075 Lebel et al. May 2004 B2
6741877 Shults et al. May 2004 B1
6742635 Hirshberg Jun 2004 B2
6743635 Neel et al. Jun 2004 B2
6749587 Flaherty Jun 2004 B2
6750055 Connelly et al. Jun 2004 B1
6770030 Schaupp et al. Aug 2004 B1
6770067 Lorenzen et al. Aug 2004 B2
6773565 Kunimoto et al. Aug 2004 B2
6780297 Matsumoto et al. Aug 2004 B2
6793632 Sohrab Sep 2004 B2
6801041 Karinka et al. Oct 2004 B2
6802957 Jung et al. Oct 2004 B2
6804002 Fine et al. Oct 2004 B2
6805693 Gray et al. Oct 2004 B2
6809653 Mann et al. Oct 2004 B1
6810290 Lebel et al. Oct 2004 B2
6811548 Jeffrey Nov 2004 B2
6813519 Lebel et al. Nov 2004 B2
6832200 Greeven et al. Dec 2004 B2
6850790 Berner et al. Feb 2005 B2
6858020 Rusnak Feb 2005 B2
6862465 Shults et al. Mar 2005 B2
6869413 Langley et al. Mar 2005 B2
6875195 Choi Apr 2005 B2
6887228 McKay May 2005 B2
6892085 McIvor et al. May 2005 B2
6893552 Wang et al. May 2005 B1
6895263 Shin et al. May 2005 B2
6895265 Silver May 2005 B2
6902544 Ludin et al. Jun 2005 B2
6925393 Kalatz et al. Aug 2005 B1
6926691 Miethke Aug 2005 B2
6931327 Goode, Jr. et al. Aug 2005 B2
6932584 Gray et al. Aug 2005 B2
6936006 Sabra Aug 2005 B2
6936029 Mann et al. Aug 2005 B2
6945965 Whiting Sep 2005 B2
6948492 Wermeling et al. Sep 2005 B2
6952604 Denuzzio et al. Oct 2005 B2
6954662 Freger et al. Oct 2005 B2
6960192 Flaherty et al. Nov 2005 B1
6965791 Hitchcock et al. Nov 2005 B1
6966325 Erickson Nov 2005 B2
6975893 Say et al. Dec 2005 B2
6979315 Rogers et al. Dec 2005 B2
6989891 Braig et al. Jan 2006 B2
6997921 Gray et al. Feb 2006 B2
6998247 Monfre et al. Feb 2006 B2
7008979 Schottman et al. Mar 2006 B2
7011630 Desai et al. Mar 2006 B2
7016713 Gardner et al. Mar 2006 B2
7022072 Fox et al. Apr 2006 B2
7022219 Mansouri et al. Apr 2006 B2
7025727 Brockway et al. Apr 2006 B2
7025743 Mann et al. Apr 2006 B2
7027848 Robinson et al. Apr 2006 B2
7029444 Shin et al. Apr 2006 B2
7033322 Silver Apr 2006 B2
7044911 Drinan et al. May 2006 B2
7048727 Moss May 2006 B1
7058437 Buse et al. Jun 2006 B2
7060059 Keith et al. Jun 2006 B2
7061593 Braig et al. Jun 2006 B2
7063086 Shahbazpour et al. Jun 2006 B2
7066884 Custer et al. Jun 2006 B2
7070577 Haller et al. Jul 2006 B1
7074307 Simpson et al. Jul 2006 B2
7081195 Simpson et al. Jul 2006 B2
7097775 Greenberg et al. Aug 2006 B2
7098803 Mann et al. Aug 2006 B2
7100628 Izenson et al. Sep 2006 B1
7108778 Simpson et al. Sep 2006 B2
7120483 Russell et al. Oct 2006 B2
7131967 Gray et al. Nov 2006 B2
7134999 Brauker et al. Nov 2006 B2
7136689 Shults et al. Nov 2006 B2
7146202 Ward et al. Dec 2006 B2
7150741 Erickson et al. Dec 2006 B2
7162290 Levin Jan 2007 B1
7166074 Reghabi et al. Jan 2007 B2
7168597 Jones et al. Jan 2007 B1
7169289 Schuelein et al. Jan 2007 B2
7183102 Monfre et al. Feb 2007 B2
7184810 Caduff et al. Feb 2007 B2
7207968 Harcinske Apr 2007 B1
7211074 Sansoucy May 2007 B2
7221970 Parker May 2007 B2
7223253 Hogendijk May 2007 B2
7225535 Feldman et al. Jun 2007 B2
7228162 Ward et al. Jun 2007 B2
7229288 Stuart et al. Jun 2007 B2
7238165 Vincent et al. Jul 2007 B2
7247138 Reghabi et al. Jul 2007 B2
7254450 Christopherson et al. Aug 2007 B2
7255690 Gray et al. Aug 2007 B2
7258681 Houde Aug 2007 B2
7261690 Teller et al. Aug 2007 B2
7266400 Fine et al. Sep 2007 B2
7267665 Steil et al. Sep 2007 B2
7276029 Goode, Jr. et al. Oct 2007 B2
7278983 Ireland et al. Oct 2007 B2
7279174 Pacetti et al. Oct 2007 B2
7282029 Poulsen et al. Oct 2007 B1
7288085 Olsen Oct 2007 B2
7291114 Mault Nov 2007 B2
7295867 Berner et al. Nov 2007 B2
7299082 Feldman et al. Nov 2007 B2
7311690 Burnett Dec 2007 B2
7313425 Finarov et al. Dec 2007 B2
7314452 Madonia Jan 2008 B2
7315767 Caduff et al. Jan 2008 B2
7316662 Delnevo et al. Jan 2008 B2
7317939 Fine et al. Jan 2008 B2
7318814 Levine et al. Jan 2008 B2
7327273 Hung et al. Feb 2008 B2
7329234 Sansoucy Feb 2008 B2
7334594 Ludin Feb 2008 B2
7335179 Burnett Feb 2008 B2
7335195 Mehier Feb 2008 B2
7338464 Blischak et al. Mar 2008 B2
7344500 Talbot et al. Mar 2008 B2
7354420 Steil et al. Apr 2008 B2
7357793 Pacetti Apr 2008 B2
7359723 Jones Apr 2008 B2
7361155 Sage, Jr. et al. Apr 2008 B2
7364562 Braig et al. Apr 2008 B2
7367942 Grage et al. May 2008 B2
7396353 Lorenzen et al. Jul 2008 B2
7399277 Saidara et al. Jul 2008 B2
7402153 Steil et al. Jul 2008 B2
7417164 Suri Aug 2008 B2
7426408 Denuzzio et al. Sep 2008 B2
7433727 Ward et al. Oct 2008 B2
7519408 Rasdal et al. Apr 2009 B2
7519478 Bartkowiak et al. Apr 2009 B2
7523004 Bartkowiak et al. Apr 2009 B2
7534230 Follman et al. May 2009 B2
7569030 Lebel et al. Aug 2009 B2
7583990 Goode, Jr. et al. Sep 2009 B2
7591801 Brauker et al. Sep 2009 B2
7599726 Goode, Jr. et al. Oct 2009 B2
7604593 Parris et al. Oct 2009 B2
7615007 Shults et al. Nov 2009 B2
7618368 Brown Nov 2009 B2
7618369 Hayter et al. Nov 2009 B2
7624028 Brown Nov 2009 B1
7640032 Jones Dec 2009 B2
7640048 Dobbles et al. Dec 2009 B2
7647237 Malave et al. Jan 2010 B2
7654955 Polidori et al. Feb 2010 B2
7657297 Simpson et al. Feb 2010 B2
7670288 Sher Mar 2010 B2
7695434 Malecha Apr 2010 B2
7727147 Osorio et al. Jun 2010 B1
7731659 Malecha Jun 2010 B2
7761126 Gardner et al. Jul 2010 B2
7766830 Fox et al. Aug 2010 B2
7857760 Brister et al. Dec 2010 B2
7901394 Ireland et al. Mar 2011 B2
7905833 Brister et al. Mar 2011 B2
7927274 Rasdal et al. Apr 2011 B2
7946985 Mastrototaro et al. May 2011 B2
7976492 Brauker et al. Jul 2011 B2
8000901 Brauker et al. Aug 2011 B2
8005524 Brauker et al. Aug 2011 B2
8005525 Goode, Jr. et al. Aug 2011 B2
8010174 Goode, Jr. et al. Aug 2011 B2
8460231 Brauker et al. Jun 2013 B2
8512276 Talbot et al. Aug 2013 B2
8721585 Brauker et al. May 2014 B2
8808228 Brister et al. Aug 2014 B2
8882741 Brauker et al. Nov 2014 B2
8920401 Brauker et al. Dec 2014 B2
8926585 Brauker et al. Jan 2015 B2
9050413 Brauker et al. Jun 2015 B2
9155843 Brauker et al. Oct 2015 B2
9451908 Kamath et al. Sep 2016 B2
9452258 Dobbles et al. Sep 2016 B2
9452259 Dobbles et al. Sep 2016 B2
9457146 Dobbles et al. Oct 2016 B2
9463277 Dobbles et al. Oct 2016 B2
9572935 Dobbles et al. Feb 2017 B2
9572936 Dobbles et al. Feb 2017 B2
9586004 Dobbles et al. Mar 2017 B2
9597453 Dobbles et al. Mar 2017 B2
9827372 Dobbles et al. Nov 2017 B2
9937293 Brauker et al. Apr 2018 B2
10278580 Brister et al. May 2019 B2
10653835 Dobbles et al. May 2020 B2
10966609 Brister et al. Apr 2021 B2
11744943 Dobbles et al. Sep 2023 B2
20010007950 North et al. Jul 2001 A1
20010016682 Berner et al. Aug 2001 A1
20010021817 Brugger et al. Sep 2001 A1
20010039053 Liseo et al. Nov 2001 A1
20010041830 Varalli et al. Nov 2001 A1
20010044588 Mault Nov 2001 A1
20010051768 Schulman et al. Dec 2001 A1
20020009810 O'Connor et al. Jan 2002 A1
20020016535 Martin et al. Feb 2002 A1
20020016719 Nemeth Feb 2002 A1
20020018843 Van Antwerp et al. Feb 2002 A1
20020019022 Dunn et al. Feb 2002 A1
20020019330 Murray et al. Feb 2002 A1
20020022883 Burg Feb 2002 A1
20020023852 McIvor et al. Feb 2002 A1
20020026110 Parris et al. Feb 2002 A1
20020026111 Ackerman Feb 2002 A1
20020042090 Heller et al. Apr 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
20020068860 Clark Jun 2002 A1
20020071776 Bandis et al. Jun 2002 A1
20020084196 Liamos et al. Jul 2002 A1
20020099282 Knobbe et al. Jul 2002 A1
20020099997 Piret Jul 2002 A1
20020111547 Knobbe et al. Aug 2002 A1
20020119711 Vanantwerp et al. Aug 2002 A1
20020123048 Gau Sep 2002 A1
20020133224 Bajgar et al. Sep 2002 A1
20020151796 Koulik Oct 2002 A1
20020155615 Novikov et al. Oct 2002 A1
20020161288 Shin et al. Oct 2002 A1
20020182241 Borenstein et al. Dec 2002 A1
20020188185 Sohrab Dec 2002 A1
20020193679 Malave et al. Dec 2002 A1
20020193885 Legeay et al. Dec 2002 A1
20020198513 Lebel et al. Dec 2002 A1
20030004432 Assenheimer Jan 2003 A1
20030006669 Pei et al. Jan 2003 A1
20030021729 Moller et al. Jan 2003 A1
20030023171 Sato et al. Jan 2003 A1
20030023317 Brauker et al. Jan 2003 A1
20030028089 Galley et al. Feb 2003 A1
20030031699 Van Antwerp Feb 2003 A1
20030032874 Rhodes et al. Feb 2003 A1
20030050546 Desai et al. Mar 2003 A1
20030054428 Monfre et al. Mar 2003 A1
20030060692 L. Ruchti et al. Mar 2003 A1
20030060753 Starkweather et al. Mar 2003 A1
20030060765 Campbell et al. Mar 2003 A1
20030070548 Clausen Apr 2003 A1
20030072741 Berglund et al. Apr 2003 A1
20030076082 Morgan et al. Apr 2003 A1
20030078481 McIvor et al. Apr 2003 A1
20030078560 Miller et al. Apr 2003 A1
20030088238 Poulsen et al. May 2003 A1
20030091433 Tam et al. May 2003 A1
20030097082 Purdy et al. May 2003 A1
20030099682 Moussy et al. May 2003 A1
20030100040 Bonnecaze et al. May 2003 A1
20030100821 Heller et al. May 2003 A1
20030114836 Estes et al. Jun 2003 A1
20030117296 Seely Jun 2003 A1
20030119208 Yoon et al. Jun 2003 A1
20030120152 Omiya Jun 2003 A1
20030125612 Fox et al. Jul 2003 A1
20030125613 Enegren et al. Jul 2003 A1
20030130616 Steil et al. Jul 2003 A1
20030132227 Geisler et al. Jul 2003 A1
20030134347 Heller et al. Jul 2003 A1
20030143746 Sage Jul 2003 A1
20030153821 Berner et al. Aug 2003 A1
20030176183 Drucker et al. Sep 2003 A1
20030187338 Say et al. Oct 2003 A1
20030188427 Say et al. Oct 2003 A1
20030199744 Buse et al. Oct 2003 A1
20030199745 Burson et al. Oct 2003 A1
20030208113 Mault et al. Nov 2003 A1
20030211050 Majeti et al. Nov 2003 A1
20030211625 Cohan et al. Nov 2003 A1
20030212317 Kovatchev et al. Nov 2003 A1
20030212346 Yuzhakov et al. Nov 2003 A1
20030212347 Sohrab Nov 2003 A1
20030212379 Bylund et al. Nov 2003 A1
20030225324 Anderson et al. Dec 2003 A1
20030225437 Ferguson Dec 2003 A1
20030231550 MacFarlane Dec 2003 A1
20030235817 Bartkowiak et al. Dec 2003 A1
20040006263 Anderson et al. Jan 2004 A1
20040010207 Flaherty et al. Jan 2004 A1
20040011671 Shults et al. Jan 2004 A1
20040015063 Denuzzio et al. Jan 2004 A1
20040015134 Lavi et al. Jan 2004 A1
20040023253 Kunwar et al. Feb 2004 A1
20040023317 Motamedi et al. Feb 2004 A1
20040024327 Brodnick Feb 2004 A1
20040030285 Lavi et al. Feb 2004 A1
20040030294 Mahurkar Feb 2004 A1
20040039298 Abreu Feb 2004 A1
20040039406 Jessen Feb 2004 A1
20040040840 Mao et al. Mar 2004 A1
20040044272 Moerman et al. Mar 2004 A1
20040045879 Shults et al. Mar 2004 A1
20040052689 Yao Mar 2004 A1
20040054352 Adams et al. Mar 2004 A1
20040068230 Estes et al. Apr 2004 A1
20040074785 Holker et al. Apr 2004 A1
20040078219 Kaylor et al. Apr 2004 A1
20040106857 Gough Jun 2004 A1
20040122297 Stahmann et al. Jun 2004 A1
20040122353 Shahmirian et al. Jun 2004 A1
20040138543 Russell et al. Jul 2004 A1
20040143173 Reghabi et al. Jul 2004 A1
20040146909 Duong et al. Jul 2004 A1
20040152187 Haight et al. Aug 2004 A1
20040152622 Keith 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
20040176672 Silver et al. Sep 2004 A1
20040180391 Gratzl et al. Sep 2004 A1
20040186362 Brauker et al. Sep 2004 A1
20040186365 Jin et al. Sep 2004 A1
20040193025 Steil et al. Sep 2004 A1
20040199059 Brauker et al. Oct 2004 A1
20040204687 Mogensen et al. Oct 2004 A1
20040219664 Heller et al. Nov 2004 A1
20040220517 Starkweather et al. Nov 2004 A1
20040224001 Pacetti et al. Nov 2004 A1
20040248282 Sobha M et al. Dec 2004 A1
20040253365 Warren et al. Dec 2004 A1
20040254433 Bandis et al. Dec 2004 A1
20050003399 Blackburn et al. Jan 2005 A1
20050010265 Baru et al. Jan 2005 A1
20050026689 Marks Feb 2005 A1
20050027180 Goode, Jr. et al. Feb 2005 A1
20050027181 Goode, Jr. et al. Feb 2005 A1
20050027182 Siddiqui et al. Feb 2005 A1
20050027462 Goode, Jr. et al. Feb 2005 A1
20050027463 Goode, Jr. et al. Feb 2005 A1
20050031689 Shults et al. Feb 2005 A1
20050033132 Shults et al. Feb 2005 A1
20050038332 Saidara et al. Feb 2005 A1
20050043598 Goode, Jr. et al. Feb 2005 A1
20050049472 Manda et al. Mar 2005 A1
20050051427 Brauker et al. Mar 2005 A1
20050051440 Simpson et al. Mar 2005 A1
20050054909 Petisce et al. Mar 2005 A1
20050056552 Simpson et al. Mar 2005 A1
20050065464 Talbot et al. Mar 2005 A1
20050077584 Uhland et al. Apr 2005 A1
20050090607 Tapsak et al. Apr 2005 A1
20050096519 Denuzzio et al. May 2005 A1
20050101847 Routt et al. May 2005 A1
20050107677 Ward et al. May 2005 A1
20050112169 Brauker et al. May 2005 A1
20050113653 Fox et al. May 2005 A1
20050113744 Donoghue et al. May 2005 A1
20050115832 Simpson et al. Jun 2005 A1
20050118344 Pacetti Jun 2005 A1
20050119720 Gale et al. Jun 2005 A1
20050121322 Say et al. Jun 2005 A1
20050124873 Shults et al. Jun 2005 A1
20050131305 Danielson et al. Jun 2005 A1
20050139489 Davies et al. Jun 2005 A1
20050143635 Kamath et al. Jun 2005 A1
20050143675 Neel et al. Jun 2005 A1
20050154271 Rasdal et al. Jul 2005 A1
20050176136 Burd et al. Aug 2005 A1
20050177036 Shults et al. Aug 2005 A1
20050177398 Watanabe et al. Aug 2005 A1
20050181012 Saint et al. Aug 2005 A1
20050182451 Griffin et al. Aug 2005 A1
20050183954 Hitchcock et al. Aug 2005 A1
20050187720 Goode, Jr. et al. Aug 2005 A1
20050192557 Brauker et al. Sep 2005 A1
20050197553 Cooper Sep 2005 A1
20050197554 Polcha Sep 2005 A1
20050203360 Brauker et al. Sep 2005 A1
20050211571 Schulein et al. Sep 2005 A1
20050215871 Feldman et al. Sep 2005 A1
20050215872 Berner et al. Sep 2005 A1
20050239154 Feldman et al. Oct 2005 A1
20050242479 Petisce et al. Nov 2005 A1
20050245795 Goode, Jr. et al. Nov 2005 A1
20050245799 Brauker et al. Nov 2005 A1
20050245904 Estes et al. Nov 2005 A1
20050251083 Carr-Brendel et al. Nov 2005 A1
20050261563 Zhou et al. Nov 2005 A1
20050288596 Eigler et al. Dec 2005 A1
20060001550 Mann et al. Jan 2006 A1
20060015020 Neale et al. Jan 2006 A1
20060015024 Brister et al. Jan 2006 A1
20060016700 Brister et al. Jan 2006 A1
20060019327 Brister et al. Jan 2006 A1
20060020186 Brister et al. Jan 2006 A1
20060020187 Brister et al. Jan 2006 A1
20060020188 Kamath et al. Jan 2006 A1
20060020189 Brister et al. Jan 2006 A1
20060020190 Kamath et al. Jan 2006 A1
20060020191 Brister et al. Jan 2006 A1
20060020192 Brister et al. Jan 2006 A1
20060036139 Brister et al. Feb 2006 A1
20060036140 Brister et al. Feb 2006 A1
20060036141 Kamath et al. Feb 2006 A1
20060036142 Brister et al. Feb 2006 A1
20060036143 Brister et al. Feb 2006 A1
20060036144 Brister et al. Feb 2006 A1
20060036145 Brister et al. Feb 2006 A1
20060040402 Brauker et al. Feb 2006 A1
20060047095 Pacetti Mar 2006 A1
20060052745 Van Antwerp et al. Mar 2006 A1
20060067908 Ding Mar 2006 A1
20060078908 Pitner et al. Apr 2006 A1
20060079740 Silver et al. Apr 2006 A1
20060079809 Goldberger et al. Apr 2006 A1
20060094946 Kellogg et al. May 2006 A1
20060100588 Brunnberg et al. May 2006 A1
20060134165 Pacetti Jun 2006 A1
20060171980 Helmus et al. Aug 2006 A1
20060173406 Hayes et al. Aug 2006 A1
20060177379 Asgari Aug 2006 A1
20060183871 Ward et al. Aug 2006 A1
20060183984 Dobbles et al. Aug 2006 A1
20060183985 Brister et al. Aug 2006 A1
20060189863 Peyser et al. Aug 2006 A1
20060195029 Shults et al. Aug 2006 A1
20060222566 Brauker et al. Oct 2006 A1
20060224141 Rush et al. Oct 2006 A1
20060253085 Geismar et al. Nov 2006 A1
20060258929 Goode, Jr. et al. Nov 2006 A1
20060263839 Ward et al. Nov 2006 A1
20060269586 Pacetti Nov 2006 A1
20060275857 Kjaer et al. Dec 2006 A1
20060281985 Ward et al. Dec 2006 A1
20070007133 Mang et al. Jan 2007 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
20070049873 Hansen et al. Mar 2007 A1
20070066873 Kamath et al. Mar 2007 A1
20070066956 Finkel Mar 2007 A1
20070085995 Pesach et al. Apr 2007 A1
20070100222 Mastrototaro et al. May 2007 A1
20070106135 Sloan et al. May 2007 A1
20070112298 Mueller, Jr. et al. May 2007 A1
20070116600 Kochar et al. May 2007 A1
20070129619 Ward et al. Jun 2007 A1
20070129621 Kellogg et al. Jun 2007 A1
20070135698 Shah et al. Jun 2007 A1
20070135699 Ward et al. Jun 2007 A1
20070151869 Heller et al. Jul 2007 A1
20070173706 Neinast et al. Jul 2007 A1
20070173710 Petisce et al. Jul 2007 A1
20070173761 Kanderian, Jr. et al. Jul 2007 A1
20070179434 Weinert et al. Aug 2007 A1
20070197889 Brister et al. Aug 2007 A1
20070200254 Curry Aug 2007 A1
20070200267 Tsai Aug 2007 A1
20070203407 Hoss et al. Aug 2007 A1
20070203410 Say et al. Aug 2007 A1
20070203966 Brauker et al. Aug 2007 A1
20070206193 Pesach Sep 2007 A1
20070208244 Brauker et al. Sep 2007 A1
20070208245 Brauker et al. Sep 2007 A1
20070208246 Brauker et al. Sep 2007 A1
20070213610 Say et al. Sep 2007 A1
20070218097 Heller et al. Sep 2007 A1
20070219441 Carlin et al. Sep 2007 A1
20070225579 Lucassen et al. Sep 2007 A1
20070225675 Robinson et al. Sep 2007 A1
20070227907 Shah et al. Oct 2007 A1
20070233013 Schoenberg Oct 2007 A1
20070235331 Simpson et al. Oct 2007 A1
20070240497 Robinson et al. Oct 2007 A1
20070244381 Robinson et al. Oct 2007 A1
20070244382 Robinson et al. Oct 2007 A1
20070249916 Pesach et al. Oct 2007 A1
20070255126 Moberg et al. Nov 2007 A1
20070275193 Desimone et al. Nov 2007 A1
20070293742 Simonsen et al. Dec 2007 A1
20070299409 Whitbourne et al. Dec 2007 A1
20080021666 Goode, Jr. et al. Jan 2008 A1
20080021668 Son Jan 2008 A1
20080027301 Ward et al. Jan 2008 A1
20080029390 Roche et al. Feb 2008 A1
20080029391 Mao et al. Feb 2008 A1
20080033254 Kamath et al. Feb 2008 A1
20080034972 Gough et al. Feb 2008 A1
20080045824 Tapsak et al. Feb 2008 A1
20080071157 McGarraugh et al. Mar 2008 A1
20080071158 McGarraugh et al. Mar 2008 A1
20080072663 Keenan et al. Mar 2008 A1
20080086040 Heller et al. Apr 2008 A1
20080086041 Heller et al. Apr 2008 A1
20080086042 Brister et al. Apr 2008 A1
20080086043 Heller et al. Apr 2008 A1
20080086044 Brister et al. Apr 2008 A1
20080086273 Shults et al. Apr 2008 A1
20080091094 Heller et al. Apr 2008 A1
20080091095 Heller et al. Apr 2008 A1
20080097289 Steil et al. Apr 2008 A1
20080108942 Brister et al. May 2008 A1
20080119703 Brister et al. May 2008 A1
20080119704 Brister et al. May 2008 A1
20080119706 Brister et al. May 2008 A1
20080125751 Fjield et al. May 2008 A1
20080139910 Mastrototaro et al. Jun 2008 A1
20080154101 Jain et al. Jun 2008 A1
20080183061 Goode et al. Jul 2008 A1
20080183399 Goode et al. Jul 2008 A1
20080187655 Markle et al. Aug 2008 A1
20080188722 Markle et al. Aug 2008 A1
20080188725 Markle et al. Aug 2008 A1
20080188731 Brister et al. Aug 2008 A1
20080189051 Goode et al. Aug 2008 A1
20080193936 Squirrell Aug 2008 A1
20080194837 Kim et al. Aug 2008 A1
20080194935 Brister et al. Aug 2008 A1
20080194936 Goode et al. Aug 2008 A1
20080194937 Goode et al. Aug 2008 A1
20080195967 Goode et al. Aug 2008 A1
20080197024 Simpson et al. Aug 2008 A1
20080200788 Brister et al. Aug 2008 A1
20080200789 Brister et al. Aug 2008 A1
20080200791 Simpson et al. Aug 2008 A1
20080208025 Shults et al. Aug 2008 A1
20080210557 Heller et al. Sep 2008 A1
20080214915 Brister et al. Sep 2008 A1
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
20080300572 Rankers et al. Dec 2008 A1
20080305009 Gamsey et al. Dec 2008 A1
20080305506 Suri Dec 2008 A1
20080306368 Goode, Jr. et al. Dec 2008 A1
20080306433 Cesaroni Dec 2008 A1
20080306434 Dobbles et al. Dec 2008 A1
20080306435 Kamath et al. Dec 2008 A1
20080306444 Brister et al. Dec 2008 A1
20090005666 Shin et al. Jan 2009 A1
20090012379 Goode, Jr. et al. Jan 2009 A1
20090018418 Markle et al. Jan 2009 A1
20090018424 Kamath et al. Jan 2009 A1
20090018426 Markle et al. Jan 2009 A1
20090036758 Brauker et al. Feb 2009 A1
20090043181 Brauker et al. Feb 2009 A1
20090043182 Brauker et al. Feb 2009 A1
20090043525 Brauker et al. Feb 2009 A1
20090043541 Brauker et al. Feb 2009 A1
20090043542 Brauker et al. Feb 2009 A1
20090061528 Suri Mar 2009 A1
20090062635 Brauker et al. Mar 2009 A1
20090062645 Fehre et al. Mar 2009 A1
20090076356 Simpson et al. Mar 2009 A1
20090076360 Brister et al. Mar 2009 A1
20090076361 Kamath et al. Mar 2009 A1
20090081803 Gamsey et al. Mar 2009 A1
20090099434 Liu et al. Apr 2009 A1
20090124877 Goode, Jr. et al. May 2009 A1
20090124878 Goode, Jr. et al. May 2009 A1
20090124964 Leach et al. May 2009 A1
20090131768 Simpson et al. May 2009 A1
20090131769 Leach et al. May 2009 A1
20090131776 Simpson et al. May 2009 A1
20090131777 Simpson et al. May 2009 A1
20090137886 Shariati et al. May 2009 A1
20090137887 Shariati et al. May 2009 A1
20090143659 Li et al. Jun 2009 A1
20090156924 Shariati et al. Jun 2009 A1
20090177143 Markle et al. Jul 2009 A1
20090178459 Li et al. Jul 2009 A1
20090182217 Li et al. Jul 2009 A1
20090192366 Mensinger et al. Jul 2009 A1
20090192380 Shariati et al. Jul 2009 A1
20090192722 Shariati et al. Jul 2009 A1
20090192724 Brauker et al. Jul 2009 A1
20090192745 Kamath et al. Jul 2009 A1
20090192751 Kamath et al. Jul 2009 A1
20090203981 Brauker et al. Aug 2009 A1
20090204341 Brauker et al. Aug 2009 A1
20090216103 Brister et al. Aug 2009 A1
20090240120 Mensinger et al. Sep 2009 A1
20090240128 Mensinger et al. Sep 2009 A1
20090240193 Mensinger et al. Sep 2009 A1
20090242399 Kamath et al. Oct 2009 A1
20090242425 Kamath et al. Oct 2009 A1
20090264719 Markle et al. Oct 2009 A1
20090264856 Lebel et al. Oct 2009 A1
20090287074 Shults et al. Nov 2009 A1
20090299155 Yang et al. Dec 2009 A1
20090299156 Simpson et al. Dec 2009 A1
20090299162 Brauker et al. Dec 2009 A1
20090299276 Brauker et al. Dec 2009 A1
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
20100030485 Brauker et al. Feb 2010 A1
20100036215 Goode, Jr. et al. Feb 2010 A1
20100036216 Goode, Jr. et al. Feb 2010 A1
20100036222 Goode, Jr. et al. Feb 2010 A1
20100036223 Goode, Jr. et al. Feb 2010 A1
20100036224 Goode, Jr. et al. Feb 2010 A1
20100036225 Goode, Jr. et al. Feb 2010 A1
20100041971 Goode, Jr. et al. Feb 2010 A1
20100045465 Brauker et al. Feb 2010 A1
20100049024 Saint et al. Feb 2010 A1
20100076283 Simpson et al. Mar 2010 A1
20100081908 Dobbles et al. Apr 2010 A1
20100081910 Brister et al. Apr 2010 A1
20100161269 Kamath et al. Jun 2010 A1
20100179401 Rasdal et al. Jul 2010 A1
20100179407 Goode, Jr. et al. Jul 2010 A1
20100179408 Kamath et al. Jul 2010 A1
20100179409 Kamath et al. Jul 2010 A1
20100234707 Goode, Jr. et al. Sep 2010 A1
20100235106 Kamath et al. Sep 2010 A1
20100240975 Goode, Jr. et al. Sep 2010 A1
20100240976 Goode, Jr. et al. Sep 2010 A1
20100331656 Mensinger et al. Dec 2010 A1
20100331657 Mensinger et al. Dec 2010 A1
20110009727 Mensinger et al. Jan 2011 A1
20110118579 Goode, Jr. et al. May 2011 A1
20110124997 Goode, Jr. et al. May 2011 A1
20110130970 Goode, Jr. et al. Jun 2011 A1
20110137601 Goode, Jr. et al. Jun 2011 A1
20110201910 Rasdal et al. Aug 2011 A1
20110218414 Kamath et al. Sep 2011 A1
20110231107 Brauker et al. Sep 2011 A1
20110231140 Goode, Jr. et al. Sep 2011 A1
20110231141 Goode, Jr. et al. Sep 2011 A1
20110231142 Goode, Jr. et al. Sep 2011 A1
20110257895 Brauker et al. Oct 2011 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
20180043096 Dobbles et al. Feb 2018 A1
20180185587 Brauker et al. Jul 2018 A1
20190070360 Sloan et al. Mar 2019 A1
20190209009 Brister et al. Jul 2019 A1
Foreign Referenced Citations (152)
Number Date Country
2127172 Jul 1998 CA
0098592 Jan 1984 EP
0107634 May 1984 EP
0127958 Dec 1984 EP
0286118 Oct 1988 EP
0288793 Nov 1988 EP
0320109 Jun 1989 EP
0352610 Jan 1990 EP
0352631 Jan 1990 EP
0353328 Feb 1990 EP
0390390 Oct 1990 EP
0396788 Nov 1990 EP
0406473 Jan 1991 EP
0440044 Aug 1991 EP
0441252 Aug 1991 EP
0441394 Aug 1991 EP
0467078 Jan 1992 EP
0534074 Mar 1993 EP
0535898 Apr 1993 EP
0539751 May 1993 EP
0563795 Oct 1993 EP
0323605 Jan 1994 EP
0647849 Apr 1995 EP
0424633 Jan 1996 EP
0729366 Sep 1996 EP
0747069 Dec 1996 EP
0776628 Jun 1997 EP
0817809 Jan 1998 EP
0838230 Apr 1998 EP
0880936 Dec 1998 EP
0885932 Dec 1998 EP
0967788 Dec 1999 EP
0995805 Apr 2000 EP
1077634 Feb 2001 EP
1078258 Feb 2001 EP
1102194 May 2001 EP
0789540 Sep 2001 EP
1153571 Nov 2001 EP
0817809 Jul 2002 EP
1266607 Dec 2002 EP
1338295 Aug 2003 EP
1067862 May 2004 EP
1498067 Jan 2005 EP
1571582 Sep 2005 EP
2223710 Sep 2010 EP
2226086 Sep 2010 EP
2228642 Sep 2010 EP
2656423 Jun 1991 FR
2760962 Sep 1998 FR
1442303 Jul 1976 GB
2149918 Jun 1985 GB
S6283649 Apr 1987 JP
S6283849 Apr 1987 JP
H0783871 Mar 1995 JP
2000060826 Feb 2000 JP
2002515302 May 2002 JP
2002189015 Jul 2002 JP
2003108679 Apr 2003 JP
2004000555 Jan 2004 JP
WO-8902720 Apr 1989 WO
WO-9000738 Jan 1990 WO
WO-9010861 Sep 1990 WO
WO-9013021 Nov 1990 WO
WO-9116416 Oct 1991 WO
WO-9213271 Aug 1992 WO
WO-9314693 Aug 1993 WO
WO-9323744 Nov 1993 WO
WO-9422367 Oct 1994 WO
WO-9507109 Mar 1995 WO
WO-9513838 May 1995 WO
WO-9601611 Jan 1996 WO
WO-9603117 Feb 1996 WO
WO-9614026 May 1996 WO
WO-9625089 Aug 1996 WO
WO-9630431 Oct 1996 WO
WO-9632076 Oct 1996 WO
WO-9637246 Nov 1996 WO
WO-9701986 Jan 1997 WO
WO-9706727 Feb 1997 WO
WO-9719188 May 1997 WO
WO-9728737 Aug 1997 WO
WO-9743633 Nov 1997 WO
WO-9824358 Jun 1998 WO
WO-9838906 Sep 1998 WO
WO-9948419 Sep 1999 WO
WO-9956613 Nov 1999 WO
WO-9958051 Nov 1999 WO
WO-9958973 Nov 1999 WO
WO-9959657 Nov 1999 WO
WO-0012720 Mar 2000 WO
WO-0013002 Mar 2000 WO
WO-0013003 Mar 2000 WO
WO-0019887 Apr 2000 WO
WO-0032098 Jun 2000 WO
WO-0033065 Jun 2000 WO
WO-0049941 Aug 2000 WO
WO-0059373 Oct 2000 WO
WO-0074753 Dec 2000 WO
WO-0078210 Dec 2000 WO
WO-0112158 Feb 2001 WO
WO-0116579 Mar 2001 WO
WO-0120019 Mar 2001 WO
WO-0120334 Mar 2001 WO
WO-0134243 May 2001 WO
WO-0143660 Jun 2001 WO
WO-0152727 Jul 2001 WO
WO-0158348 Aug 2001 WO
WO-0168901 Sep 2001 WO
WO-0169222 Sep 2001 WO
WO-0188524 Nov 2001 WO
WO-0188534 Nov 2001 WO
WO-0205702 Jan 2002 WO
WO-0224065 Mar 2002 WO
WO-0078210 May 2002 WO
WO-02082989 Oct 2002 WO
WO-02089666 Nov 2002 WO
WO-02100266 Dec 2002 WO
WO-03000127 Jan 2003 WO
WO-03022125 Mar 2003 WO
WO-03022327 Mar 2003 WO
03047426 Jun 2003 WO
WO-03063700 Aug 2003 WO
WO-03072269 Sep 2003 WO
WO-03101862 Dec 2003 WO
WO-2004009161 Jan 2004 WO
WO-2004110256 Dec 2004 WO
WO-2005011489 Feb 2005 WO
WO-2005012873 Feb 2005 WO
WO-2005026689 Mar 2005 WO
WO-2005032400 Apr 2005 WO
WO-2005057168 Jun 2005 WO
WO-2005057175 Jun 2005 WO
WO-2005078424 Aug 2005 WO
WO-2005026689 Oct 2005 WO
WO-2005093629 Oct 2005 WO
2005106446 Nov 2005 WO
WO-2006017358 Feb 2006 WO
WO-2006021430 Mar 2006 WO
WO-2006050405 May 2006 WO
WO-2006105146 Oct 2006 WO
WO-2006118713 Nov 2006 WO
WO-2006131288 Dec 2006 WO
WO-2007002209 Jan 2007 WO
WO-2007002579 Jan 2007 WO
WO-2007065285 Jun 2007 WO
WO-2007097754 Aug 2007 WO
WO-2007114943 Oct 2007 WO
WO-2007127606 Nov 2007 WO
WO-2007137286 Nov 2007 WO
WO-2007143225 Dec 2007 WO
WO-2008001091 Jan 2008 WO
WO-2008076868 Jun 2008 WO
Non-Patent Literature Citations (482)
Entry
US 7,530,950 B2, 05/2009, Brister et al. (withdrawn)
Aalders, et al., “Development of a Wearable Glucose Sensor; Studies in Healthy Volunteers and in Diabetic Patients,” The International Journal Of Artificial Organs, 1991, vol. 14, No. 2, pp. 102-108.
Abe, et al., “Characterization of Glucose Microsensors for Intracellular Measurements,” Analytical Chemistry, 1992, vol. 64, No. 18, pp. 2160-2163.
Abel, et al., “Biosensors For in Vivo Glucose Measurements: Can We Cross the Experimental Stage,” Biosensors & Bioelectronics, 2002, vol. 17, pp. 1059-1070.
Abel, et al., “Experience With An Implantable Glucose Sensor as a Prerequisite of an Artificial Beta Cell,” Biomed. Biochim. Actan, 1984, vol. 43, No. 5, pp. 577-584.
Adilman, et al., “Videogames: Knowing The Score, Creative Computing,” Dec. 1983, Dialog: File 148; IAC Trade & Industry Database, vol. 9, p. 224(5) (9 pages).
Alcock S.J., et al., “Continuous Analyte Monitoring To Aid Clinical Practice,” IEEE Engineering in Medicine & Biology, 1994, vol. 13, pp. 319-325.
Amer M.M.B., “An Accurate Amperometric Glucose Sensor Based Glucometer with Eliminated Cross-Sensitivity,” Journal of Medical Engineering & Technology, vol. 26 (5), Sep./Oct. 2002, pp. 208-213.
American Diabetes Association., “Position Statement: Diagnosis and Classification of Diabetes Mellitus,” Diabetes Care, vol. 30, Supplement 01, Jan. 2007, pp. S42-S47.
American Diabetes Association., “Position Statement: Standards of Medical Care in Diabetes,” Diabetes Care, vol. 30, Supplement 01, Jan. 2007, pp. S4-S41.
American Diabetes Association., “Summary of Revisions for the 2007 Clinical Practice Recommendations,” Diabetes Care, vol. 30, Supplement 01, Jan. 2007, pp. S3.
Amin R., et al., “Hypoglycemia Prevalence in Prepubertal Children With Type 1 Diabetes on Standard Insulin Regimen: Use of Continuous Glucose Monitoring System,” Diabetes Care, 2003, vol. 26, No. 3, pp. 662-667.
Armour J.C., et al., “Application of Chronic Intravascular Blood Glucose Sensor in Dogs,” Diabetes, Dec. 1990, vol. 39, pp. 1519-1526.
Asberg P., et al., “Hydrogels of a Conducting Conjugated Polymer as 3-D Enzyme Electrode,” Biosensors Bioelectronics, 2003, vol. 19, pp. 199-207.
Assolant-Vinet C.H., et al., “New Immobilized Enzyme Membranes for Tailor-Made Biosensors,” Analytical Letters, 1986, vol. 19(7&8), pp. 875-885.
Atanasov P., et al., “Biosensor for Continuous Glucose Monitoring,” Biotechnology and Bioengineering, John Wiley & sons Inc, 1994, vol. 43, pp. 262-266.
Atanasov P., et al., “Implantation of a Refillable Glucose Monitoring-Telemetry Device,” Biosensors and Bioelectronics, vol. 12 (7), 1997, pp. 669-680.
Aussedat B., et al., “A User-Friendly Method For Calibrating a Subcutaneous Glucose Sensor-Based Hypoglycaemic Alarm,” Elsevier Science Limited, Biosensors & Bioelectronic, 1997, vol. 12, No. 11, pp. 1061-1071.
Aussedat B., et al., “Interstitial Glucose Concentration and Glycemia: Implications for Continuous Subcutaneous Glucose Monitoring,” American Journal of Physiology—Endocrinology and Metabolism, vol. 278 (4), Apr. 1, 2000, pp. E716-E728.
Bailey T.S., et al., “Reduction in Hemoglobin A1C with Real-Time Continuous Glucose Monitoring: Results from a 12-Week Observational Study,” Diabetes Technology & Therapeutics, vol. 9 (3), 2007, pp. 203-210.
Baker D.A., et al., “Dynamic Concentration Challenges for Biosensor Characterization,” Biosensors & Bioelectronics, vol. 8, 1993, pp. 433-441.
Baker D.A., et al., “Dynamic Delay and Maximal Dynamic Error in Continuous Biosensors,” Analytical Chemistry, vol. 68 (8), Apr. 15, 1996, pp. 1292-1297.
Bard A.J., et al., “Electrochemical Methods,” Fundamentals and Applications, John Wiley & Sons, New York, 1980, pp. 173-175.
Bardeletti G., et al., “A Reliable L-Lactate Electrode with a New Membrane for Enzyme Immobilization for Amperometric Assay of Lactate,” Analytica Chemica Acta, vol. 187, 1986, pp. 47-54.
Beach R.D., et al., “Subminiature Implantable Potentiostat and Modified Commercial Telemetry Device for Remote Glucose Monitoring,” IEEE Transactions on Instrumentation and Measurement, vol. 48 (6), Dec. 1999, pp. 1239-1245.
Bellucci F., et al., “Electrochemical Behaviour of Graphite-Epoxy Composite Materials (GECM) in Aqueous Salt Solutions,” Journal of Applied Electrochemistry, vol. 16 (1), Jan. 1986, pp. 15-22.
Berger M., et al., “Computer Programs to Assist the Physician in the Analysis of Self-Monitored Blood Glucose Data,” Proceedings of the Annual Symposium on Computer Applications in Medical Care, 1988, pp. 52-57.
Bertrand C., et al., “Multipurpose Electrode with Different Enzyme Systems Bound to Collagen Films,” Analytica Chemica Acta, 1981, vol. 126, pp. 23-34.
Bessman S.P., et al., “Progress toward a Glucose Sensor for the Artificial Pancreas,” Proceedings of a Workshop on lon-Selective Microelectrodes, Jun. 4-5, 1973, Boston University, 1973, pp. 189-197.
Biermann E., et al., “How Would Patients Behave if they were Continually Informed of their Blood Glucose Levels? A Simulation Study Using a “Virtual” Patient,” Diabetes Technology & Therapeutics, vol. 10 (3), 2008, pp. 178-187.
Bindra D.S., et al., “Design and in Vitro Studies of a Needle-Type Glucose Sensor for Subcutaneous Monitoring,” Analytical Chemistry, vol. 63, Sep. 1, 1991, pp. 1692-1696.
Bindra D.S., et al., “Pulsed Amperometric Detection of Glucose in Biological Fluids at a Surface-Modified Gold Electrode,” Analytical Chemistry, vol. 61 (22), Nov. 15, 1989, pp. 2566-2570.
Bisenberger M., et al., “A Triple-Step Potential Waveform at Enzyme Multisensors with Thick-Film Gold Electrodes for Detection of Glucose and Sucrose,” Sensors and Actuators B, vol. 28, 1995, pp. 181-189.
Bland J.M., et al., “A Note on the Use of the Intraclass Correlation Coefficient in the Evaluation of Agreement between Two Methods of Measurement,” Computers in Biology and Medicine, vol. 20 (5), 1990, pp. 337-340.
Bland J.M., et al., “Statistical Methods for Assessing Agreement Between Two Methods of Clinical Measurement,” The Lancet, Feb. 8, 1986, pp. 307-310.
Bobbioni-Harsch E., et al., “Lifespan of Subcutaneous Glucose Sensors and their Performances during Dynamic Glycaemia Changes in Rats,” J. Biomed. Eng., vol. 15, 1993, pp. 457-463.
Bode B.W., “Clinical Utility of the Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S35-S41.
Bode B.W., et al., “Continuous Glucose Monitoring Used to Adjust Diabetes Therapy Improves Glycosylated Hemoglobin: A Pilot Study,” Diabetes Research and Clinical Practice, vol. 46, 1999, pp. 183-190.
Bode B.W., et al., “Using the Continuous Glucose Monitoring System to Improve the Management of Type 1 Diabetes,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S43-S48.
Boedeker Plastics Inc, “Polyethylene Specifications,” Polyethylene Data Sheet, Retrieved from http://www.boedeker.com/polye.sub.--p.htm on Aug. 19, 2009, 4 pages.
Boland E., et al., “Limitations of Conventional Methods of Self-Monitoring of Blood Glucose,” Diabetes Care, vol. 24 (11), Nov. 2001, pp. 1858-1862.
Bolinder J., et al., “Self-Monitoring of Blood Glucose in Type I Diabetic Patients: Comparison with Continuous Microdialysis Measurements of Glucose in Subcutaneous Adipose Tissue during Ordinary Life Conditions,” Diabetes Care, vol. 20 (1), Jan. 1997, pp. 64-70.
Bolinder J., et al., “Microdialysis Measurement of the Absolute Glucose Concentration in Subcutaneous Adipose Tissue Allowing Glucose Monitoring in Diabetic Patients,” Rapid Communication, Diabetologia, vol. 35, 1992, pp. 1177-1180.
Bott A.W., “A Comparison of Cyclic Voltammetry and Cyclic Staircase Voltammetry,” Current Separations, vol. 16 (1), 1997, pp. 23-26.
Bott A.W., “Electrochemical Methods for the Determination of Glucose,” Current Separations, vol. 17 (1), 1998, pp. 25-31.
Bowman L., et al., “The Packaging of Implantable Integrated Sensors,” IEEE Transactions in Biomedical Engineering, vol. BME-33 (2), Feb. 1986, pp. 248-255.
Brauker, et al., “Sustained Expression of High Levels of Human Factor IX from Human Cells Implanted within an Immunoisolation Device into Athymic Rodents,” Human Gene Therapy, Apr. 10, 1998, vol. 9, pp. 879-888.
Brauker J., et al., “Local Inflammatory Response Around Diffusion Chambers Containing Xenografts,” Transplantation, vol. 61 (12), Jun. 27, 1996, pp. 1671-1677.
Brauker J H., et al., “Neovascularization of Synthetic Membranes Directed by Membrane Microarchitecture,” Journal of Biomedical Material Research, 1995, vol. 29, pp. 1517-1524.
Brauker J., “Unraveling Mysteries at the Biointerface: Molecular Mediator of Inhibition of Blood Vessel Formation in the Foreign Body Capsule Revealed,” SurFACTS in Biomaterials, vol. 6 (3), 2001, pp. 1,5.
Braunwald E., “Biomarkers in Heart Failure,” Medical Progress, The New England Journal of Medicine, vol. 358, May 15, 2008, pp. 2148-2159.
Bremer T., et al., “Is Blood Glucose Predictable from Previous Values? A Solicitation for Data,” Perspectives in Diabetes, vol. 48, Mar. 1999, pp. 445-451.
Bremer T.M., et al., “Benchmark Data from the Literature for Evaluation of New Glucose Sensing Technologies,” Diabetes Technology & Therapeutics, vol. 3 (3), 2001, pp. 409-418.
Brooks S.L., et al., “Development of an On-line Glucose Sensor for Fermentation Monitoring,” Biosensors, vol. 3, 1987/1988, pp. 45-56.
Bruckel J., et al., “In Vivo Measurement of Subcutaneous Glucose Concentrations with an Enzymatic Glucose Sensor and a Wick Method,” Klin Wochenschr, vol. 67, 1989, pp. 491-495.
Brunner G.A., et al., “Validation of Home Blood Glucose Meters with Respect to Clinical and Analytical Approaches,” Diabetes Care, vol. 21, No. 4, Apr. 1998, pp. 585-590.
Brunstein E., et al., “Preparation and Validation of Implantable Electrodes for the Measurement of Oxygen and Glucose,” Biomed Biochim. Acta, vol. 48 (11/12), 1989, pp. 911-917.
Cai Q., et al., “A Wireless, Remote Query Glucose Biosensor Based on a pH-Sensitive Polymer,” Analytical Chemistry, vol. 76 (14), Jul. 15, 2004, pp. 4038-4043.
Cameron T., et al., “Micromodular Implants to Provide Electrical Stimulation of Paralyzed Muscles and Limbs,” IEEE Transactions on Biomedical Engineering, vol. 44 (9), Sep. 1997, pp. 781-790.
Campanella L., et al., “Biosensor for Direct Determination of Glucose and Lactate in Undiluted Biological Fluids,” Biosensors & Bioelectronics, vol. 8, 1993, pp. 307-314.
Candas B., et al., “An Adaptive Plasma Glucose Controller Based on a Nonlinear Insulin/Glucose Model,” IEEE Transactions on Biomedical Engineering, vol. 41 (2), Feb. 1994, pp. 116-124.
Cass A.E.G., et al., “Ferrocene-Mediated Enzyme Electrodes for Amperometric Determination of Glucose,” Analytical Chemistry, vol. 56 (4), Apr. 1984, pp. 667-671.
Cassidy J.F., et al., “Novel Electrochemical Device for the Detection of Cholesterol or Glucose,” Analyst, vol. 118, Apr. 1993, pp. 415-418.
Chase H.P., et al., “Continuous Subcutaneous Glucose Monitoring in Children with Type 1 Diabetes,” Pediatrics, vol. 107 (2), Feb. 2001, pp. 222-226.
Chase J.G., et al., “Targeted Glycemic Reduction in Critical Care Using Closed-Loop Control,” Diabetes Technology & Therapeutics, vol. 7 (2), 2005, pp. 274-282.
Chen C., et al., “A Noninterference Polypyrrole Glucose Biosensor,” Biosensors and Bioelectronics, vol. 22, 2006, pp. 639-643.
Chen T., et al., “Defining the Period of Recovery of the Glucose Concentration after its Local Perturbation by the Implantation of a Miniature Sensor,” Clinical Chemistry and Laboratory Medicine, vol. 40 (8), 2002, pp. 786-789.
Chia C.W., et al., “Glucose Sensors: Toward Closed Loop Insulin Delivery,” Endocrinology and Metabolism Clinics of North America, vol. 33, 2004, pp. 175-195.
Choleau C., et al., “Calibration of a Subcutaneous Amperometric Glucose Sensor Implanted for 7 Days in Diabetic Patients Part 2. Superiority of the One-point Calibration Method,” Biosensors and Bioelectronics, vol. 17 (8), 2002, pp. 647-654.
Choleau C., et al., “Calibration of a Subcutaneous Amperometric Glucose Sensor Part 1. Effect of Measurement Uncertainties on the Determination of Sensor Sensitivity and Background Current,” Biosensors and Bioelectronics, vol. 17, 2002, pp. 641-646.
Ciba Specialty Chemicals, “Ciba® Irgacure® 2959,” Coating Effects Segment, Photoinitiator Product Description, Basel Switzerland, Apr. 2, 1998, 3 pages.
Claremont D.J., et al., “Potentially-Implantable, Ferrocene-Mediated Glucose Sensor,” Journal of Biomedical Engineering, vol. 8, Jul. 1986, pp. 272-274.
Claremont D.J., et al., “Subcutaneous Implantation of a Ferrocene-Mediated Glucose Sensor in Pigs,” Diabetologia, vol. 29, 1986, pp. 817-821.
Clark L.C., et al., “Configurational Cyclic Voltammetry: Increasing the Specificity and Reliability of Implanted Electrodes,” IEEE/Ninth Annual Conference of the Engineering in Medicine and Biology Society, 1987, pp. 0782-0783.
Clark L.C., et al., “Long-Term Stability of Electroenzymatic Glucose Sensors Implanted in Mice,” vol. XXXIV, Transactions—American Society for Artificial Internal Organs, 1988, vol. 34, pp. 259-265.
Clark L.C., et al., “One-Minute Electrochemical Enzymic Assay for Cholesterol in Biological Materials,” Clinical Chemistry, vol. 27 (12), 1981, pp. 1978-1982.
Clarke W.L., et al., “Evaluating Clinical Accuracy of Systems for Self Monitoring of Blood Glucose,” Technical Articles, Diabetes Care, vol. 10 (5), Sep.-Oct. 1987, pp. 622-628.
Colangelo V.J., et al., “Corrosion Rate Measurements in Vivo,” Journal of Biomedical Materials Research, vol. 1, 1967, pp. 405-414.
Colowick S.P., et al., “Methods in Enzymology,” vol. XLIV, Immobilized Enzymes, Edited by Mosbach K, New York Academic Press, 1976, 11 pages.
Coulet P.R., et al., “Enzymes Immobilized on Collagen Membranes: A Tool for Fundamental Research and Enzyme Engineering,” Journal of Chromatography, vol. 215, 1981, pp. 65-72.
Coulet P.R., “Polymeric Membranes and Coupled Enzymes in the Design of Biosensors,” Journal of Membrane Science, 1992, vol. 68, pp. 217-228.
Cox D.J., et al., “Accuracy of Perceiving Blood Glucose in IDDM,” Diabetes Care, vol. 8 (6), Nov.-Dec. 1985, pp. 529-536.
Csoregi E., et al., “Amperometric Microbiosensors for Detection of Hydrogen Peroxide and Glucose Based on Peroxidase-Modified Carbon Fibers,” Electroanalysis, vol. 6, 1994, pp. 925-933.
Csoregi E., et al., “Design, Characterization and One-Point in Vivo Calibration of a Subcutaneously Implanted Glucose Electrode,” American Chemical Society, Analytical Chemistry, vol. 66 (19), Oct. 1, 1994, pp. 3131-3138.
Currie J.F., et al., “Novel Non-Intrusive Trans-Dermal Remote Wireless Micro-Fluidic Monitoring System Applied to Continuous Glucose and Lactate Assays for Casualty Care and Combat Readiness Assessment,” RTO HFM Symposium, RTO-MP-HFM-109, Aug. 16-18, 2004, pp. ‘24-1’-‘24-18’.
Dai W.S., et al., “Hydrogel Membranes with Mesh Size Asymmetry based on the Gradient Crosslinking of Poly(Vinyl Alcohol),” Journal of Membrane Science, 1999, vol. 156, pp. 67-79.
Danielsson B., et al., “Enzyme Thermistors,” Methods in Enzymology, vol. 137, 1988, pp. 181-197.
D'Arrigo G., et al., “Porous-Si Based Bio Reactors for Glucose Monitoring and Drugs Production,” Proceedings of SPIE, 2003, vol. 4982, pp. 178-184.
Dassau E., et al., “In Silico Evaluation Platform for Artificial Pancreatic β-Cell Development—A Dynamic Simulator for Closed-Loop Control with Hardware-in-the-loop,” Diabetes Technology & Therapeutics, vol. 11 (3), 2009, pp. 1-8.
Davies M.L., et al., “Polymer Membranes in Clinical Sensor Applications,” An overview of membrane function, Biomaterials, vol. 13 (14), 1992, pp. 971-978.
Davis G., et al., “Bioelectrochemical Fuel Cell and Sensor Based on a Quinoprotein, Alcohol Dehydrogenase,” Enzyme and Microbial Technology, vol. 5 (5), Sep. 1983, pp. 383-388.
De Vos P., et al., “Considerations for Successful Transplantation of Encapsulated Pancreatic Islets,” Diabetologia, vol. 45, 2002, pp. 159-173.
Deutsch T., et al., “Time Series Analysis and Control of Blood Glucose Levels in Diabetic Patients,” Computer Methods and Programs in Biomedicine, Elsevier Scientific Publishers, vol. 41, 1994, pp. 167-182.
Dixon B.M., et al., “Characterization in Vitro and in Vivo of the Oxygen Dependence of an Enzyme/Polymer Biosensor for Monitoring Brain Glucose,” Journal of Neuroscience Methods, vol. 119, 2002, pp. 135-142.
DuPont, “Dimension® AR Clinical Chemistry System,” The Chemistry Analyzer that Makes the most of your Time, Money and Effort, Dade International, Chemistry Systems, Newark, 1998, 18 pages.
Durliat H., et al., “Spectrophotometric and Electrochemical Determinations of L( +)-Lactate in Blood by Use of Lactate Dehydrogenase from Yeast,” Clinical Chemistry, vol. 22 (11), 1976, pp. 1802-1805.
Edwards Lifesciences, “Accuracy for You and Your Patients,” Marketing materials, 2002, 4 pages.
El Degheidy M.M., et al., “Optimization of an Implantable Coated Wire Glucose Sensor,” Journal of Biomedical Engineering, vol. 8, Apr. 1986, pp. 121-129.
ELCO Diagnostics Company, “Direct 30/30® Blood Glucose Sensor,” Markwell Medical Catalog, 1990, 1 page.
El-Khatib F.H., et al., “Adaptive Closed-Loop Control Provides Blood-Glucose Regulation Using Dual Subcutaneous Insulin and Glucagon Infusion in Diabetic Swine,” Journal of Diabetes Science and Technology, Diabetes Technology Society, vol. 1 (2), 2007, pp. 181-192.
El-Sa'ad L., et al., “Moisture Absorption by Epoxy Resins: The Reverse Thermal Effect,” Journal of Materials Science, vol. 25, 1990, pp. 3577-3582.
Ernst H., et al., “Reliable Glucose Monitoring Through the Use of Microsystem Technology,” Analytical Bioanalytical Chemistry, vol. 373, 2002, pp. 758-761.
Fabietti P.G., et al., “Clinical Validation of a New Control-Oriented Model of Insulin and Glucose Dynamics in Subjects with Type 1 Diabetes,” Diabetes Technology & Therapeutics, vol. 9 (4), 2007, pp. 327-338.
Fahy B.G., et al., “An Analysis: Hyperglycemic Intensive Care Patients Need Continuous Glucose Monitoring-Easier Said Than Done,” Journal of Diabetes Science and Technology, Diabetes Technology Society, vol. 2 (2), Mar. 2008, pp. 201-204.
Fare T.L., et al., “Functional Characterization of a Conducting Polymer-Based Immunoassay System,” Biosensors & Bioelectronics, vol. 13 (3-4), 1998, pp. 459-470.
Feldman B., et al., “A Continuous Glucose Sensor Based on Wired EnzymeTM Technology—Results from a 3-Day Trial in Patients with Type 1 Diabetes,” Diabetes Technology & Therapeutics, vol. 5 (5), 2003, pp. 769-779.
Fischer U., et al., “Assessment of Subcutaneous Glucose Concentration: Validation of the Wick Technique as a Reference for Implanted Electrochemical Sensors in Normal and Diabetic Dogs,” Diabetologia, vol. 30, 1987, pp. 940-945.
Fischer U., et al., “Hypoglycaemia-Warning by Means of Subcutaneous Electrochemical Glucose Sensors: An Animal Study,” Horm. Metab. Res, vol. 27, 1995, p. 53. (Abstract Only).
Fischer U., et al., “Oxygen Tension at the Subcutaneous Implantation Site of Glucose Sensors,” Biomed. Biochim. Acta, vol. 48 (11/12), 1989, pp. 965-971.
Freedman D., et al., “Statistics,” Second Edition, W.W. Norton & Company, New York & London, 1991, p. 74 (3 pages).
Freiberger P., “Video Game Takes on Diabetes Superhero ‘Captain Novolin’ Offers Treatment Tips,” Fourth Edition, Jun. 26, 1992, Business Section, 2 pages.
Frohnauer M.K., et al., “Graphical Human Insulin Time-Activity Profiles Using Standardized Definitions,” Diabetes Technology & Therapeutics, vol. 3 (3), 2001, pp. 419-429.
Frost M.C., et al., “Implantable Chemical Sensors for Real-Time Clinical Monitoring: Progress and Challenges,” Current Opinion in Chemical Biology, Analytical Techniques, vol. 6, 2002, pp. 633-641.
Gabby R.A., et al., “Optical Coherence Tomography-Based Continuous Noninvasive Glucose Monitoring in Patients with Diabetes,” Diabetes Technology & Therapeutics, vol. 10, Nov. 3, 2008, pp. 188-193.
Ganesan N., et al., “Gold Layer-Based Dual Crosslinking Procedure of Glucose Oxidase with Ferrocene Monocarboxylic Acid Provides a Stable Biosensor,” Analytical Biochemistry, Notes & Tips, vol. 343, 2005, pp. 188-191.
Ganesh A., et al., “Evaluation of the Via® Blood Chemistry Monitor for Glucose in Healthy and Diabetic Volunteers,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 182-193.
Garg S.K., et al., “Correlation of Fingerstick Blood Glucose Measurements With GlucoWatch Biographer Glucose Results in Young Subjects With Type 1 Diabetes,” Emerging Treatments and Technologies, Diabetes Care, vol. 22 (10), Oct. 1999, pp. 1708-1714.
Garg S.K., et al., “Improved Glucose Excursions Using an Implantable Real-Time Continuous Glucose Sensor in Adults With Type 1 Diabetes,” Emerging Treatments and Technologies, Diabetes Care, vol. 27 (3), 2004, pp. 734-738.
Garg S.K., “New Insulin Analogues,” Diabetes Technology & Therapeutics, vol. 7 (5), 2005, pp. 813-817.
Geller R.I., et al., “Use of an Immunoisolation Device for Cell Transplantation and Tumor Immunotherapy,” Annals of the New York Academy of Science, 1997, vol. 831, pp. 438-451.
Gerritsen M., et al., “Influence of Inflammatory Cells and Serum on the Performance of Implantable Glucose Sensors,” Journal of Biomedical Material Research, 2001, vol. 54, pp. 69-75.
Gerritsen M., et al., “Performance of Subcutaneously Implanted Glucose Sensors for Continuous Monitoring,” The Netherlands Journal of Medicine, vol. 54, 1999, pp. 167-179.
Gerritsen M., et al., “Problems Associated with Subcutaneously Implanted Glucose Sensors,” Diabetes Care, vol. 23 (2), Feb. 2000, pp. 143-145.
Gilligan B.J., et al., “Evaluation of a Subcutaneous Glucose Sensor Out to 3 Months in a Dog Model” Diabetes Care, vol. 17 (8), Aug. 1994, pp. 882-887.
Gilligan B.J., et al., “Feasibility of Continuous Long-Term Glucose Monitoring from a Subcutaneous Glucose Sensor in Humans,” Diabetes Technology & Therapeutics, vol. 6 (3), 2004, pp. 378-386.
Godsland I.F., et al., “Maximizing the Success Rate of Minimal Model Insulin Sensitivity Measurement in Humans: The Importance of Basal Glucose Levels,” The Biochemical Society and the Medical Research Society, Clinical Science, vol. 101, 2001, pp. 1-9.
Gouda M.D., et al., “Thermal Inactivation of Glucose Oxidase,” The Journal of Biological Chemistry, vol. 278 (27), Issue of Jul. 4, 2003, pp. 24324-24333.
Gough D.A., et al., “Frequency Characterization of Blood Glucose Dynamics,” Annals of Biomedical Engineering, vol. 31, 2003, pp. 91-97.
Gough D.A., et al., “Immobilized Glucose Oxidase in Implantable Glucose Sensor Technology,” Diabetes Technology & Therapeutics, vol. 2 (3), 2000, pp. 377-380.
Gough D.A., “The implantable Glucose Sensor: An Example of Bioengineering Design,” Introduction to Bioengineering, 2001, Chapter 3, pp. 57-66.
Gregg B A., et al., “Cross-Linked Redox Gels Containing Glucose Oxidase for Amperometric Biosensor Applications,” Anal Chem, 1990, vol. 62, pp. 258-263.
Gross, et al., “Diabetes Technology & Therapeutics,” Letters to the Editor, Diabetes Technology & Therapeutics, vol. 3 (1), 2001, pp. 129-131.
Gross T.M., et al., “Efficacy and Reliability of the Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S19-S26.
Gross T.M., et al., “Performance Evaluation Of The Minimed® Continuous Glucose Monitoring System During Patient Home Use,” Diabetes Technology & Therapeutics, vol. 2(1), 2000, pp. 49-56.
Guerci B., et al., “Clinical Performance of CGMS in Type 1 Diabetic Patients Treated by Continuous Subcutaneous Insulin Infusion Using Insulin Analogs,” Diabetes Care, vol. 26, 2003, pp. 582-589.
Hagvik J., “Glucose Measurement: Time for a Gold Standard,” Journal of Diabetes Science and Technology, vol. 1 (2), Mar. 2007, pp. 169-172.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part 1. An Adsorption-controlled Mechanism,” Electrochimica Acta, vol. 43, Nos. 5/6, 1998, pp. 579-588.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part II: Effect of potential,” Electrochimica Acta, vol. 43 (14-15), 1998, pp. 2015-2024.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part III: Effect of Temperature,” Electrochimica Acta, vol. 44, 1999, pp. 2455-2462.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part IV: Phosphate Buffer Dependence,” Electrochimica Acta, vol. 44, 1999, pp. 4573-4582.
Hall S.B., et al., “Electrochemical Oxidation of Hydrogen Peroxide at Platinum Electrodes. Part V: Inhibition by Chloride,” Electrochimica Acta, vol. 45, 2000, pp. 3573-3579.
Hamilton, “Complete Guide to Selecting the Right Hamilton Gastight, Microliter, and Specialty Syringe for your Application,” Syringe Selection, www.hamiltoncompany.com 2006, 20 pages.
Harrison, et al., “Characterization of Perfluorosulfonic Acid Polymer Coated Enzyme Electrodes and a Miniaturized Integrated Potentiostat for Glucose Analysis in Whole Blood,” Analytical Chemistry, 1988, vol. 60, pp. 2002-2007.
Hashiguchi Y., et al., “Development of a Miniaturized Glucose Monitoring System by Combining a Needle-Type Glucose Sensor with Microdialysis Sampling Method: Long-term subcutaneous tissue glucose monitoring in ambulatory diabetic patients,” Diabetes Care, vol. 17, No. 5, May 1994, pp. 387-396.
Heinemann L., et al., “Review: Measurement of Insulin Absorption and Insulin Action,” Diabetes Technology & Therapeutics, vol. 6 (5), 2004, pp. 698-718.
Heinemann L., “Measurement Quality of Blood Glucose Meters: Is There a Need for an Institution with an Unbiased View?,” Journal of Diabetes Science and Technology, vol. 1 (2), Mar. 2007, pp. 178-180.
Heinemann L., “Review: Variability of Insulin Absorption and Insulin Action,” Diabetes Technology & Therapeutics, vol. 4 (5), 2002, pp. 673-682.
Heise T., et al., “Hypoglycemia warning signal and glucose sensors: Requirements and concepts,” Diabetes Technology & Therapeutics, vol. 5, No. 4, 2003, pp. 563-571.
Heller A., “Electrical Connection of Enzyme Redox Centers to Electrodes,” J. Phys. Chem., vol. 96, 1992, pp. 3579-3587.
Heller A., “Electrical Wiring of Redox Enzymes,” Ace. Chem. Res., vol. 23, 1990, pp. 128-134.
Heller A., “Implanted Electrochemical Glucose Sensors for the Management of Diabetes,” Annu. Rev., Biomed Eng., vol. 1, 1999, pp. 153-175.
Heller A., “Plugging Metal Connectors into Enzymes,” Nature Biotechnology, vol. 21, No. 6, Jun. 2003, pp. 631-632.
Hicks J.M., “In Situ Monitoring,” Clinical Chemistry, vol. 31 (12), 1985, pp. 1931-1935.
Hitchman M.L., “Measurement of Dissolved Oxygen,” Edited by Elving P.J et al., Chemical Analysis, New York, John Wiley & Sons, vol. 49, Chapter 3, 1978, pp. 34-49 and 59-123.
Hoel P.G., “Elementary Statistics,” Fourth Edition, John Wiley & Sons, Inc., 1976, pp. 113-114.
Houghton Mifflin Company, “American Heritage Dictionary,” 4th Edition, 2000, pp. 82.
Houghton Mifflin Company, “Xenogenic, the American Heritage Stedman's Medical Dictionary,” 2002, Answers.Com, retrieved from http://www.answers.com/topic/xenogenic, on Nov. 7, 2006, 2 Pages.
Hovorka R., et al., “Closing the Loop: The Adicol Experience,” Diabetes Technology & Therapeutics, vol. 6 (3), 2004, pp. 307-318.
Hrapovic S., et al., “Picoamperometric Detection of Glucose at Ultrasmall Platinum-Based Biosensors Preparation and Characterization,” Anal. Chem, vol. 75, 2003, pp. 3308-3315.
Hu Y., et al., “A Needle-Type Enzyme-Based Lactate Sensor for In Vivo Monitoring,” Analytica Chimica Acta, vol. 281, 1993, pp. 503-511.
Huang C., et al., “Electrochemical Generation of Oxygen. 1: The Effects of Anions and Cations on Hydrogen Chemisorption and Anodic Oxide Film Formation on Platinum Electrode. 2: The Effects of Anions and Cations on Oxygen Generation on Platinum Electrode,” U.S. Department of Commence/NTIS, 1975, 126 pages.
Huang Q., et al., “A 0.5mW Passive Telemetry IC for Biomedical Applications,” Proceedings of the 23rd European Solid-State Circuits Conference (ESSCIRC '97), Southampton, UK, Sep. 16-18, 1997, pp. 172-175.
Hunsley B., et al., “Whole Blood Glucose Standard Is Key to Accurate Insulin Dosages,” Journal of Diabetes Science and Technology, vol. 1 (2), Mar. 2007, pp. 173-177.
Hunter I., et al., “Minimally Invasive Glucose Sensor and Insulin Delivery System,” MIT Home Automation and Healthcare Consortium, Mar. 31, 2000, Progress Report No. 25, 17 pages.
International Preliminary Report on Patentability for Application No. PCT/US2005/006301, mailed Aug. 30, 2006, 4 pages.
International Preliminary Report on Patentability for Application No. PCT/US2007/080848 mailed Apr. 13, 2010, 6 page.
International Preliminary Report on Patentability for Application No. PCT/US2008/058158, mailed Sep. 29, 2009, 9 pages.
International Preliminary Report on Patentability for Application No. PCT/US2008/065978 mailed Jun. 19, 2008, 14 pages.
International Search Report and Written Opinion for Application No. PCT/US2005/006301, mailed Jun. 22, 2005, 4 pages.
International Search Report and Written Opinion for Application No. PCT/US2007/080848 mailed Aug. 28, 2008, 6 pages.
International Search Report and Written Opinion for Application No. PCT/US2008/058158, mailed Aug. 8, 2008, 10 pages.
International Search Report and Written opinion for Application No. PCT/US2008/065978 mailed Oct. 2, 2008, 14 pages.
Ishikawa M., et al., “Initial Evaluation of A 290-Mm Diameter Subcutaneous Glucose Sensor: Glucose Monitoring With A Biocompatible, Flexible-Wire, Enzyme-Based Amperometric Microsensor in Diabetic and Nondiabetic Humans,” Journal of Diabetes and Its Complications, vol. 12, 1998, pp. 295-301.
Jablecki M., et al., “Simulations of the Frequency Response of Implantable Glucose Sensors,” Analytical Chemistry, vol. 72, 2000, 1853-1859.
Jaffari S.A., et al., “Recent Advances in Amperometric Glucose Biosensors for In Vivo Monitoring,” Physiological Measurement, 1995, vol. 16, pp. 1-15.
Jaremko J., et al., “Advances Toward the Implantable Artificial Pancreas for Treatment of Diabetes,” Diabetes Care, vol. 21 (3), Mar. 1998, pp. 444-450.
Jensen M.B., et al., “Fast Wave Forms for Pulsed Electrochemical Detection of Glucose by Incorporation of Reductive Desorption of Oxidation Products,” Analytical Chemistry, vol. 69 (9), May 1997, pp. 1776-1781.
Jeong R.A., et al., “In Vivo Calibration of the Subcutaneous Amperometric Glucose Sensors Using a Non-Enzyme Electrode,” Biosensors and Bioelectronics, Elsevier, vol. 19, 2003, pp. 313-319.
Jeutter D.C., “A Transcutaneous Implanted Battery Recharging and Biotelemeter Power Switching System,” IEEE Transactions on Biomedical Engineering, vol. BME-29 (5), May 1982, pp. 314-321.
Jeutter D.C., et al., “Design of a Radio-Linked Implantable Cochlear Prosthesis Using Surface Acoustic Wave Devices,” IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 40 (5), Sep. 1993, pp. 469-477.
Jobst G., et al., “Thin-Film Microbiosensors for Glucose-Lactate Monitoring,” Anal Chem, Sep. 15, 1996, vol. 68(18), pp. 3173-3179.
Johnson K.W., et al., “In Vivo Evaluation of an Electroenzymatic Glucose Sensor Implanted in Subcutaneous Tissue,” Biosensors and Bioelectronics, 1992, vol. 7, pp. 709-714.
Johnson K.W., “Reproducible Electrodeposition of Biomolecules for the Fabrication of Miniature Electroenzymatic Biosensors,” Sensors and Actuators B, vol. 5, 1991, pp. 85-89.
Jones S.M., et al., “Optimal Insulin Pump Dosing and Postprandial Glycemia Following a Pizza Meal Using the Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 7 (2), Apr. 2005, pp. 233-240.
Joung G.B., et al., “An Energy Transmission System for an Artificial Heart Using Leakage Inductance Compensation of Transcutaneous Transformer,” IEEE Transactions on Power Electronics, vol. 13 (6), Nov. 1998, pp. 1013-1022.
Jovanovic L.M.D., “The Role of Continuous Glucose Monitoring in Gestational Diabetes Mellitus,” Diabetes Technology and Therapeutics, vol. 2 (1), 2000, pp. S67-S71.
Kacaniklic V., et al., “Amperometric Biosensors for Detection of L- and D-Amino Acids Based on Coimmoblized Peroxidase and L- and D-Amino Acid Oxidases in Carbon Paste Electrodes,” Electroanalysis, vol. 6, May-Jun. 1994, pp. 381-390.
Kamath A., et al., “Calibration of a Continuous Glucose Monitor: Effect of Glucose Rate of Change,” Eighth Annual Diabetes Technology Meeting, Nov. 13-15, 2008, pp. A88 (2 pages).
Kang S.K., et al., “In Vitro and Short-Term in Vivo Characteristics of a Kel-F Thin Film Modified Glucose Sensor,” Analytical Sciences, vol. 19, Nov. 2003, pp. 1481-1486.
Kaplan S.M., “Wiley Electrical and Electronics Engineering Dictionary,” IEEE Press, John Wiley & Sons, Inc., 2004, pp. 141, 142, 548 & 549.
Kargol M., et al., “Studies on the Structural Properties of Porous Membranes: Measurement of Linear Dimensions of Solutes,” Biophysical Chemistry, 2001, vol. 91, pp. 263-271.
Karube I., et al., “Microbiosensors for Acetylcholine and Glucose,” Biosensors & Bioelectronics, 1993, vol. 8, pp. 219-228.
Kaufman F.R., et al., “A Pilot Study of the Continuous Glucose Monitoring System,” Diabetes Care, vol. 24 (12), Dec. 2001, pp. 2030-2034.
Kaufman F.R., “Role of the Continuous Glucose Monitoring System in Pediatric Patients,” Diabetes Technology and Therapeutics, vol. 2 (1), 2000, S49-S52.
Kawagoe J.L., et al., “Enzyme-Modified Organic Conducting Salt Microelectrode,” Analytical Chemistry, vol. 63, 1991, pp. 2961-2965.
Keedy F.H., et al., “Determination of Urate in Undiluted Whole Blood by Enzyme Electrode,” Biosensors and Bioelectronics, vol. 6, 1991, pp. 491-499.
Kerner, et al., “A Potentially Implantable Enzyme Electrode for Amperometric Measurement of Glucose,” Hormone and Metabolic Research Supplement, vol. 20, 1988, pp. 8-13.
Kerner W., et al., “The Function of a Hydrogen Peroxide-Detecting Electroenzymatic Glucose Electrode is Markedly Impaired in Human Sub-Cutaneous Tissue and Plasma,” Biosensors and Bioelectronics, vol. 8, 1993, pp. 473-482.
Kerner W., “Implantable Glucose Sensors: Present Status and Future Developments,” Experimental and Clinical Endocrinol Diabetes, vol. 109 (2), 2001, pp. S341-S346.
Kiechle F.L., “The Impact of Continuous Glucose Monitoring on Hospital Point-of-Care Testing Programs,” Diabetes Technology and Therapeutics, vol. 3 (4), 2001, pp. 647-649.
Kizilel S., et al., “Review: The Bioartificial Pancreas: Progress and Challenges,” Diabetes Technology & Therapeutics, vol. 7 (6), 2005, pp. 968-985.
Klonoff D., et al., “Performance Metrics for Continuous Interstitial Glucose Monitoring; Approved Guideline,” Clinical and Laboratory Standards Institute, POCT05-A, vol. 28 (33), 2008, 72 pages.
Klonoff D.C., “Editorial: Current, Emerging, and Future Trends in Metabolic Monitoring,” Diabetes Technology & Therapeutics, vol. 4 (5), 2002, pp. 583-588.
Klueh U., et al., “Inflammation and Glucose Sensors: Use of Dexamethasone to Extend Glucose Sensor Function and Life Span in Vivo,” Journal of Diabetes Science and Technology, vol. 1 (4), Jul. 2007, pp. 496-504.
Klueh U., et al., “Use of Vascular Endothelial Cell Growth Factor Gene Transfer to Enhance Implantable Sensor Function in Vivo,” Biosensor Function and VEGF-Gene Transfer, vol. 67 (4), 2003, pp. 1072-1086.
Kondo T., et al., “A Miniature Glucose Sensor, Implantable in the Blood Stream,” Diabetes Care, vol. 5 (3), May-Jun. 1982, 218-221.
Koschinsky T., et al., “Sensors For Glucose Monitoring: Technical And Clinical Aspects,” Diabetes Metabolism Research and Reviews, vol. 17, No. 2, Jan. 1, 2001, pp. 113-123.
Koschinsky T., et al., “New Approach to Technical and Clinical Evaluation of Devices for Self-Monitoring of Blood Glucose,” Diabetes Care, vol. 11 (8), Sep. 1988, pp. 619-629.
Koschinsky T., et al., “Review: Glucose Sensors and the Alternate Site Testing-like Phenomenon: Relationship Between Rapid Blood Glucose Changes and Glucose Sensor Signals,” Diabetes Technology & Therapeutics, vol. 5 (5), 2003, pp. 829-842.
Kost J., et al., “Glucose-Sensitive Membranes Containing Glucose Oxidase: Activity, Swelling, And Permeability Studies,” Journal of Biomedical Materials Research, vol. 19, 1985, pp. 1117-1133.
Koudelka M., et al., “In Vivo Response of Microfabricated Glucose Sensors to Glycemia Changes in Normal Rats,” Biomed. Biochim. Acta, vol. 48 (11/12), Nov.-Dec. 1989, pp. 953-956.
Koudelka M., et al., “In-Vivo Behaviour of Hypodermically Implanted Microfabricated Glucose Sensors,” Biosensors and Bioelectronics, vol. 6, 1991, pp. 31-36.
Kovatchev B.P., et al., “Evaluating the Accuracy of Continuous Glucose-Monitoring Sensors: Continuous Glucose-Error Grid Analysis Illustrated by TheraSense Freestyle Navigator Data,” Diabetes Care, vol. 27 (8), Aug. 2004, pp. 1922-1928.
Kraver., et al., “A Mixed-Signal Sensor Interface Microinstrument,” Sensors and Actuators A, Physical 2001, vol. 91, pp. 266-277.
Krouwer U.S., “Setting Performance Goals and Evaluating Total Analytical Error for Diagnostic Assays,” Clinical Chemistry, vol. 48 (6), 2002, pp. 919-927.
Kruger D., et al., “Psychological Motivation and Patient Education: A Role for Continuous Glucose Monitoring,” Diabetes Technology and Therapeutics, vol. 2 (1), 2000, pp. S93-S97.
Kulys J., et al., “Carbon-Paste Biosensors Array for Long-Term Glucose Measurement,” Biosensors & Bioelectronics, vol. 9, 1994, pp. 491-500.
Kunjan K., et al., “Automated Blood Sampling and Glucose Sensing in Critical Care Settings,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 194-200.
Kunzler J., et al.,“ Hydrogels based on Hydrophilic Side Chain Siloxanes,” Poly Mat Sci and Eng, 1993, vol. 69, pp. 226-227.
Kunzler J F., et al., “Contact Lens Materials,” Chemistry & Industry, Aug. 21, 1995, pp. 651-655.
Kurnik R.T., et al., “Application of the Mixtures of Experts Algorithm for Signal Processing in a Noninvasive Glucose Monitoring System,” Sensors and Actuators B, vol. 60, 1999, pp. 19-26.
Kurtz T.W., et al., “Recommendations for Blood Pressure Measurement in Humans and Experimental Animals, Part 2: Blood Pressure Measurement In Experimental Animals: A Statement for Professionals From the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research,” Hypertension, Feb. 2005, vol. 45, pp. 299-310.
Lacourse W.R., et al., “Optimization of Waveforms for Pulsed Amperometric Detection of Carbohydrates Based on Pulsed Voltammetry,” Analytical Chemistry, vol. 65, 1993, pp. 50-52.
Ladd M.F.C., et al., “Structure Determination By X-Ray Crystallography,” 3rd Edition, Plenum Press, 1994, Ch. 1, pp. xxi-xxiv and 1-58.
Lee E., et al., “Effects of Pore Size, Void Volume and Pore Connectivity on Tissue Responses to Porous Silicone Implants,” Society for Biomaterials, 25th Annual Meeting, 1999, p. 171.
Lee S.W., et al., “Combined Insulin Pump Therapy with Real-Time Continuous Glucose Monitoring Significantly Improves Glycemic Control Compared to Multiple Daily Injection Therapy in Pump Naïve Patients with Type 1 Diabetes; Single Center Pilot Study Experience,” Journal of Diabetes Science and Technology, vol. 1 (3), May 2007, pp. 400-404.
Lehmann E.D., et al., Retrospective Validation of a Physiological Model of Glucose-Insulin Interaction in Type 1 Diabetes Mellitus. Medical Engineering & Physics, vol. 16, May 1994, pp. 193-202.
Lerner., et al., “An Implantable Electrochemical Glucose Sensor,” Ann. N. Y. Acad. Sci., vol. 428, May 1984, pp. 263-278.
Lewandowski J.J., et al., “Evaluation of a Miniature Blood Glucose Sensor,” Transactions—American Society for Artificial Internal Organs, vol. 34, 1988, pp. 255-258.
Leypoldt J.K., et al., “Model of a Two-Substrate Enzyme Electrode for Glucose,” Analytical Chemistry, vol. 56, 1984, pp. 2896-2904.
Linke B., et al., “Amperometric Biosensor for In Vivo Glucose Sensing Based on Glucose Oxidase Immobilized In A Redox Hydrogel,” Biosensors and Bioelectronics, vol. 9, 1994, pp. 151-158.
Loffler P., et al., “Separation and Determination of Traces of Ammonia in Air by Means of Chromatomembrane Cells,” Fresenius Journal of Analytical Chemistry, 1995, vol. 352, pp. 613-614.
Lohn A., et al., “A Knowledge-Based System for Real-Time Validation of Calibrations and Measurements,” Chemometrics and Intelligent Laboratory Systems, vol. 46, 1999, pp. 57-66.
Lowe C.R., “Biosensors,” Trends in Biotechnology, vol. 2 (3), 1984, pp. 59-65.
Luong J.H.T., et al., “Solubilization of Multiwall Carbon Nanotubes by 3-Aminopropyltriethoxysilane towards the Fabrication of Electrochemical Biosensors with Promoted Electron Transfer,” Electroanalysis, vol. 16 (1-2), 2004, pp. 132-139.
Lyandres O., et al. “Progress toward an In Vivo Surface-Enhanced Raman Spectroscopy Glucose Sensor,” Diabetes Technology and Therapeutics, vol. 10 (4), 2008, pp. 257-265.
Lyman D J., “Polyurethanes. I. The Solution Polymerization of Diisocyanates with Ethylene Glycol,” Journal of Polymer Science, 1960, vol. XLV, pp. 49-59.
Lynch S.M., et al., “Estimation-Based Model Predictive Control of Blood Glucose in Type I Diabetics: A Simulation Study,” Proceedings of the IEEE 27th Annual Northeast Bioengineering Conference, 2001, pp. 79-80.
Lynn P.A., “Recursive Digital Filters for Biological Signals,” Med. & Biol. Engineering, vol. 9, 1971, pp. 37-43.
Madaras M B., et al., “Microfabricated Amperometric Creatine and Creatinine Biosensors,” Analytica Chimica Acta, 1996, vol. 319, pp. 335-345.
Maidan R., et al., “Elimination of Electrooxidizable Interferent-Produced Currents in Amperometric Biosensors,” Analytical Chemistry, vol. 64, 1992, pp. 2889-2896.
Makale M.T., et al., “Tissue Window Chamber System for Validation of Implanted Oxygen Sensors,” American Journal of Physiology-Heart and Circulatory Physiology, vol. 284, Feb. 21, 2003, pp. 1-27.
Malin S.F., et al., “Noninvasive Prediction of Glucose by Near-Infrared Diffuse Reflectance Spectroscopy,” Clinical Chemistry, vol. 45 (9), 1999, pp. 1651-1658.
Mancy K.H., et al., “A Galvanic Cell Oxygen Analyzer,” Journal of Electroanalytical Chemistry, vol. 4, 1962, pp. 65-92.
Maran A., et al., “Continuous Subcutaneous Glucose Monitoring in Diabetic Patients,” A Multicenter Analysis, Diabetes Care, vol. 25 (2), Feb. 2002, pp. 347-352.
March W.F., “Dealing with the Delay,” Diabetes Technology & Therapeutics, vol. 4 (1), 2002, pp. 49-50.
Marena S., et al., “The Artificial Endocrine Pancreas in Clinical Practice and Research,” Panminerva Medica, vol. 35 (2), 1993, pp. 67-74.
Martin R.F., “General Deming Regression for Estimating Systematic Bias and its Confidence Interval in Method-Comparison Studies,” Clinical Chemistry, vol. 46 (1), 2000, pp. 100-104.
Mascini M., et al., “Glucose Electrochemical Probe with Extended Linearity for Whole Blood,” Journal Pharmaceutical and Biomedical Analysis, vol. 7 (12), 1989, pp. 1507-1512.
Mastrototaro J.J., et al., “An Electroenzymatic Glucose Sensor Fabricated on a Flexible Substrate,” Sensors and Actuators B, vol. 5, 1991, pp. 139-144.
Mastrototaro J.J., et al., “Reproducibility of the Continuous Glucose Monitoring System Matches Previous Reports and the Intended Use of the Product,” Diabetes Care, vol. 26 (1), Jan. 2003, pp. 256-257.
Mastrototaro J.J., “The MiniMed Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S13-S18.
Matsuki H., “Energy Transfer System Utilizing Amorphous Wires For Implantable Medical Devices,” IEEE Transactions on Magnetics, vol. 31 (2), 1994, pp. 1276-1282.
Matsumoto T., et al., “A long-Term Lifetime Amperometric Glucose Sensor with a Perfluorocarbon Polymer Coating,” Biosensors & Bioelectronics, vol. 16, 2001, pp. 271-276.
Matsumoto T., et al., “A Micro-Planar Amperometric Glucose Sensor Unsusceptible to Interference Species,” Sensors and Actuators B, 49, 1998, pp. 68-72.
Matthews D.R., et al., “An Amperometric Needle-Type Glucose Sensor Testing in Rats and Man,” Diabetic Medicine, vol. 5, 1988, pp. 248-252.
Mazze R.S., et al., “Characterizing Glucose Exposure for Individuals with Normal Glucose Tolerance Using Continuous Glucose Monitoring and Ambulatory Glucose Profile Analysis,” Diabetes Technology & Therapeutics, vol. 10 (3), 2008, pp. 149-159.
Mazzola F., et al., “Video Diabetes: A Teaching Tool for Children with Insulin-Dependent Diabetes,” IEEE, Proceedings 7th Annual Symposium on Computer Applications in Medical Care, Oct. 1983, 1 page Abstract.
McCartney L.J., et al., “Near-Infrared Fluorescence Lifetime Assay for Serum Glucose Based on Allophycocyanin-Labeled Concanavalin A,” Analytical Biochemistry, vol. 292, 2001, pp. 216-221.
McGrath M.J., et al., “The Use of Differential Measurements with a Glucose Biosensor for Interference Compensation During Glucose Determinations by Flow Injection Analysis,” Biosens Bioelectron, vol. 10, 1995, pp. 937-943.
McKean B.D., et al., “A Telemetry Instrumentation System for Chronically Implanted Glucose and Oxygen Sensors,” IEEE Transactions on Biomedical Engineering, vol. 35 (7), Jul. 1988, pp. 526-532.
Memoli A., et al., “A Comparison between Different Immobilised Glucoseoxidase-Based Electrodes,” Journal of Pharmaceutical and Biomedical Analysis, vol. 29, 2002, pp. 1045-1052.
Merriam Webster Online Dictionary, Definition for “Aberrant,” retrieved from https://www.merriam-webster.com/dictionary/aberrant Aug. 19, 2008, 1 page.
Merriam-Webster Online Dictionary, Definition of “Acceleration” retrieved from http://www.merriam-webster.com/dictionary/Acceleration Jan. 11, 2010, 1 page.
Merriam-Webster Online Dictionary, Definition of “Nominal” retrieved from http://www.merriam-webster.com/dictionary/nominal Apr. 23, 2007, 1 page.
Merriam-Webster Online Dictionary, Definition of “System”. http://www.merriamwebster.com/dictionary/System Jan. 11, 2010, 2 pages.
Metzger M., et al., “Reproducibility of Glucose Measurements using the Glucose Sensor,” Diabetes Care, vol. 25 (6), Jul. 2002, pp. 1185-1191.
Meyerhoff C., et al., “On Line Continuous Monitoring of Subcutaneous Tissue Glucose in Men by Combining Portable Glucosensor With Microdialysis,” Diabetologia, vol. 35 (11), 1992, pp. 1087-1092.
Miller J.A., et al., “Development of an Autotuned Transcutaneous Energy Transfer System,” ASAIO Journal, vol. 39, 1993, pp. M706-M710.
Miller K.M., et al., “Generation of IL-1 like Activity in Response to Biomedical Polymer Implants: a Comparison of in Vitro and in Vivo Models,” Journal of Biomedical Materials Research, vol. 23(9), 1989, pp. 1007-1026.
Miller K.M., et al., “Human monocyte/macrophage activation and interleukin 1 generation by biomedical polymers,” Journal of Biomedical Materials Research, vol. 22 (8), 1988, pp. 713-731.
Miller K.M., et al., “In Vitro Stimulation of Fibroblast Activity by Factors Generated from Human Monocytes Activated by Biomedical Polymers,” Journal of Biomedical Materials Research, vol. 23(8), 1989, pp. 911-930.
Moatti-Sirat D., et al., “Evaluating In Vitro and In Vivo the Interference of Ascorbate and Acetaminophen on Glucose Detection by a Needle-Type Glucose Sensor,” Biosensors and Bioelectronics, vol. 7, 1992, pp. 345-352.
Moatti-Sirat D., et al., “Reduction of Acetaminophen Interference in Glucose Sensors by a Composite Nafion Membrane: Demonstration in Rats and Man,” Diabetologia, vol. 37 (6), Jun. 1994, pp. 610-616.
Moatti-Sirat., et al., “Towards Continuous Glucose Monitoring: In Vivo Evaluation of a Miniaturized Glucose Sensor Implanted for Several Days in Rat Subcutaneous Tissue,” Diabetologia, vol. 35, 1992, pp. 224-230.
Monsod T.P., et al., “Do Sensor Glucose Levels Accurately Predict Plasma Glucose Concentrations During Hypoglycemia And Hyperinsulinemia? ,”Diabetes Care, vol. 25 (5), 2002, pp. 889-893.
Morff R.J., et al., “Microfabrication of Reproducible, Economical, Electroenzymatic Glucose Sensors,” Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 12 (2), 1990, pp. 0483-0484.
Mosbach K., et al., “Determination of Heat Changes in the Proximity of Immobilized Enzymes with an Enzyme Thermistor and its Use for the Assay of Metabolites,” Biochimica Biophysica Acta, vol. 403, 1975, pp. 256-265.
Motonaka J., et al., “Determination of Cholesterol and Cholesterol Ester with Novel enzyme Microsensors,” Anal. Chem., vol. 65, 1993, pp. 3258-3261.
Moussy F., et al., “A Miniaturized Nafion-Based Glucose Sensor: In Vitro and In Vivo Evaluation in Dogs, ” International Journals of Artificial Organs, vol. 17 (2), 1994, pp. 88-94.
Moussy F., et al., “Biomaterials community examines biosensor biocompatibility,” Diabetes Technology & Therapeutics, vol. 2(3), 2000, pp. 473-477.
Moussy F., et al., “Performance of Subcutaneously Implanted Needle-Type Glucose Sensors Employing a Novel Trilayer Coating,” Analytical Chemistry, vol. 65, Aug. 1, 1993, pp. 2072-2077.
Moussy F., “Implantable Glucose Sensor: Progress and Problems,” IEEE, Nov. 2002, pp. 270-273.
Mowery K.A., et al., “Preparation and Characterization by Hydrophobic Polymeric Films that are Thromboresistant via Nitric Oxide Release,” Biomaterials, vol. 21, 2000, pp. 9-21.
Murphy S.M., et al., “Polymer Membranes in Clinical Sensor Applications, II. The Design and Fabrication of Permselective Hydrogels for Electrochemical Devices,” Biomaterials, 1992, vol. 13 (14), pp. 979-990.
Muslu, “Trickling Filter Performance,” Applied Biochemistry and Biotechnology, vol. 37, 1992, pp. 211-224.
Myler S., et al., “Ultra-Thin-Polysiloxane-Film-Composite Membranes for the Optimisation of Amperometric Oxidase Enzyme Electrodes,” Biosensors & Bioelectronics, vol. 17, 2002, pp. 35-43.
Nakayama Y., et al., “Surface Fixation of Hydrogels: Heparin and Glucose Oxidase Hydrogelated Surfaces” ASAIO Journal, 1992, pp. M421-M424.
Nam Y.S., et al., “A Novel Fabrication Method of Macroporous Biodegradable Polymer Scaffolds Using Gas Foaming Salt as a Porogen Additive,” J Biomed Mater Res, 2000, vol. 53, pp. 1-7.
Neuburger G.G., et al., “Pulsed Amperometric Detection of Carbohydrates at Gold Electrodes with a Two-Step Potential Waveform,” Anal. Chem., vol. 59, 1987, pp. 150-154.
NewsRx, “Glucose Monitoring: FDA OKs New Device to Manage Diabetes,” Medical Letter on the CDC & FDA via NewsRx.com, Aug. 3, 2003, 1 page.
Nintendo Healthcare, Wired, Dec. 1993, 1 page.
Novo Nordisk Pharmaceuticals Inc., “Diabetes Educational Video Game Recognized by Software Publishers Association,” Press Release, Mar. 14, 1994, 4 pages.
Ohara T.J., et al., “Glucose Electrodes Based On Cross-Linked [Os(bpy)2Cl](+/2+) Complexed Poly(1-Vinylimidazole) Films,” Analytical Chemistry, vol. 65, Dec. 1993, pp. 3512-3517.
Ohara T.J., et al., ““Wired” Enzyme Electrodes for Amperometric Determination of Glucose or Lactate in the Presence of Interfering Substances,” Anal Chem, vol. 66, 1994, pp. 2451-2457.
Okuda, et al., “Mutarotase Effect on Micro Determinations of D-Glucose and its Anomers with β D-Glucose Oxidase,” Anal Biochem, vol. 43 (1), 1971, pp. 312-315.
Oxford English Dictionary Online, Definition of “Impending,” http://www.askoxford.com/results/?view=devdictfield-12668446_Impending&branch Jan. 11, 2010, 1 page.
Palmisano F., et al., “Simultaneous Monitoring of Glucose and Lactate by an Interference and Cross-Talk Free Dual Electrode Amperometric Biosensor Based on Electropolymerized Thin Films,” Biosensors & Bioelectronics, vol. 15, 2000, pp. 531-539.
Panetti T.S., “Differential Effects of Sphingosine 1-Phosphate and Lysophosphatidic Acid on Endothelial Cells,” Biochimica et Biophysica Acta, vol. 1582, 2002, pp. 190-196.
Panteleon A.E., et al., “The Role of the Independent Variable to Glucose Sensor Calibration,” Diabetes Technology & Therapeutics, vol. 5 (3), 2003, pp. 401-410.
Parker R.S., et al., “A Model-Based Algorithm for Blood Glucose Control In Type I Diabetic Patients,” IEEE Trans Biomed Engg (BME), vol. 46(2), 1999, pp. 148-157.
Patel H., et al., “Amperometric Glucose Sensors Based on Ferrocene Containing Polymeric Electron Transfer Systems—A Preliminary Report,” Biosensors & Bioelectronics, vol. 18, 2003, pp. 1073-1076.
Peacock W.F., et al., “Cardiac Troponin and Outcome in Acute Heart Failure,” N. Engl. J. Med., vol. 358, 2008, pp. 2117-2126.
Peguin S., et al., “Pyruvate Oxidase and Oxaloacetate Decarboxylase Enzyme Electrodes—Simultaneous Determination of Transaminases with a Two-electrode-based Analyzer,” Analytica Chimica Acta, vol. 222, 1989, pp. 83-93.
Pfeiffer E.F., et al., “On Line Continuous Monitoring of Subcutaneous Tissue Glucose is Feasible by Combining Portable Glucosensor with Microdialysis,” Horm. Metab. Res., vol. 25, 1993, pp. 121-124.
Pfeiffer E.F., “The Glucose Sensor: The Missing Link in Diabetes Therapy,” Horm Metab Res Suppl., vol. 24, 1990, pp. 154-164.
Phillips R.E., et al., “Biomedical Applications of Polyurethanes: Implications of Failure Mechanisms,” Journal of Biomedical application, vol. 3, Oct. 1988, pp. 206-227.
Phillips R.P., “A High Capacity Transcutaneous Energy Transmission System,” ASIAO Journal, vol. 41, 1995, pp. M259-M262.
Pichert J.W., et al., “Issues for the Coming Age of Continuous Glucose Monitoring,” Diabetes Educator, vol. 26 (6), Nov.-Dec. 2000, pp. 969-980.
Pickup J.C., et al., “Developing Glucose Sensors for In Vivo Use,” Elsevier Science Publishers Ltd (UK), Tibtech, vol. 11, 1993, pp. 285-291.
Pickup J.C., et al., “Implantable Glucose Sensors: Choosing the Appropriate Sensor Strategy,” Biosensors, vol. 3, (1987/1988), pp. 335-346.
Pickup J.C., et al., “In Vivo Molecular Sensing in Diabetes Mellitus: An Implantable Glucose Sensor with Direct Electron Transfer,” Diabetologia, vol. 32, 1989, pp. 213-217.
Pickup J.C., et al., “Potentially-Implantable, Amperometric Glucose Sensors with Mediated Electron Transfer: Improving the Operating Stability,” Biosensors, vol. 4, 1989, pp. 109-119.
Pickup J.C., et al., “Progress Towards in Vivo Glucose Sensing with a Ferrocene-Mediated Amperometric Enzyme Electrode,” Horm Metab Res Suppl, vol. 20, 1988, pp. 34-36.
Pickup J.C., et al., “Responses and Calibration of Amperometric Glucose Sensors Implanted in the Subcutaneous Tissue of Man,” ACTA Diabetol, vol. 30, 1993, pp. 143-148.
Pineda L.M., et al., “Bone Regeneration with Resorbable Polymeric Membranes. III. Effect of Poly(L-lactide) Membrane Pore Size on the Bone Healing Process in Large Defects,” Journal of Biomedical Materials Research, vol. 31, 1996, pp. 385-394.
Pinner S.H., et al., “Cross-Linking of Cellulose Acetate by lonizing Radiation,” Nature, vol. 184, Oct. 24, 1959, pp. 1303-1304.
Pishko M.V., et al., “Amperometric Glucose Microelectrodes Prepared Through Immobilization of Glucose Oxidase in Redox Hydrogels,” Analytical Chemistry, vol. 63 (20), 1991, pp. 2268-2272.
Pitzer K.R., et al., “Detection of Hypoglycemia with the Glucowatch Biographer,” Diabetes Care, vol. 24 (5), 2001, pp. 881-885.
Poirier J.Y., et al., “Clinical and Statistical Evaluation of Self-Monitoring Blood Glucose Meters,” Diabetes Care, vol. 21 (11), Nov. 1998, pp. 1919-1924.
Poitout V., et al., “A Glucose Monitoring System for on Line Estimation in Man of Blood Glucose Concentration Using a Miniaturized Glucose Sensor Implanted in the Subcutaneous Tissue and a Wearable Control Unit,” Diabetologia, vol. 36, 1993, pp. 658-663.
Poitout V., et al., “Development of a Glucose Sensor for Glucose Monitoring in Man: The Disposable Implant Concept,” Clinical Materials, vol. 15, 1994, pp. 241-246.
Poitout V., et al., “In Vitro and In Vivo Evaluation in Dogs of a Miniaturized Glucose Sensor,” ASAIO Transactions, vol. 37, 1991, pp. M298-M300.
Postlethwaite T.A., et al., “Interdigitated Array Electrode as an Alternative to the Rotated Ring-Disk Electrode for Determination of the Reaction Products of Dioxygen Reduction,” Analytical Chemistry, vol. 68 (17), Sep. 1996, pp. 2951-2958.
Prabhu V.G., et al., “Electrochemical Studies of Hydrogen Peroxide at a Platinum Disc Electrode,” Electrochimica Acta, vol. 26 (6), 1981, pp. 725-729.
Quinn C.A.P., et al., “Biocompatible, Glucose-Permeable Hydrogel for In situ Coating of Implantable Biosensors,” Biomaterials, vol. 18 (24), 1997, pp. 1665-1670.
Quinn C.P., et al., “Kinetics of Glucose Delivery to Subcutaneous Tissue in Rats Measured with 0.3-mm Amperometric Microsensors,” The American Physiological Society, vol. 269, 1995, pp. E155-E161.
Rabah M.A., et al., “Electrochemical Wear of Graphite Anodes During Electrolysis of Brine,” Carbon, vol. 29 (2), 1991, pp. 165-171.
Rafael E., “Cell Transplantation and Immunoisolation: Studies on a Macroencapsulation Device,” Departments of Transplantation Surgery and Pathology, Karolinska Institutet, Huddinge Hospital, Stockholm, Sweden, 1999, pp. 1-83.
Ratner B.D., “Reducing Capsular Thickness and Enhancing Angiogenesis around Implant Drug Release Systems,” Journal of Controlled Release, vol. 78, 2002, pp. 211-218.
Raya Systems Pioneers, “Raya Systems Pioneers Healthy Video Games,” PlayRight, Nov. 1993, pp. 14-15.
Reach G., “A Method for Evaluating in vivo the Functional Characteristics of Glucose Sensors,” Biosensors, vol. 2, 1986, pp. 211-220.
Reach G., et al., “Can Continuous Glucose Monitoring Be Used for the Treatment of Diabetes?,” Analytical Chemistry, vol. 64 (6), Mar. 15, 1992, pp. 381A-386A.
Reach G., “Which Threshold to Detect Hypoglycemia? Value of Receiver-Operator Curve Analysis to Find a Compromise Between Sensitivity and Specificity,” Diabetes Care, vol. 24 (5), May 2001, pp. 803-804.
Rebrin K., et al., “Automated Feedback Control of Subcutaneous Glucose Concentration in Diabetic Dogs,” Diabetologia, vol. 32, 1989, pp. 573-576.
Rebrin K., et al., “Subcutaneous Glucose Monitoring by Means of Electrochemical Sensors: Fiction or Reality?,” Journal of Biomedical Engineering, vol. 14, Jan. 1992, pp. 33-40.
Rebrin K., et al., “Subcutaneous Glucose Predicts Plasma Glucose Independent of Insulin: Implications for Continuous Monitoring,” The American Physiological Society, vol. 277, 1999, pp. E561-E571.
Renard E., “Implantable Closed-Loop Glucose Sensing and Insulin Delivery: The Future for Insulin Pump Therapy,” Current Opinion in Pharmacology, vol. 2 (6), 2002, pp. 708-716.
Reush, “Organometallic Compounds,” Chemical Reactivity, Virtual Textbook of Organic Chemistry, Retrieved from http://www.cem.msu.edu/-reuschlVirtualText/orgmetal.htm 2004, pp. 1-16.
Rhodes R.K., et al., “Prediction of Pocket-Portable and Implantable Glucose Enzyme Electrode Performance from Combined Species Permeability and Digital Simulation Analysis,” Analytical Chemistry, vol. 66 (9), May 1, 1994, pp. 1520-1529.
Rigla M., et al., “Real-Time Continuous Glucose Monitoring Together with Telemedical Assistance Improves Glycemic Control and Glucose Stability in Pump-Treated Patients,” Diabetes Technology & Therapeutics, vol. 10 (3), 2008, pp. 194-199.
Rinken T., et al., “Calibration of Glucose Biosensors By Using Pre-Steady State Kinetic Data,” Biosensors & Bioelectronics, vol. 13, 1998, pp. 801-807.
Ristic S., et al., “Review: Effects of Rapid-Acting Insulin Analogs on Overall Glycemic Control in Type 1 and Type 2 Diabetes Mellitus,” Diabetes Technology & Therapeutics, vol. 5 (1), 2003, pp. 57-66.
Rivers E.P., et al., “Central Venous Oxygen Saturation Monitoring in the Critically Ill Patient,” Current Opinion in Critical Care, 2001, vol. 7, pp. 204-211.
Sachlos E., et al., “Making Tissue Engineering Scaffolds Work Review on the Application of Solid Freeform Fabrication Technology to the Production of Tissue Engineering Scaffolds,” European Cells and Materials, vol. 5, 2003, pp. 29-40.
Sakakida M., et al., “Development of Ferrocene-Mediated Needle-Type Glucose Sensor as a Measure of True Subcutaneous Tissue Glucose Concentrations,” Artif. Organs Today, vol. 2 (2), 1992, pp. 145-158.
Sakakida M., et al., “Ferrocene-Mediated Needle Type Glucose Sensor Covered with Newly Designed Biocompatible Membrane,” Sensors and Actuators B, vol. 13-14, 1993, pp. 319-322.
Salardi S., et al., “The Glucose Area Under the Profiles Obtained with Continuous Glucose Monitoring System Relationships with HbA1C in Pediatric Type 1 Diabetic Patients,” Diabetes Care, vol. 25 (10), Oct. 2002, pp. 1840-1844.
Samuels M.P., “The Effects of Flight and Altitude,” Arch Dis Child, vol. 89, 2004, pp. 448-455.
San Diego Plastics Inc, “Polyethylene,” Datasheet, Retrieved from http://www.sdplastics.com/polyeth.html on Aug. 19, 2009, 7 pages.
Sanders E., et al., “Fibrous Encapsulation of Single Polymer Microfibers Depends on their Vertical Dimension in Subcutaneous Tissue Polymer Microfibers,” Journal of Biomedical Material Research, vol. 67A, 2003, pp. 1181-1187.
Sansen W., et al., “A Smart Sensor for the Voltammetric Measurement of Oxygen or Glucose Concentrations,” Sensors and Actuators B1, 1990, pp. 298-302.
Sansen W., et al., “Glucose Sensor with Telemetry System,” In Implantable Sensors for Closed Loop Prosthetic Systems edited by Ko W.H, Chapter 12, 1985, pp. 167-175.
Schaffar B.P.H., “Thick Film Biosensors for Metabolites in Undiluted Whole Blood and Plasma Samples,” Analytical Bioanalytical Chemistry, Dec. 2001, vol. 372, pp. 254-260.
Schmidt F.J., et al., “Calibration of a Wearable Glucose Sensor,” The International Journal of Artificial Organs, Wichtig Publishing, IT, vol. 15 (1), Jan. 1, 1992, pp. 55-61.
Schmidt F.J., et al., “Glucose Concentration in Subcutaneous Extracellular Space,” Diabetes Care, vol. 16 (5), May 1993, pp. 695-700.
Schmidtke D.W., et al., “Accuracy of the One-Point in Vivo Calibration of “Wired” Glucose Oxidase Electrodes Implanted in Jugular Veins of Rats in Periods of Rapid Rise and Decline of the Glucose Concentration,” Analytical Chemistry, vol. 70 (10), May 15, 1998, pp. 2149-2155.
Schmidtke D.W., et al., “Measurement and Modeling of the Transient Difference Between Blood and Subcutaneous Glucose Concentrations in the Rat After Injection of Insulin,” Proceedings of the National Academy of Sciences, vol. 95, Jan. 1998, pp. 294-299.
Schoemaker M., et al., “The SCGMI System: Subcutaneous Continuous Glucose Monitoring Based on Microdialysis Technique,” Diabetes Technology & Therapeutics, vol. 5 (4), 2003, pp. 599-608.
Schoonen A.J.M., et al., “Development of a Potentially Wearable Glucose Sensor for Patients with Diabetes Mellitus: Design and In-vitro Evaluation,” Biosensors & Bioelectronics, vol. 5, 1990, pp. 37-46.
Schuler, et al., “Modified Gas-Permeable Silicone Rubber Membranes for Covalent Immobilisation of Enzymes and their Use in Biosensor Development,” Analyst, 1999, vol. 124, pp. 1181-1184.
Selam J.L., “Management of Diabetes with Glucose Sensors and Implantable Insulin Pumps,” From the Dream of the 60s to the Realities of the 90s, ASAIO Journal 1997, vol. 43, pp. 137-142.
Service F.J., et al., “Mean Amplitude of Glycemic Excursions, A Measure of Diabetic Instability,” Diabetes, vol. 19 (9), Sep. 1970, pp. 644-655.
Service F.J., et al., “Measurements of Glucose Control,” Diabetes Care, vol. 10 (2), Mar.-Apr. 1987, pp. 225-237.
Service R.F., “Can Sensors Make a Home in the Body?,” Science, Materials Science: Soft Surface, vol. 297, Aug. 9, 2002, pp. 962-963.
Sharkawy A.A., et al., “Engineering the Tissue Which Encapsulates Subcutaneous Implants. I. Diffusion Properties,” Journal of Biomedical Materials Research, vol. 37, 1996, pp. 401-412.
Shaw G.W., et al., “In Vitro Testing of a Simply Constructed, Highly Stable Glucose Sensor Suitable for Implantation in Diabetic Patients,” Biosensors & Bioelectronics, vol. 6, 1991, pp. 401-406.
Shichiri M., et al., “Glycaemic Control in Pancreatectomized Dogs with a Wearable Artificial Endocrine Pancreas,” Diabetologia, vol. 24, 1983, pp. 179-184.
Shichiri M., et al., “Membrane Design for Extending the Long-Life of an Implantable Glucose Sensor,” Diabetes Nutrition & Metabolism, vol. 2 (4), 1989, pp. 309-313.
Shichiri M., et al., “Needle Type Glucose Sensor for Wearable Artificial Endocrine Pancreas,” In Implantable Sensors for Closed-Loop Prosthetic Systems edited by Ko W.H, Chapter 15, 1985, pp. 197-210.
Shichiri M., et al., “Telemetry Glucose Monitoring Device with Needle-Type Glucose Sensor: A Useful Tool for Blood Glucose Monitoring in Diabetic Individuals,” Diabetes Care, vol. 9 (3), May-Jun. 1986, pp. 298-301.
Shichiri M., et al., “Wearable Artificial Endocrine Pancreas with Needle-Type Glucose Sensor,” Preliminary Communication, Lancet, vol. 2, Nov. 20, 1982, pp. 1129-1131.
Shults M.C., et al., “A Telemetry-Instrumentation System for Monitoring Multiple Subcutaneously Implanted Glucose Sensors,” IEEE Transactions on Biomedical Engineering, vol. 41 (10), Oct. 1994, pp. 937-942.
Sieminski, et al., “Biomaterial-Microvasculature Interactions,” Biomaterials, 2000, vol. 21, pp. 2233-2241.
Sigma-Aldrich Corp., “Cellulose Acetate,” Product Description, Product No. 419028, St. Louis, MO, 2005, 1 page.
Sigma-Aldrich Corp. “Nafion® 117 Solution Product Description, Product No. 70160,” retrieved from https//:www.sigmaaldrich.com/cgi-bin/hsrun/Suite7/Suite/HAHTpage/Suite.HsExternalProd on Apr. 7, 2005, 1 page.
Skyler J.S., “The Economic Burden of Diabetes and the Benefits of Improved Glycemic Control: The Potential Role of a Continuous Glucose Monitoring System,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S7-S12.
Slater-MacLean L., et al., “Accuracy of Glycemic Measurements in the Critically Ill,” Diabetes Technology and Therapeutics, vol. 10 (3), 2008, pp. 169-177.
Smith B., et al., “An Externally Powered, Multichannel, Implantable Stimulator-Telemeter for Control of Paralyzed Muscle,” IEEE Transactions on Biomedical Engineering, vol. 45 (4), Apr. 1998, pp. 463-475.
Smith, et al., “A Comparison of Islet Transplantation and Subcutaneous Insulin Injections for the Treatment of Diabetes Mellitus,” Computers in Biology and Medicine, 1991, vol. 21 (6), pp. 417-427.
Sokol L., et al., “Immobilized-Enzyme Rate-Determination Method for Glucose Analysis,” Clinical Chemistry, vol. 26 (1), 1980, pp. 89-92.
Sokolov S., et al., “Metrological Opportunities of the Dynamic Mode of Operating an Enzyme Amperometric Biosensor,” Medical Engineering & Physics, vol. 17 (6), 1995, pp. 471-476.
Sparacino G., et al., “Continuous Glucose Monitoring Time Series and Hypo-Hyperglycemia Prevention: Requirements, Methods, Open Problems,” Current Diabetes Reviews, vol. 4 (3), 2008, pp. 181-192.
Sproule B.A., et al., “Fuzzy Pharmacology: Theory and Applications,” Trends in Pharmacological Sciences, vol. 23 (9), Sep. 2002, pp. 412-417.
Sriyudthsak M., et al., “Enzyme-Epoxy Membrane Based Glucose Analyzing System and Medical Applications,” Biosensors & Bioelectronics, vol. 11 (8), 1996, pp. 735-742.
Steil G.M., et al., “Determination of Plasma Glucose During Rapid Glucose Excursions with a Subcutaneous Glucose Sensor,” Diabetes Technology & Therapeutics, vol. 5 (1), 2003, pp. 27-31.
Stern M., et al., “Electrochemical Polarization: I. A Theoretical Analysis of the Shape of Polarization Curves,” Journal of the Electrochemical Society, vol. 104 (1), Jan. 1957, pp. 56-63.
Sternberg, et al., “Covalent Enzyme Coupling on Cellulose Acetate Membranes for Glucose Sensor Development,” Anal Chem, Dec. 1988, vol. 60(24), pp. 2781-2786.
Sternberg F., et al., “Does Fall in Tissue Glucose Precede Fall in Blood Glucose?,” Diabetologia, vol. 39, 1996, pp. 609-612.
Sternberg R., et al., “Study and Development of Multilayer Needle-type Enzyme Based Glucose Microsensors,” Biosensors, Mar. 20, 1988, vol. 4 (1), pp. 27-40.
Stokes, “Polyether Polyurethanes: Biostable or Not,” Journal of Biomaterials Applications, Oct. 1988, vol. 3, pp. 228-259.
Street, et al., “Islet Graft Assessment in the Edmonton Protocol: Implications for Predicting Long-Term Clinical Outcome,” Diabetes, 2004, vol. 53, pp. 3107-3114.
Street J.O., et al., “A Note on Computing Robust Regression Estimates Via Iteratively Reweighted Least Squares,” The American Statistician, vol. 42 (2), May 1988, pp. 152-154.
Suh, et al., “Behavior of Fibroblasts on a Porous Hyaluronic Acid Incorporated Collagen Matrix,” Yonsei Medical Journal, 2002, vol. 43 (2), pp. 193-202.
Sumino T., et al., “Preliminary Study of Continuous Glucose Monitoring with a Microdialysis Technique,” Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 20 (4), 1998, pp. 1775-1778.
Takatsu I., et al., “Solid State Biosensors Using Thin-Film Electrodes,” Sensors and Actuators, 1987, vol. 11, pp. 309-317.
Takegami S., et al., “Pervaporation of Ethanol/Water Mixtures Using Novel Hydrophobic Membranes Containing Polydimethylsiloxane,” Journal of Membrane Science, vol. 75, 1992, pp. 93-105.
Tamura T., et al., “Preliminary Study of Continuous Glucose Monitoring with a Microdialysis Technique and a Null Method—A Numerical Analysis,” Frontiers of Medical & Biological Engineering, vol. 10 (2), 2000, pp. 147-156.
Tanenberg R.J., et al., “Continuous Glucose Monitoring System: A New Approach to the Diagnosis of Diabetic Gastroparesis,” Diabetes Technology & Therapeutics, vol. 2, Supplement 1, 2000, pp. S73-S80.
Tang, et al., “Fibrin(ogen) Mediates Acute Inflammatory Responses to Biomaterials,” J.Exp.Med, 1993, vol. 178, pp. 2147-2156.
Tang, et al., “Inflammatory Responses to Biomaterials,” Am J Clin Pathol, 1995, vol. 103, pp. 466-471.
Tang, et al., “Mast Cells Mediate Acute Inflammatory Responses to Implanted Biomaterials,” Proceedings of the National Academy of Sciences of the USA, 1998, vol. 95, pp. 8841-8846.
Tang, et al., “Molecular Determinants of Acute Inflammatory Responses to Biomaterials,” J Clin Invest, 1996, vol. 97, pp. 1329-1334.
Tatsuma T., et al., “Oxidase/Peroxidase Bilayer-Modified Electrodes as Sensors for Lactate, Pyruvate, Cholesterol and Uric Acid,” Analytica Chimica Acta, vol. 242, 1991, pp. 85-89.
Thennadil S.N., et al., “Comparison of Glucose Concentration in Interstitial Fluid, and Capillary and Venous Blood During Rapid Changes in Blood Glucose Levels,” Diabetes Technology & Therapeutics, vol. 3 (3), 2001, pp. 357-365.
Thijssen, et al., “A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 1, Theory and Simulations, Analytica chimica Acta, 1984, vol. 156, pp. 87-101.
Thijssen, et al., “A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 3,Variance Reduction ,Analytica chimica Acta, 1985, vol. 173, pp. 265-272.
Thijssen, et al., “A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 4, Flow Injection Analysis, Analytica chimica Acta, 1985, vol. 174, pp. 27-40.
Thijssen P.C., “A Kalman Filter for Calibration, Evaluation of Unknown Samples and Quality Control in Drifting Systems,” Part 2,Optimal Designs, Analytica chimica Acta, vol. 162, 1984, pp. 253-262.
Thome V., et al., “(Abstract) Can the Decrease in Subcutaneous Glucose Concentration Precede the Decrease in Blood Glucose Level? Proposition for a Push-Pull Kinetics Hypothesis,” Horm. metab. Res., vol. 27, 1995, p. 53.
Thome-Duret V., et al., “Continuous Glucose Monitoring in the Free-Moving Rat,” Metabolism, vol. 47 (7), Jul. 1998, pp. 799-803.
Thome-Duret V., et al., “Modification of the Sensitivity of Glucose Sensor Implanted into Subcutaneous Tissue,” Diabetes & Metabolism, vol. 22, 1996, pp. 174-178.
Thome-Duret V., et al., “Use of a Subcutaneous Glucose Sensor to Detect Decreases in Glucose Concentration Prior to Observation in Blood,” Analytical Chemistry, vol. 68 (21), Nov. 1, 1996, pp. 3822-3826.
Thompson M., et al., “In Vivo Probes: Problems and Perspectives,” Clinical Biochemistry, vol. 19 (5), Oct. 1986, pp. 255-261.
Tibell, et al., “Survival of Macroencapsulated Allogeneic Parathyroid Tissue One Year after Transplantation in Nonimmunosuppressed Humans,” Cell Transplantation, 2001, vol. 10, pp. 591-599.
Tierney M.J., et al., “Effect of Acetaminophen on the Accuracy of Glucose Measurements Obtained with the GlucoWatch Biographer,” Diabetes Technology & Therapeutics, vol. 2 (2), 2000, pp. 199-207.
Tierney M.J., et al., “The Gluco Watch® Biographer: A Frequent, Automatic and Noninvasive Glucose Monitor,” Annals of Medicine, vol. 32, 2000, pp. 632-641.
Tilbury J.B., et al., “Receiver Operating Characteristic Analysis for Intelligent Medical Systems—A New Approach for Finding Confidence Intervals,” IEEE Transactions on Biomedical Engineering, vol. 47 (7), Jul. 2000, pp. 952-963.
Torjman M.C., et al., “Glucose Monitoring in Acute Care: Technologies on the Horizon,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 178-181.
Trajanoski Z., et al., “Neural Predictive Controller For Insulin Delivery Using The Subcutaneous Route,” IEEE Transactions on Biomedical Engineering, vol. 45(9), 1998, pp. 1122-1134.
Trecroci D., “A Glimpse into the Future-Continuous Monitoring of Glucose with a Microfiber,” Diabetes Interview, Jul. 2002, pp. 42-43.
Tse P.S.H., et al., “Time-Dependent Inactivation of Immobilized Glucose Oxidase and Catalase,” Biotechnology & Bioengineering, vol. 29, 1987, pp. 705-713.
Turner A.P.F., “Amperometric Biosensor based on Mediator-Modified Electrodes,” Methods in Enzymology, 1988, vol. 137, pp. 90-103.
Turner A.P.F., et al., “Carbon Monoxide: Acceptor Oxidoreductase from Pseudomonas Thermocarboxydovorans Strain C2 and its Use in a Carbon Monoxide Sensor,” Analytica Chimica Acta, vol. 163, 1984, pp. 161-174.
Turner A.P.F., et al., “Diabetes Mellitus: Biosensors for Research and Management,” Biosensors, vol. 1, 1985, pp. 85-115.
Unger J., et al., “Glucose Control in the Hospitalized Patient,” Emergency Medicine, vol. 36 (9), 2004, pp. 12-18.
Updike S.J., et al., “A Subcutaneous Glucose Sensor with Improved Longevity, Dynamic Range, and Stability of Calibration,” Diabetes Care, vol. 23 (2), Feb. 2000, pp. 208-214.
Updike S.J., et al., “Continuous Glucose Monitor Based on an Immobilized Enzyme Electrode Detector,” Journal of Laboratory and Clinical Medicine, vol. 93(4), 1979, pp. 518-527.
Updike S.J., et al., “Enzymatic Glucose Sensor: Improved Long-Term Performance in Vitro and In Vivo,” ASAIO Journal, vol. 40 (2), Apr.-Jun. 1994, pp. 157-163.
Updike S.J., et al., “Implanting the Glucose Enzyme Electrode: Problems, Progress, and Alternative Solutions,” Diabetes Care, vol. 5 (3), May-Jun. 1982, pp. 207-212.
Updike S.J., et al., “Laboratory Evaluation of New Reusable Blood Glucose Sensor,” Diabetes Care, vol. 11 (10), Nov.-Dec. 1988, pp. 801-807.
Updike S.J., et al., “Principles of Long-Term Fully Implanted Sensors with Emphasis on Radiotelemetric Monitoring of Blood Glucose Form Inside a Subcutaneous Foreign Body Capsule (FBC),” Edited by Fraser D M, Biosensors in the Body: Continuous in vivo Monitoring, John Wiley & Sons Ltd., New York, 1997, Chapter 4, pp. 117-137.
Updike S.J., et al., “The Enzyme Electrode,” Nature, vol. 214, Jun. 3, 1967, pp. 986-988.
Utah Medical Products Inc., “Deltran—Disposable Blood Pressure Transducers,” Product Specifications, 2003-2006, 6 pages.
Vadgama P., “Diffusion Limited Enzyme Electrodes,” NATO ASI Series: Series C, Math and Phys. Sci, vol. 226, 1988, pp. 359-377.
Vadgama P., “Enzyme Electrodes as Practical Biosensors,” Journal of Medical Engineering & Technology, vol. 5 (6), Nov. 1981, pp. 293-298.
Valdes T.I., et al., “In Vitro and In Vivo Degradation of Glucose Oxidase Enzyme used for an Implantable Glucose Biosensor,” Diabetes Technology & Therapeutics, vol. 2 (3), 2000, pp. 367-376.
Van Den Berghe, “Tight Blood Glucose Control with Insulin in “Real-Life” Intensive Care,” Mayo Clinic Proceedings, vol. 79 (8), Aug. 2004, pp. 977-978.
Velho G., et al., “In Vitro and In Vivo Stability of Electrode Potentials in Needle-Type Glucose Sensors,” Influence of Needle Material, Diabetes, vol. 38, Feb. 1989, pp. 164-171.
Velho G., et al., “Strategies for Calibrating a Subcutaneous Glucose Sensor,” Biomed Biochim Acta, vol. 48 (11/12), 1989, pp. 957-964.
Vesper H.W., et al., “Assessment of Trueness of a Glucose Monitor Using Interstitial Fluid and Whole Blood as Specimen Matrix,” Diabetes Technology & Therapeutics, vol. 8 (1), 2006, pp. 76-80.
Von Woedtke T., et al., “In Situ Calibration of Implanted Electrochemical Glucose Sensors,” Biomed. Biochim. Acta 48 vol. 11/12, 1989, pp. 943-952.
Wade L.G., “Reactions of Aromatic Compounds,” Organic Chemistry, Chapter 17, 5th edition, 2003, pp. 762-763.
Wagner, et al., “Continuous Amperometric Monitoring of Glucose in a Brittle Diabetic Chimpanzee with a Miniature Subcutaneous Electrode,” Proc. Natl. Acad. Sci. USA, vol. 95, May 1998, pp. 6379-6382.
Wang J., et al., “Highly Selective Membrane-Free Mediator-Free Glucose Biosensor,” Analytical Chemistry, vol. 66 (21), Nov. 1, 1994, pp. 3600-3603.
Wang X., et al., “Improved Ruggedness for Membrane-Based Amperometric Sensors using a Pulsed Amperometric Method,” Analytical Chemistry, vol. 69 (21), Nov. 1, 1997, pp. 4482-4489.
Ward W.K., et al., “A New Amperometric Glucose Microsensor: In Vitro and Short-Term In Vivo Evaluation,” Biosensors & Bioelectronics, vol. 17, 2002, pp. 181-189.
Ward W.K., et al., “Assessment of Chronically Subcutaneous Glucose Sensors in Dogs: The Effect of Surrounding Fluid Masses,” ASAIO Journal, 1999, vol. 45 (6), pp. 555-561.
Ward W.K., et al., “Rise in Background Current Over Time in a Subcutaneous Glucose Sensor in the Rabbit,” Relevance to Calibration and Accuracy, Biosensors & Bioelectronics, vol. 15, 2000, pp. 53-61.
Ward W.K., et al., “Understanding Spontaneous Output Fluctuations of an Amperometric Glucose Sensor: Effect of Inhalation Anesthesia and Use of a Nonenzyme Containing Electrode,” ASAIO Journal, 2000, pp. 540-546.
Wentholt I.M.E., et al., “Relationship between Interstitial and Blood Glucose in Type 1 Diabetes Patients: Delay and the Push-pull Phenomenon Revisited,” Diabetes Technology & Therapeutics, vol. 9 (2), 2007, pp. 169-175.
Wientjes K.J.C., “Development of a Glucose Sensor for Diabetic Patients,” (Ph.D. Thesis), 2000, 212 pages.
Wikipedia., “Intravenous Therapy,” http://en.wikipedia.org/wiki/Intravenous_therapy, Aug. 15, 2006, 6 pages.
Wilkins E., et al., “Glucose Monitoring: State of the Art and Future Possibilities,” Med. Eng. Phys., vol. 18 (4), 1996, pp. 273-288.
Wilkins E., et al., “Integrated Implantable Device for Long-Term Glucose Monitoring,” Biosensors & Bioelectronics, vol. 10, 1995, pp. 485-494.
Wilkins E.S., et al., “The Coated Wire Electrode Glucose Sensor,” Horm Metab Res Suppl., vol. 20, 1988, pp. 50-55.
Wilson G.S., et al., “Enzyme-Based Biosensors for In Vivo Measurements,” Chem. Rev., vol. 100, 2000, pp. 2693-2704.
Wilson G.S., et al., “Progress Toward the Development of an Implantable Sensor for Glucose,” Clinical Chemistry, vol. 38 (9), 1992, pp. 1613-1617.
Wolpert H., “Establishing a Continuous Glucose Monitoring Program,” Journal of Diabetes Science and Technology, Mar. 2008, vol. 2 (2), pp. 307-310.
Wolpert H.A., “Commentary: A Clinician's Perspective on Some of the Challenges in Closed Loop,” Diabetes Technology & Therapeutics, vol. 5 (5), 2003, pp. 843-846.
Wood W D., et al., “Hermetic Sealing with Epoxy,” Pave Technology-Mechanical Engineering, Mar. 1990, 3 pages.
Woodward S.C., “How Fibroblasts and Giant Cells Encapsulate Implants: Considerations in Design of Glucose Sensors,” Diabetes Care, vol. 5 (3) May-Jun. 1982, pp. 278-281.
Worsley G.J et al., “Measurement of Glucose in Blood with a Phenylboronic Acid Optical Sensor,” Journal of Diabetes Science and Technology, vol. 2 (2), Mar. 2008, pp. 213-220.
Wright M., et al., “Bioelectrochemical Dehalogenations Via Direct Electrochemistry of Poly(ethylene oxide)-Modified Myoglobin,” Electrochemistry Communications, vol. 1, 1999, pp. 609-613.
Wu H., et al., “In Situ Electrochemical Oxygen Generation with an Immunoisolation Device,” Annals New York Academy of Sciences, vol. 875, 1999, pp. 105-125.
Yamasaki Y., et al., “Direct Measurement of Whole Blood Glucose by a Needle-Type Sensor,” Clinica Chimica Acta. 93, 1989, pp. 93-98.
Yamasaki Y., “The Development of a Needle-Type Glucose Sensor for Wearable Artificial Endocrine Pancreas,” Medical Journal of Osaka University, vol. 35 (1-2), Sep. 1984, pp. 25-34.
Yang C., et al., “A Comparison of Physical Properties and Fuel Cell Performance of Nafion and Zirconium Phosphate/Nation Composite Membranes,” Journal of Membrane Science, vol. 237, 2004, pp. 145-161.
Yang Q., et al., “Development of Needle-Type Glucose Sensor with High Selectivity,” Science and Actuators B, vol. 46, 1998, pp. 249-256.
Yang S., et al., “A Glucose Biosensor Based On an Oxygen Electrode: In-Vitro Performances in a Model Buffer Solution and in Blood Plasma,” Biomedical Instrumentation & Technology, vol. 30 (1), 1996, pp. 55-61.
Yang S., et al., “Glucose Biosensors with Enzyme Entrapped in Polymer Coating,” Biomedical Instrument and Technology, Mar./Apr. 1995, vol. 29 (2), pp. 125-133.
Ye L., et al., “High Current Density Wired' Quinoprotein Glucose Dehydrogenase Electrode,” Analytical Chemistry, vol. 65, 1993, pp. 238-241.
Zamzow K.L., et al., “Development and Evaluation of a Wearable Blood Glucose Monitor,” ASAIO Transactions, vol. 36 (3), 1990, pp. M588-M591.
Zavalkoff S.R., et al., “Evaluation Of Conventional Blood Glucose Monitoring as An Indicator of Integrated Glucose Values Using a Continuous Subcutaneous Sensor,” Diabetes Care, vol. 25(9), 2002, pp. 1603-1606.
Zethelius B., et al., “Use Of Multiple Biomarkers to Improve the Prediction of Death From Cardiovascular Causes,” N. Engl. J. Med., vol. 358, May 2008, pp. 2107-2116.
Zhang, et al., “Elimination of the Acetaminophen Interference in an Implantable Glucose Sensor,” Analytical Chemistry, 1994, vol. 66 (7), pp. 1183-1188.
Zhang Y., et al., “Electrochemical Oxidation Of H2O2 On Pt and Pt + Ir Electrodes in Physiological Buffer and its Applicability to H2O2-Based Biosensors,” J. Electro Analytical Chemistry, vol. 345, 1993, pp. 253-271.
Zhang Y., et al., “In Vitro and In Vivo Evaluation of Oxygen Effects on a Glucose Oxidase Based Implantable Glucose Sensor,” Analytica Chimica Acta, vol. 281, 1993, pp. 513-520.
Zhu, et al., “Fabrication and Characterization of Glucose Sensors Based on a Microarray H2O2 Electrode,” Biosensors & Bioelectronics, 1994, vol. 9, pp. 295-300.
Zhu, et al., “Planar Amperometric Glucose Sensor Based on Glucose Oxidase Immobilized by Chitosan Film on Prussian blue Layer,” Sensors, 2002, vol. 2, pp. 127-136.
Ziaie, et al., “A Single-Channel Implantable Microstimulator for Functional Neuromuscular Stimulation,” IEEE Transactions on Biomedical Engineering, 1997, vol. 44(10), pp. 909-920.
U.S. Appl. No. 17/196,864, “Final Office Action”, U.S. Appl. No. 17/196,864, filed Aug. 15, 2023, 23 pages.
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