Method and apparatus for providing data processing and control in a medical communication system

Description

BACKGROUND

Analyte, e.g., glucose monitoring systems including continuous and discrete monitoring systems generally include a small, lightweight battery powered and microprocessor controlled system which is configured to detect signals proportional to the corresponding measured glucose levels using an electrometer, and RF signals to transmit the collected data. One aspect of certain analyte monitoring systems includes a transcutaneous or subcutaneous analyte sensor configuration which is, for example, partially mounted on the skin of a subject whose analyte level is to be monitored. The sensor cell may use a two or three-electrode (work, reference and counter electrodes) configuration driven by a controlled potential (potentiostat) analog circuit connected through a contact system.

The analyte sensor may be configured so that a portion thereof is placed under the skin of the patient so as to detect the analyte levels of the patient, and another portion of segment of the analyte sensor that is in communication with the transmitter unit. The transmitter unit is configured to transmit the analyte levels detected by the sensor over a wireless communication link such as an RF (radio frequency) communication link to a receiver/monitor unit. The receiver/monitor unit performs data analysis, among others on the received analyte levels to generate information pertaining to the monitored analyte levels. To provide flexibility in analyte sensor manufacturing and/or design, among others, tolerance of a larger range of the analyte sensor sensitivities for processing by the transmitter unit is desirable.

In view of the foregoing, it would be desirable to have a method and system for providing data processing and control for use in medical telemetry systems such as, for example, analyte monitoring systems.

SUMMARY

In one embodiment, a method including receiving glucose related data from an in vivo analyte sensor, determining a first filtered value associated with the received data based on a first predetermined time period and the received data, determining a second filtered value associated with the received data based on a second predetermined time period and the received data, determining a rate of change of the glucose level based at least in part on the received data, generating a weighted average value based upon the first filtered value and the second filtered value, and determining a filtered glucose value based at least in part on the weighted average value and a predetermined parameter, is disclosed.

These and other objects, features and advantages of the present disclosure will become more fully apparent from the following detailed description of the embodiments, the appended claims and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of a data monitoring and management system for practicing one or more embodiments of the present disclosure;

FIG. 2 is a block diagram of the transmitter unit of the data monitoring and management system shown in FIG. 1 in accordance with one embodiment of the present disclosure;

FIG. 3 is a block diagram of the receiver/monitor unit of the data monitoring and management system shown in FIG. 1 in accordance with one embodiment of the present disclosure;

FIGS. 4A-4B illustrate a perspective view and a cross sectional view, respectively of an analyte sensor in accordance with one embodiment of the present disclosure;

FIG. 5 is a flowchart illustrating ambient temperature compensation routine for determining on-skin temperature information in accordance with one embodiment of the present disclosure;

FIG. 6 is a flowchart illustrating digital anti-aliasing filtering routing in accordance with one embodiment of the present disclosure;

FIG. 7 is a flowchart illustrating actual or potential sensor insertion or removal detection routine in accordance with one embodiment of the present disclosure;

FIG. 11 is a flowchart illustrating a data quality verification routine in accordance with one embodiment of the present disclosure;

FIG. 12 is a flowchart illustrating a rate variance filtering routine in accordance with one embodiment of the present disclosure;

FIG. 13 is a flowchart illustrating a composite sensor sensitivity determination routine in accordance with one embodiment of the present disclosure;

FIG. 14 is a flowchart illustrating an outlier data point verification routine in accordance with one embodiment of the present disclosure;

FIG. 15 is a flowchart illustrating a sensor stability verification routine in accordance with one embodiment of the present disclosure;

FIG. 16 illustrates analyte sensor code determination in accordance with one embodiment of the present disclosure;

FIG. 17 illustrates an early user notification function associated with the analyte sensor condition in one aspect of the present disclosure;

FIG. 18 illustrates uncertainty estimation associated with glucose level rate of change determination in one aspect of the present disclosure;

FIG. 19 illustrates glucose trend determination in accordance with one embodiment of the present disclosure; and

FIG. 20 illustrates glucose trend determination in accordance with another embodiment of the present disclosure.

DETAILED DESCRIPTION

As described in further detail below, in accordance with the various embodiments of the present disclosure, there is provided a method and apparatus for providing data processing and control for use in a medical telemetry system. In particular, within the scope of the present disclosure, there are provided method and system for providing data communication and control for use in a medical telemetry system such as, for example, a continuous glucose monitoring system.

FIG. 1 illustrates a data monitoring and management system such as, for example, analyte (e.g., glucose) monitoring system 100 in accordance with one embodiment of the present disclosure. The subject invention is further described primarily with respect to a glucose monitoring system for convenience and such description is in no way intended to limit the scope of the invention. It is to be understood that the analyte monitoring system may be configured to monitor a variety of analytes, e.g., lactate, and the like.

Analytes that may be monitored include, for example, acetyl choline, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase (e.g., CK-MB), creatine, DNA, fructosamine, glucose, glutamine, growth hormones, hormones, ketones, lactate, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid stimulating hormone, and troponin. The concentration of drugs, such as, for example, antibiotics (e.g., gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs of abuse, theophylline, and warfarin, may also be monitored.

The analyte monitoring system 100 includes a sensor 101, a transmitter unit 102 coupled to the sensor 101, and a primary receiver unit 104 which is configured to communicate with the transmitter unit 102 via a communication link 103. The primary receiver unit 104 may be further configured to transmit data to a data processing terminal 105 for evaluating the data received by the primary receiver unit 104. Moreover, the data processing terminal in one embodiment may be configured to receive data directly from the transmitter unit 102 via a communication link which may optionally be configured for bi-directional communication.

Also shown in FIG. 1 is a secondary receiver unit 106 which is operatively coupled to the communication link and configured to receive data transmitted from the transmitter unit 102. Moreover, as shown in the Figure, the secondary receiver unit 106 is configured to communicate with the primary receiver unit 104 as well as the data processing terminal 105. Indeed, the secondary receiver unit 106 may be configured for bi-directional wireless communication with each of the primary receiver unit 104 and the data processing terminal 105. As discussed in further detail below, in one embodiment of the present disclosure, the secondary receiver unit 106 may be configured to include a limited number of functions and features as compared with the primary receiver unit 104. As such, the secondary receiver unit 106 may be configured substantially in a smaller compact housing or embodied in a device such as a wrist watch, for example. Alternatively, the secondary receiver unit 106 may be configured with the same or substantially similar functionality as the primary receiver unit 104, and may be configured to be used in conjunction with a docking cradle unit for placement by bedside, for night time monitoring, and/or bi-directional communication device.

Only one sensor 101, transmitter unit 102, communication link 103, and data processing terminal 105 are shown in the embodiment of the analyte monitoring system 100 illustrated in FIG. 1. However, it will be appreciated by one of ordinary skill in the art that the analyte monitoring system 100 may include one or more sensor 101, transmitter unit 102, communication link 103, and data processing terminal 105. Moreover, within the scope of the present disclosure, the analyte monitoring system 100 may be a continuous monitoring system, or semi-continuous, or a discrete monitoring system. In a multi-component environment, each device is configured to be uniquely identified by each of the other devices in the system so that communication conflict is readily resolved between the various components within the analyte monitoring system 100.

In one embodiment of the present disclosure, the sensor 101 is physically positioned in or on the body of a user whose analyte level is being monitored. The sensor 101 may be configured to continuously sample the analyte level of the user and convert the sampled analyte level into a corresponding data signal for transmission by the transmitter unit 102. In one embodiment, the transmitter unit 102 is coupled to the sensor 101 so that both devices are positioned on the user's body, with at least a portion of the analyte sensor 101 positioned transcutaneously under the skin layer of the user. The transmitter unit 102 performs data processing such as filtering and encoding on data signals, each of which corresponds to a sampled analyte level of the user, for transmission to the primary receiver unit 104 via the communication link 103.

In one embodiment, the analyte monitoring system 100 is configured as a one-way RF communication path from the transmitter unit 102 to the primary receiver unit 104. In such embodiment, the transmitter unit 102 transmits the sampled data signals received from the sensor 101 without acknowledgement from the primary receiver unit 104 that the transmitted sampled data signals have been received. For example, the transmitter unit 102 may be configured to transmit the encoded sampled data signals at a fixed rate (e.g., at one minute intervals) after the completion of the initial power on procedure. Likewise, the primary receiver unit 104 may be configured to detect such transmitted encoded sampled data signals at predetermined time intervals. Alternatively, the analyte monitoring system 100 may be configured with a bi-directional RF (or otherwise) communication between the transmitter unit 102 and the primary receiver unit 104.

Additionally, in one aspect, the primary receiver unit 104 may include two sections. The first section is an analog interface section that is configured to communicate with the transmitter unit 102 via the communication link 103. In one embodiment, the analog interface section may include an RF receiver and an antenna for receiving and amplifying the data signals from the transmitter unit 102, which are thereafter, demodulated with a local oscillator and filtered through a band-pass filter. The second section of the primary receiver unit 104 is a data processing section which is configured to process the data signals received from the transmitter unit 102 such as by performing data decoding, error detection and correction, data clock generation, and data bit recovery.

In operation, upon completing the power-on procedure, the primary receiver unit 104 is configured to detect the presence of the transmitter unit 102 within its range based on, for example, the strength of the detected data signals received from the transmitter unit 102 or a predetermined transmitter identification information. Upon successful synchronization with the corresponding transmitter unit 102, the primary receiver unit 104 is configured to begin receiving from the transmitter unit 102 data signals corresponding to the user's detected analyte level. More specifically, the primary receiver unit 104 in one embodiment is configured to perform synchronized time hopping with the corresponding synchronized transmitter unit 102 via the communication link 103 to obtain the user's detected analyte level.

Referring again to FIG. 1, the data processing terminal 105 may include a personal computer, a portable computer such as a laptop or a handheld device (e.g., personal digital assistants (PDAs)), and the like, each of which may be configured for data communication with the receiver via a wired or a wireless connection. Additionally, the data processing terminal 105 may further be connected to a data network (not shown) for storing, retrieving and updating data corresponding to the detected analyte level of the user.

Within the scope of the present disclosure, the data processing terminal 105 may include an infusion device such as an insulin infusion pump or the like, which may be configured to administer insulin to patients, and which may be configured to communicate with the receiver unit 104 for receiving, among others, the measured analyte level. Alternatively, the receiver unit 104 may be configured to integrate an infusion device therein so that the receiver unit 104 is configured to administer insulin therapy to patients, for example, for administering and modifying basal profiles, as well as for determining appropriate boluses for administration based on, among others, the detected analyte levels received from the transmitter unit 102.

Additionally, the transmitter unit 102, the primary receiver unit 104 and the data processing terminal 105 may each be configured for bi-directional wireless communication such that each of the transmitter unit 102, the primary receiver unit 104 and the data processing terminal 105 may be configured to communicate (that is, transmit data to and receive data from) with each other via the wireless communication link 103. More specifically, the data processing terminal 105 may in one embodiment be configured to receive data directly from the transmitter unit 102 via a communication link, where the communication link, as described above, may be configured for bi-directional communication.

In this embodiment, the data processing terminal 105 which may include an insulin pump, may be configured to receive the analyte signals from the transmitter unit 102, and thus, incorporate the functions of the receiver unit 104 including data processing for managing the patient's insulin therapy and analyte monitoring. In one embodiment, the communication link 103 may include one or more of an RF communication protocol, an infrared communication protocol, a Bluetooth® enabled communication protocol, an 802.11x wireless communication protocol, a Zigbee® transmission protocol, or an equivalent wireless communication protocol which would allow secure, wireless communication of several units (for example, per HIPAA requirements) while avoiding potential data collision and interference.

FIG. 2 is a block diagram of the transmitter of the data monitoring and detection system shown in FIG. 1 in accordance with one embodiment of the present disclosure. Referring to the Figure, the transmitter unit 102 in one embodiment includes an analog interface 201 configured to communicate with the sensor 101 (FIG. 1), a user input 202, and a temperature detection section 203, each of which is operatively coupled to a transmitter processor 204 such as a central processing unit (CPU).

Further shown in FIG. 2 are a transmitter serial communication section 205 and an RF transmitter 206, each of which is also operatively coupled to the transmitter processor 204. Moreover, a power supply 207 such as a battery is also provided in the transmitter unit 102 to provide the necessary power for the transmitter unit 102. Additionally, as can be seen from the Figure, clock 208 is provided to, among others, supply real time information to the transmitter processor 204.

As can be seen from FIG. 2, the sensor 101 (FIG. 1) is provided four contacts, three of which are electrodes—work electrode (W) 210, guard contact (G) 211, reference electrode (R) 212, and counter electrode (C) 213, each operatively coupled to the analog interface 201 of the transmitter unit 102. In one embodiment, each of the work electrode (W) 210, guard contact (G) 211, reference electrode (R) 212, and counter electrode (C) 213 may be made using a conductive material that is either printed or etched, for example, such as carbon which may be printed, or metal foil (e.g., gold) which may be etched, or alternatively provided on a substrate material using laser or photolithography.

In one embodiment, a unidirectional input path is established from the sensor 101 (FIG. 1) and/or manufacturing and testing equipment to the analog interface 201 of the transmitter unit 102, while a unidirectional output is established from the output of the RF transmitter 206 of the transmitter unit 102 for transmission to the primary receiver unit 104. In this manner, a data path is shown in FIG. 2 between the aforementioned unidirectional input and output via a dedicated link 209 from the analog interface 201 to serial communication section 205, thereafter to the processor 204, and then to the RF transmitter 206. As such, in one embodiment, via the data path described above, the transmitter unit 102 is configured to transmit to the primary receiver unit 104 (FIG. 1), via the communication link 103 (FIG. 1), processed and encoded data signals received from the sensor 101 (FIG. 1). Additionally, the unidirectional communication data path between the analog interface 201 and the RF transmitter 206 discussed above allows for the configuration of the transmitter unit 102 for operation upon completion of the manufacturing process as well as for direct communication for diagnostic and testing purposes.

As discussed above, the transmitter processor 204 is configured to transmit control signals to the various sections of the transmitter unit 102 during the operation of the transmitter unit 102. In one embodiment, the transmitter processor 204 also includes a memory (not shown) for storing data such as the identification information for the transmitter unit 102, as well as the data signals received from the sensor 101. The stored information may be retrieved and processed for transmission to the primary receiver unit 104 under the control of the transmitter processor 204. Furthermore, the power supply 207 may include a commercially available battery.

The transmitter unit 102 is also configured such that the power supply section 207 is capable of providing power to the transmitter for a minimum of about three months of continuous operation after having been stored for about eighteen months in a low-power (non-operating) mode. In one embodiment, this may be achieved by the transmitter processor 204 operating in low power modes in the non-operating state, for example, drawing no more than approximately 1 μA of current. Indeed, in one embodiment, the final step during the manufacturing process of the transmitter unit 102 may place the transmitter unit 102 in the lower power, non-operating state (i.e., post-manufacture sleep mode). In this manner, the shelf life of the transmitter unit 102 may be significantly improved. Moreover, as shown in FIG. 2, while the power supply unit 207 is shown as coupled to the processor 204, and as such, the processor 204 is configured to provide control of the power supply unit 207, it should be noted that within the scope of the present disclosure, the power supply unit 207 is configured to provide the necessary power to each of the components of the transmitter unit 102 shown in FIG. 2.

Referring back to FIG. 2, the power supply section 207 of the transmitter unit 102 in one embodiment may include a rechargeable battery unit that may be recharged by a separate power supply recharging unit (for example, provided in the receiver unit 104) so that the transmitter unit 102 may be powered for a longer period of usage time. Moreover, in one embodiment, the transmitter unit 102 may be configured without a battery in the power supply section 207, in which case the transmitter unit 102 may be configured to receive power from an external power supply source (for example, a battery) as discussed in further detail below.

Referring yet again to FIG. 2, the temperature detection section 203 of the transmitter unit 102 is configured to monitor the temperature of the skin near the sensor insertion site. The temperature reading is used to adjust the analyte readings obtained from the analog interface 201. The RF transmitter 206 of the transmitter unit 102 may be configured for operation in the frequency band of 315 MHz to 322 MHz, for example, in the United States. Further, in one embodiment, the RF transmitter 206 is configured to modulate the carrier frequency by performing Frequency Shift Keying and Manchester encoding. In one embodiment, the data transmission rate is 19,200 symbols per second, with a minimum transmission range for communication with the primary receiver unit 104.

Referring yet again to FIG. 2, also shown is a leak detection circuit 214 coupled to the guard contact (G) 211 and the processor 204 in the transmitter unit 102 of the data monitoring and management system 100. The leak detection circuit 214 in accordance with one embodiment of the present disclosure may be configured to detect leakage current in the sensor 101 to determine whether the measured sensor data are corrupt or whether the measured data from the sensor 101 is accurate.

FIG. 3 is a block diagram of the receiver/monitor unit of the data monitoring and management system shown in FIG. 1 in accordance with one embodiment of the present disclosure. Referring to FIG. 3, the primary receiver unit 104 includes a blood glucose test strip interface 301, an RF receiver 302, an input 303, a temperature detection section 304, and a clock 305, each of which is operatively coupled to a receiver processor 307. As can be further seen from the Figure, the primary receiver unit 104 also includes a power supply 306 operatively coupled to a power conversion and monitoring section 308. Further, the power conversion and monitoring section 308 is also coupled to the receiver processor 307. Moreover, also shown are a receiver serial communication section 309, and an output 310, each operatively coupled to the receiver processor 307.

In one embodiment, the test strip interface 301 includes a glucose level testing portion to receive a manual insertion of a glucose test strip, and thereby determine and display the glucose level of the test strip on the output 310 of the primary receiver unit 104. This manual testing of glucose can be used to calibrate sensor 101. The RF receiver 302 is configured to communicate, via the communication link 103 (FIG. 1) with the RF transmitter 206 of the transmitter unit 102, to receive encoded data signals from the transmitter unit 102 for, among others, signal mixing, demodulation, and other data processing. The input 303 of the primary receiver unit 104 is configured to allow the user to enter information into the primary receiver unit 104 as needed. In one aspect, the input 303 may include one or more keys of a keypad, a touch-sensitive screen, or a voice-activated input command unit. The temperature detection section 304 is configured to provide temperature information of the primary receiver unit 104 to the receiver processor 307, while the clock 305 provides, among others, real time information to the receiver processor 307.

Each of the various components of the primary receiver unit 104 shown in FIG. 3 is powered by the power supply 306 which, in one embodiment, includes a battery. Furthermore, the power conversion and monitoring section 308 is configured to monitor the power usage by the various components in the primary receiver unit 104 for effective power management and to alert the user, for example, in the event of power usage which renders the primary receiver unit 104 in sub-optimal operating conditions. An example of such sub-optimal operating condition may include, for example, operating the vibration output mode (as discussed below) for a period of time thus substantially draining the power supply 306 while the processor 307 (thus, the primary receiver unit 104) is turned on. Moreover, the power conversion and monitoring section 308 may additionally be configured to include a reverse polarity protection circuit such as a field effect transistor (FET) configured as a battery activated switch.

The serial communication section 309 in the primary receiver unit 104 is configured to provide a bi-directional communication path from the testing and/or manufacturing equipment for, among others, initialization, testing, and configuration of the primary receiver unit 104. Serial communication section 309 can also be used to upload data to a computer, such as time-stamped blood glucose data. The communication link with an external device (not shown) can be made, for example, by cable, infrared (IR) or RF link. The output 310 of the primary receiver unit 104 is configured to provide, among others, a graphical user interface (GUI) such as a liquid crystal display (LCD) for displaying information. Additionally, the output 310 may also include an integrated speaker for outputting audible signals as well as to provide vibration output as commonly found in handheld electronic devices, such as mobile telephones presently available. In a further embodiment, the primary receiver unit 104 also includes an electro-luminescent lamp configured to provide backlighting to the output 310 for output visual display in dark ambient surroundings.

Referring back to FIG. 3, the primary receiver unit 104 in one embodiment may also include a storage section such as a programmable, non-volatile memory device as part of the processor 307, or provided separately in the primary receiver unit 104, operatively coupled to the processor 307. The processor 307 is further configured to perform Manchester decoding as well as error detection and correction upon the encoded data signals received from the transmitter unit 102 via the communication link 103.

In a further embodiment, the one or more of the transmitter unit 102, the primary receiver unit 104, secondary receiver unit 106, or the data processing terminal/infusion section 105 may be configured to receive the blood glucose value wirelessly over a communication link from, for example, a glucose meter. In still a further embodiment, the user or patient manipulating or using the analyte monitoring system 100 (FIG. 1) may manually input the blood glucose value using, for example, a user interface (for example, a keyboard, keypad, and the like) incorporated in the one or more of the transmitter unit 102, the primary receiver unit 104, secondary receiver unit 106, or the data processing terminal/infusion section 105.

Additional detailed description of the continuous analyte monitoring system, its various components including the functional descriptions of the transmitter are provided in U.S. Pat. No. 6,175,752 issued Jan. 16, 2001 entitled “Analyte Monitoring Device and Methods of Use”, and in U.S. application Ser. No. 10/745,878 filed Dec. 26, 2003, now U.S. Pat. No. 7,811,231, entitled “Continuous Glucose Monitoring System and Methods of Use”, each assigned to the Assignee of the present application, and each of which are incorporated herein by reference for all purposes.

FIGS. 4A-4B illustrate a perspective view and a cross sectional view, respectively of an analyte sensor in accordance with one embodiment of the present disclosure. Referring to FIG. 4A, a perspective view of a sensor 400, the major portion of which is above the surface of the skin 410, with an insertion tip 430 penetrating through the skin and into the subcutaneous space 420 in contact with the user's biofluid such as interstitial fluid. Contact portions of a working electrode 401, a reference electrode 402, and a counter electrode 403 can be seen on the portion of the sensor 400 situated above the skin surface 410. Working electrode 401, a reference electrode 402, and a counter electrode 403 can be seen at the end of the insertion tip 430.

Referring now to FIG. 4B, a cross sectional view of the sensor 400 in one embodiment is shown. In particular, it can be seen that the various electrodes of the sensor 400 as well as the substrate and the dielectric layers are provided in a stacked or layered configuration or construction. For example, as shown in FIG. 4B, in one aspect, the sensor 400 (such as the sensor 101FIG. 1), includes a substrate layer 404, and a first conducting layer 401 such as a carbon trace disposed on at least a portion of the substrate layer 404, and which may comprise the working electrode. Also shown disposed on at least a portion of the first conducting layer 401 is a sensing layer 408.

Referring back to FIG. 4B, a first insulation layer such as a first dielectric layer 405 is disposed or stacked on at least a portion of the first conducting layer 401, and further, a second conducting layer 409 such as another carbon trace may be disposed or stacked on top of at least a portion of the first insulation layer (or dielectric layer) 405. As shown in FIG. 4B, the second conducting layer 409 may comprise the reference electrode 402, and in one aspect, may include a layer of silver/silver chloride (Ag/AgCl).

Referring still again to FIG. 4B, a second insulation layer 406 such as a dielectric layer in one embodiment may be disposed or stacked on at least a portion of the second conducting layer 409. Further, a third conducting layer 403 which may include carbon trace and that may comprise the counter electrode 403 may in one embodiment be disposed on at least a portion of the second insulation layer 406. Finally, a third insulation layer 407 is disposed or stacked on at least a portion of the third conducting layer 403. In this manner, the sensor 400 may be configured in a stacked or layered construction or configuration such that at least a portion of each of the conducting layers is separated by a respective insulation layer (for example, a dielectric layer).

Additionally, within the scope of the present disclosure, some or all of the electrodes 401, 402, 403 may be provided on the same side of the substrate 404 in a stacked construction as described above, or alternatively, may be provided in a co-planar manner such that each electrode is disposed on the same plane on the substrate 404, however, with a dielectric material or insulation material disposed between the conducting layers/electrodes. Furthermore, in still another aspect of the present disclosure, the one or more conducting layers such as the electrodes 401, 402, 403 may be disposed on opposing sides of the substrate 404.

Referring back to the Figures, in one embodiment, the transmitter unit 102 (FIG. 1) is configured to detect the current signal from the sensor 101 (FIG. 1) and the skin temperature near the sensor 101, which are preprocessed by, for example, the transmitter processor 204 (FIG. 2) and transmitted to the receiver unit (for example, the primary receiver unit 104 (FIG. 1)) periodically at a predetermined time interval, such as for example, but not limited to, once per minute, once every two minutes, once every five minutes, or once every ten minutes. Additionally, the transmitter unit 102 may be configured to perform sensor insertion detection and data quality analysis, information pertaining to which are also transmitted to the receiver unit 104 periodically at the predetermined time interval. In turn, the receiver unit 104 may be configured to perform, for example, skin temperature compensation as well as calibration of the sensor data received from the transmitter unit 102.

For example, in one aspect, the transmitter unit 102 may be configured to oversample the sensor signal at a nominal rate of four samples per second, which allows the analyte anti-aliasing filter in the transmitter unit 102 to attenuate noise (for example, due to effects resulting from motion or movement of the sensor after placement) at frequencies above 2 Hz. More specifically, in one embodiment, the transmitter processor 204 may be configured to include a digital filter to reduce aliasing noise when decimating the four Hz sampled sensor data to once per minute samples for transmission to the receiver unit 104. As discussed in further detail below, in one aspect, a two stage Kaiser FIR filter may be used to perform the digital filtering for anti-aliasing. While Kaiser FIR filter may be used for digital filtering of the sensor signals, within the scope of the present disclosure, other suitable filters may be used to filter the sensor signals.

In one aspect, the temperature measurement section 203 of the transmitter unit 102 may be configured to measure once per minute the on skin temperature near the analyte sensor at the end of the minute sampling cycle of the sensor signal. Within the scope of the present disclosure, different sample rates may be used which may include, for example, but not limited to, measuring the on skin temperature for each 30 second periods, each two minute periods, and the like. Additionally, as discussed above, the transmitter unit 102 may be configured to detect sensor insertion, sensor signal settling after sensor insertion, and sensor removal, in addition to detecting for sensor—transmitter system failure modes and sensor signal data integrity. Again, this information is transmitted periodically by the transmitter unit 102 to the receiver unit 104 along with the sampled sensor signals at the predetermined time intervals.

Referring again to the Figures, as the analyte sensor measurements are affected by the temperature of the tissue around the transcutaneously positioned sensor 101, in one aspect, compensation of the temperature variations and affects on the sensor signals are provided for determining the corresponding glucose value. Moreover, the ambient temperature around the sensor 101 may affect the accuracy of the on skin temperature measurement and ultimately the glucose value determined from the sensor signals. Accordingly, in one aspect, a second temperature sensor is provided in the transmitter unit 102 away from the on skin temperature sensor (for example, physically away from the temperature measurement section 203 of the transmitter unit 102), so as to provide compensation or correction of the on skin temperature measurements due to the ambient temperature effects. In this manner, the accuracy of the estimated glucose value corresponding to the sensor signals may be attained.

In one aspect, the processor 204 of the transmitter unit 102 may be configured to include the second temperature sensor, which is located closer to the ambient thermal source within the transmitter unit 102. In other embodiments, the second temperature sensor may be located at a different location within the transmitter unit 102 housing where the ambient temperature within the housing of the transmitter unit 102 may be accurately determined.

Referring now to FIG. 5, in one aspect, an ambient temperature compensation routine for determining the on-skin temperature level for use in the glucose estimation determination based on the signals received from the sensor 101. Referring to FIG. 5, for each sampled signal from the sensor 101, a corresponding measured temperature information is received (510), for example, by the processor 204 from the temperature measurement section 203 (which may include, for example, a thermistor provided in the transmitter unit 102). In addition, a second temperature measurement is obtained (520), for example, including a determination of the ambient temperature level using a second temperature sensor provided within the housing of the transmitter unit 102.

In one aspect, based on a predetermined ratio of thermal resistances between the temperature measurement section 203 and the second temperature sensor (located, for example, within the processor 204 of the transmitter unit 102), and between the temperature measurement section 203 and the skin layer on which the transmitter unit 102 is placed and coupled to the sensor 101, ambient temperature compensation may be performed (530), to determine the corresponding ambient temperature compensated on skin temperature level (540). In one embodiment, the predetermined ratio of the thermal resistances may be approximately 0.2. However, within the scope of the present disclosure, this thermal resistance ratio may vary according to the design of the system, for example, based on the size of the transmitter unit 102 housing, the location of the second temperature sensor within the housing of the transmitter unit 102, and the like.

With the ambient temperature compensated on-skin temperature information, the corresponding glucose value from the sampled analyte sensor signal may be determined.

Referring again to FIG. 2, the processor 204 of the transmitter unit 102 may include a digital anti-aliasing filter. Using analog anti-aliasing filters for a one minute measurement data sample rate would require a large capacitor in the transmitter unit 102 design, and which in turn impacts the size of the transmitter unit 102. As such, in one aspect, the sensor signals may be oversampled (for example, at a rate of 4 times per second), then the data is digitally decimated to derive a one-minute sample rate.

As discussed above, in one aspect, the digital anti-aliasing filter may be used to remove, for example, signal artifacts or otherwise undesirable aliasing effects on the sampled digital signals received from the analog interface 201 of the transmitter unit 102. For example, in one aspect, the digital anti-aliasing filter may be used to accommodate decimation of the sensor data from approximately four Hz samples to one-minute samples. In one aspect, a two stage FIR filter may be used for the digital anti-aliasing filter, which includes improved response time, pass band and stop band properties.

Referring to FIG. 6, a routine for digital anti-aliasing filtering is shown in accordance with one embodiment. As shown, in one embodiment, at each predetermined time period such as every minute, the analog signal from the analog interface 201 corresponding to the monitored analyte level received from the sensor 101 (FIG. 1) is sampled (610). For example, at every minute, in one embodiment, the signal from the analog interface 201 is over-sampled at approximately 4 Hz. Thereafter, the first stage digital filtering on the over-sampled data is performed (620), where, for example, a ⅙ down-sampling from 246 samples to 41 samples is performed, and the resulting 41 samples is further down-sampled at the second stage digital filtering (630) such that, for example, a 1/41 down-sampling is performed from 41 samples (from the first stage digital filtering), to a single sample. Thereafter, the filter is reset (640), and the routine returns to the beginning for the next minute signal received from the analog interface 201.

While the use of FIR filter, and in particular the use of Kaiser FIR filter, is within the scope of the present disclosure, other suitable filters, such as FIR filters with different weighting schemes or IIR filters, may be used.

Referring yet again to the Figures, the transmitter unit 102 may be configured in one embodiment to periodically perform data quality checks including error condition verifications and potential error condition detections, and also to transmit the relevant information related to one or more data quality, error condition or potential error condition detection to the receiver unit 104 with the transmission of the monitored sensor data. For example, in one aspect, a state machine may be used in conjunction with the transmitter unit 102 and which may be configured to be updated four times per second, the results of which are transmitted to the receiver unit 104 every minute.

In particular, using the state machine, the transmitter unit 102 may be configured to detect one or more states that may indicate when a sensor is inserted, when a sensor is removed from the user, and further, may additionally be configured to perform related data quality checks so as to determine when a new sensor has been inserted or transcutaneously positioned under the skin layer of the user and has settled in the inserted state such that the data transmitted from the transmitter unit 102 does not compromise the integrity of signal processing performed by the receiver unit 104 due to, for example, signal transients resulting from the sensor insertion.

That is, when the transmitter unit 102 detects low or no signal from the sensor 101, which is followed by detected signals from the sensor 101 that is above a given signal, the processor 204 may be configured to identify such transition in monitored signal levels and associate with a potential sensor insertion state. Alternatively, the transmitter unit 102 may be configured to detect the signal level above another predetermined threshold level, which is followed by the detection of the signal level from the sensor 101 that falls below the predetermined threshold level. In such a case, the processor 204 may be configured to associate or identify such transition or condition in the monitored signal levels as a potential sensor removal state.

Accordingly, when either the potential sensor insertion state or potential sensor removal state is detected by the transmitter unit 102, this information is transmitted to the receiver unit 104, and in turn, the receiver unit may be configured to prompt the user for confirmation of either of the detected potential sensor related state. In another aspect, the sensor insertion state or potential sensor removal state may be detected or determined by the receiver unit based on one or more signals received from the transmitter unit 102. For example, similar to an alarm condition or a notification to the user, the receiver unit 104 may be configured to display a request or a prompt on the display or an output unit of the receiver unit 104 a text and/or other suitable notification message to inform the user to confirm the state of the sensor 101.

For example, the receiver unit 104 may be configured to display the following message: “New Sensor Inserted?” or a similar notification in the case where the receiver unit 104 receives one or more signals from the transmitter unit 102 associated with the detection of the signal level below the predetermined threshold level for the predefined period of time, followed by the detection of the signal level from the sensor 101 above another predetermined threshold level for another predefined period of time. Additionally, the receiver unit 104 may be configured to display the following message: “Sensor Removed?” or a similar notification in the case where the receiver unit 104 received one or more signals from the transmitter unit 102 associated with the detection of the signal level from the sensor 101 that is above another predetermined threshold level for another predefined period of time, which is followed by the detection of the signal level from the sensor 101 that falls below the predetermined threshold level for the predefined period of time.

Based on the user confirmation received, the receiver unit 104 may be further configured to execute or perform additional related processing and routines in response to the user confirmation or acknowledgement. For example, when the user confirms, using the user interface input/output mechanism of the receiver unit 104, for example, that a new sensor has been inserted, the receiver unit 104 may be configured to initiate a new sensor insertion related routines including, such as, for example, sensor calibration routine including, for example, calibration timer, sensor expiration timer and the like. Alternatively, when the user confirms or it is determined that the sensor 101 is not properly positioned or otherwise removed from the insertion site, the receiver unit 104 may be accordingly configured to perform related functions such as, for example, stop displaying of the glucose values/levels, or deactivating the alarm monitoring conditions.

On the other hand, in response to the potential sensor insertion notification generated by the receiver unit 104, if the user confirms that no new sensor has been inserted, then the receiver unit 104 in one embodiment is configured to assume that the sensor 101 is in acceptable operational state, and continues to receive and process signals from the transmitter unit 102.

In this manner, in cases, for example, when there is momentary movement or temporary dislodging of the sensor 101 from the initially positioned transcutaneous state, or when one or more of the contact points between sensor 101 and the transmitter unit 102 are temporarily disconnected, but otherwise, the sensor 101 is operational and within its useful life, the routine above provides an option to the user to maintain the usage of the sensor 101, without replacing the sensor 101 prior to the expiration of its useful life. In this manner, in one aspect, false positive indications of sensor 101 failure may be identified and addressed.

For example, FIG. 7 is a flowchart illustrating actual or potential sensor insertion or removal detection routine in accordance with one embodiment of the present disclosure. Referring to the Figure, the current analyte related signal is first compared to a predetermined signal characteristic (710). In one aspect, the predetermined signal characteristic may include one of a signal level transition from below a first predetermined level (for example, but not limited to 18, ADC (analog to digital converter) counts) to above the first predetermined level, a signal level transition from above a second predetermined level (for example, but not limited to, 9 ADC counts) to below the second predetermined level, a transition from below a predetermined signal rate of change threshold to above the predetermined signal rate of change threshold, and a transition from above the predetermined signal rate of change threshold to below the predetermined signal rate of change threshold.

In this manner, in one aspect of the present disclosure, based on a transition state of the received analyte related signals, it may be possible to determine the state of the analyte sensor (720), and based on which, the user or the patient to confirm whether the analyte sensor is in the desired or proper position, has been temporarily dislocated, or otherwise, removed from the desired insertion site so as to require a new analyte sensor.

In this manner, in one aspect, when it is determined that the monitored signal from the sensor 101 crosses a transition level (730) (for example, from no or low signal level to a high signal level, or vice versa), the transmitter unit 102 may be configured to generate an appropriate output data associated with the sensor signal transition (740), for transmission to the receiver unit 104 (FIG. 1). Additionally, as discussed in further detail below, in another embodiment, the determination of whether the sensor 101 has crossed a transition level (730) may be determined by the receiver/monitor unit 104/106 based, at least in part on the one or more signals received from the transmitter unit 102.

FIG. 8 is a flowchart illustrating receiver unit processing corresponding to the actual or potential sensor insertion or removal detection routine of FIG. 7 in accordance with one embodiment of the present disclosure. Referring now to FIG. 8, when the receiver unit 104 receives the generated output data from the transmitter unit 102 (810), a corresponding operation state is associated with the received output data (820), for example, related to the operational state of the sensor 101. Moreover, a notification associated with the sensor operation state is generated and output to the user on the display unit or any other suitable output segment of the receiver unit 104 (830). When a user input signal is received in response to the notification associated with the sensor state operation state (840), the receiver unit 104 is configured to execute one or more routines associated with the received user input signal (850).

That is, as discussed above, in one aspect, if the user confirms that the sensor 101 has been removed, the receiver unit 104 may be configured to terminate or deactivate alarm monitoring and glucose displaying functions. On the other hand, if the user confirms that a new sensor 101 has been positioned or inserted into the user, then the receiver unit 104 may be configured to initiate or execute routines associated with the new sensor insertion, such as, for example, calibration procedures, establishing calibration timer, and establishing sensor expiration timer.

In a further embodiment, based on the detected or monitored signal transition, the receiver/monitor unit may be configured to determine the corresponding sensor state without relying upon the user input or confirmation signal associated with whether the sensor is dislocated or removed from the insertion site, or otherwise, operating properly.

FIG. 9 is a flowchart illustrating data processing corresponding to the actual or potential sensor insertion or removal detection routine in accordance with another embodiment of the present disclosure. Referring to FIG. 9, a current analyte related signal is received and compared to a predetermined signal characteristic (910). Thereafter, an operational state associated with an analyte monitoring device such as, for example, the sensor 101 (FIG. 1) is retrieved (920) from a storage unit or otherwise resident in, for example, a memory of the receiver/monitor unit. Additionally, a prior analyte related signal is also retrieved from the storage unit, and compared to the current analyte related signal received (930). An output data is generated which is associated with the operational state (940), and which at least in part is based on the one or more of the received current analyte related signal and the retrieved prior analyte related signal.

Referring again to FIG. 9, when the output data is generated, a corresponding user input command or signal is received in response to the generated and output data (950), which may include one or more of a confirmation, verification, or rejection of the operational state related to the analyte monitoring device.

FIG. 10 is a flowchart illustrating a concurrent passive notification routine in the data receiver/monitor unit of the data monitoring and management system of FIG. 1 in accordance with one embodiment of the present disclosure. Referring to FIG. 10, a predetermined routine is executed for a predetermined time period to completion (1010). During the execution of the predetermined routine, an alarm condition is detected (1020), and when the alarm or alert condition is detected, a first indication associated with the detected alarm or alert condition is output concurrent to the execution of the predetermined routine (1030).

That is, in one embodiment, when a predefined routine is being executed, and an alarm or alert condition is detected, a notification is provided to the user or patient associated with the detected alarm or alert condition, which does not interrupt or otherwise disrupt the execution of the predefined routine. Referring back to FIG. 10, upon termination of the predetermined routine, another output or second indication associated with the detected alarm condition is output or displayed (1040).

More specifically, in one aspect, the user interface notification feature associated with the detected alarm condition is output to the user only upon the completion of an ongoing routine which was in the process of being executed when the alarm condition is detected. As discussed above, when such alarm condition is detected during the execution of a predetermined routine, a temporary alarm notification such as, for example, a backlight indicator, a text output on the user interface display or any other suitable output indication may be provided to alert the user or the patient of the detected alarm condition substantially in real time, but which does not disrupt an ongoing routine.

Within the scope of the present disclosure, the ongoing routine or the predetermined routine being executed may include one or more of performing a finger stick blood glucose test (for example, for purposes of periodically calibrating the sensor 101), or any other processes that interface with the user interface, for example, on the receiver/monitor unit 104/106 (FIG. 1) including, but not limited to, the configuration of device settings, review of historical data such as glucose data, alarms, events, entries in the data log, visual displays of data including graphs, lists, and plots, data communication management including RF communication administration, data transfer to the data processing terminal 105 (FIG. 1), or viewing one or more alarm conditions with a different priority in a preprogrammed or determined alarm or notification hierarchy structure.

In this manner, in one aspect of the present disclosure, the detection of one or more alarm conditions may be presented or notified to the user or the patient, without interrupting or disrupting an ongoing routine or process in, for example, the receiver/monitor unit 104/106 of the data monitoring and management system 100 (FIG. 1).

Referring now back to the Figures, FIG. 11 is a flowchart illustrating a data quality verification routine in accordance with one embodiment of the present disclosure. Referring to FIG. 11, initially the data quality status flags are cleared or initialized or reset (1110). Thereafter data quality checks or verifications are performed, for example, as described above (1120). Thereafter, data quality flag is generated and associated with the data packet when data quality check has failed (1130). In one aspect, the generated data quality flag may be based on data quality verification such that when the underlying condition being verified is determined to be acceptable, the data quality flag may return a value of zero (or one or more predetermined value). Alternatively, in the case where the underlying condition being verified is determined to be not within the acceptable criteria (or above the acceptable level), the associated data quality flag may return a value of one (or one or more predetermined value associated with the determination of such condition).

Referring to FIG. 11, the data packet including the raw glucose data as well as the data quality flags are transmitted, for example, to the receiver/monitor unit 104/106 for further processing (1140). As described above, the data quality checks may be performed in the transmitter unit 102 (FIG. 1) and/or in the receiver/monitor unit 104/106 in the data monitoring and management system 100 (FIG. 1) in one aspect of the present disclosure.

FIG. 12 is a flowchart illustrating a rate variance filtering routine in accordance with one embodiment of the present disclosure. Referring to FIG. 12, when glucose related data is detected or received (1210), for example, for each predetermined time interval such as every minute, every five minutes, or any other suitable time intervals, a plurality of filtered values based on the received or detected glucose related data is determined (1220). For example, as discussed above, in one aspect, using, for example, an FIR filter, or based on a weighted average, a plurality of filtered values for a 15 minute and two minute glucose related data including the currently received or detected glucose related are determined.

Referring back to FIG. 12, weighting associated with the plurality of filtered values is determined (1230). Thereafter, a rate of change of the glucose level based in part on the detected or received glucose related data is determined as well as a standard deviation of the rate of change based on the glucose related data (1240). Further, a weighted average associated with the current detected or monitored glucose related data is determined based on the plurality of filtered values and the determined standard deviation of the rate of change and/or the rate of change of the glucose level (1250). For example, when the rate of change is determined to be high relative to the rate of change variation, the filtered value based on the two minute data is weighted more heavily. On the other hand, when the rate of change is determined to be low relative to the rate of change variation, the filtered glucose related data includes one of the plurality of filtered values based on the 15 minute data which is weighted more heavily. In this manner, in one aspect, there is provided a rate variance filtering approach which may be configured to dynamically modify the weighting function or data filtering to, for example, reduce undesirable variation in glucose related signals due to factors such as noise.

FIG. 13 is a flowchart illustrating a composite sensor sensitivity determination routine in accordance with one embodiment of the present disclosure. Referring to FIG. 13, during scheduled calibration time periods or otherwise manual calibration routines to calibrate the analyte sensor, when a current blood glucose value is received or detected (1310), a current or present sensitivity is determined based on the detected blood glucose value (1320). For example, the current sensitivity may be determined by taking a ratio of the current glucose sensor value and the detected blood glucose value.

Referring to FIG. 13, a prior sensitivity previously determined is retrieved, for example, from the storage unit (1330). In one aspect, the prior sensitivity may include a previous sensitivity determined during a prior sensor calibration event, or may be based on the nominal sensor sensitivity based on the sensor code from manufacturing, for example. Returning again to FIG. 13, a first weighted parameter is applied to the current sensitivity, and a second weighted parameter is applied to the retrieved prior sensitivity (1340). For example, based on the time lapsed between the calibration event associated with the retrieved prior sensitivity value and the current calibration event (associated with the current or received blood glucose value), the first and second weighted parameters may be modified (e.g., increased or decreased in value) to improve accuracy.

Referring back to FIG. 13, based on applying the first and the second weighted parameters to the current sensitivity and the retrieved prior sensitivity, a composite sensitivity associated with the analyte sensor for the current calibration event is determined (1350). For example, using a time based approach, in one embodiment, the sensitivity associated with the analyte sensor for calibration may be determined to, for example, reduce calibration errors or accommodate sensitivity drift.

FIG. 14 is a flowchart illustrating an outlier data point verification routine in accordance with one embodiment of the present disclosure. Referring to FIG. 14, and as discussed in detail above, in determining composite sensitivity associated with the analyte sensor calibration, in one aspect, an outlier data point may be detected and accordingly corrected. For example, in one aspect, two successive sensitivities associated with two successive calibration events for the analyte sensor is compared (1410). If it is determined that the comparison between the two sensitivities are within a predetermined range (1420), the composite sensitivity for the current calibration of the analyte sensor is determined based on the two successive sensitivity values (1430), using, for example, the weighted approach described above.

Referring back to FIG. 14, if it is determined that the comparison of the two successive sensitivities results in the compared value being outside of the predetermined range, then the user may be prompted to enter or provide a new current blood glucose value (for example, using a blood glucose meter) (1440). Based on the new blood glucose value received, an updated or new sensitivity associated with the analyte sensor is determined (1450). Thereafter, the new or updated sensitivity determined is compared with the two prior sensitivities compared (at 1420) to determine whether the new or updated sensitivity is within a predefined range of either of the two prior sensitivities (1460). If it is determined that the new or updated sensitivity of the analyte sensor is within the predefined range of either of the two prior successive sensitivities, a composite sensitivity is determined based on the new or updated sensitivity and one of the two prior successive sensitivities within the defined range of which the new or updated sensitivity is determined (1470). On the other hand, if it is determined that the new or updated sensitivity is not within the predefined range of either of the two prior sensitivities, then the routine repeats and prompts the user to enter a new blood glucose value (1440).

FIG. 15 is a flowchart illustrating a sensor stability verification routine in accordance with one embodiment of the present disclosure. Referring to FIG. 15, and as discussed above, between predetermined or scheduled baseline calibration events to calibrate the sensor, the analyte sensor sensitivity stability may be verified, to determine, for example, if additional stability calibrations may be needed prior to the subsequent scheduled baseline calibration event.

For example, referring to FIG. 15, in one embodiment, after the second baseline calibration event to calibrate the analyte sensor, the user may be prompted to provide a new blood glucose value. With the current blood glucose value received (1510), the current sensor sensitivity is determined (1520). Thereafter, the most recent stored sensor sensitivity value from prior calibration event is retrieved (for example, from a storage unit) (1530), and the determined current sensor sensitivity is compared with the retrieved stored sensor sensitivity value to determine whether the difference, if any, between the two sensitivity values are within a predefined range (1540).

Referring back to FIG. 15, if it is determined that the difference between the current and retrieved sensitivity values are within the predefined range, then the stability associated with the sensor sensitivity is confirmed (1550), and no additional calibration is required prior to the subsequent scheduled baseline calibration event. On the other hand, if it is determined that the difference between the current sensitivity and the retrieved prior sensitivity is not within the predefined range, then after a predetermined time period has lapsed (1560), the routine returns to the beginning and prompts the user to enter a new blood glucose value to perform the stability verification routine.

In this manner, in one aspect, the stability checks may be performed after the outlier check is performed, and a new composite sensitivity determined as described above. Accordingly, in one aspect, analyte sensor sensitivity may be monitored as the sensitivity attenuation is dissipating to, among others, improve accuracy of the monitored glucose data and sensor stability.

FIG. 16 illustrates analyte sensor code determination in accordance with one embodiment. Referring to the Figure, a batch of predetermined number of analyte sensors, for example, glucose sensors, is selected during manufacturing process (1610). The batch of predetermined number of glucose sensors may be a set number, or a variable number depending upon other manufacturing or post-manufacturing parameters (for example, such as testing, quality control verification, or packaging).

Referring to FIG. 16, the sensitivity of each selected glucose sensor is determined (1620). For example, in one aspect, in vitro sensitivity determination is performed for each selected glucose sensor to determine the corresponding sensitivity. Thereafter, a variation between the determined sensitivity of each glucose sensor is determined (1630). That is, in one aspect, the determined in vitro sensitivity associated with each selected glucose sensor is compared to a predefined variation tolerance level (1640).

In one aspect, if the variation of the sensitivity is greater than the predefined variation tolerance level for one of the selected glucose sensor in the selected batch of predetermined number of glucose sensors (1660), then the entire batch or lot may be rejected and not used. In another aspect, the rejection of the selected batch of predetermined number of glucose sensors may be based on a predetermined number of sensors within the selected batch that are associated with a sensitivity value that exceeds the predefined variation tolerance level. For example, in a batch of 30 glucose sensors, if 10 percent (or 3 sensors) has sensitivity that exceeds the predefined variation tolerance level, then the entire batch of 30 glucose sensors is rejected and not further processed during the manufacturing routine, for example, for use. Within the scope of the present disclosure, the number of sensors in the selected batch, or the number of sensors within the selected batch that exceeds the predefined variation tolerance level to result in a failed batch may be varied depending upon, for example, but not limited to, sensor manufacturing process, sensor testing routines, quality control verification, or other parameters associated with sensor performance integrity.

Referring back to FIG. 16, if it is determined that the sensitivity of the selected glucose sensors are within the predefined variation tolerance level, a nominal sensitivity is determined for the batch of the predetermined number of glucose sensors (1650). Further, a sensor code is associated with the determined nominal sensitivity for the batch of predetermined number of analyte sensors (1670).

In one aspect, the sensor code may be provided on the labeling for the batch of glucose sensors for use by the patient or the user. For example, in one aspect, the analyte monitoring system may prompt the user to enter the sensor code into the system (for example, to the receiver unit 104/106FIG. 1) after the sensor has been initially positioned in the patient and prior to the first sensor calibration event. In a further aspect, based on the sensor code, the analyte monitoring system may be configured to retrieve the nominal sensitivity associated with the batch of predetermined number of sensors for, for example, calibration of the transcutaneously positioned glucose sensor.

FIG. 17 illustrates an early user notification function associated with the analyte sensor condition in one aspect of the present disclosure. Referring to FIG. 17, upon detection of the sensor insertion (1710), for example, in fluid contact with the patient or user's analyte (e.g., interstitial fluid), one or more adverse data condition occurrence associated with the patient or the user's analyte level is monitored (1720). Examples of the adverse data condition occurrence may include, for example, a persistent low sensor signal (for example, continuous for a predefined time period), identified data quality flags or identifiers associated with erroneous or potentially inaccurate sensor signal level or sensor condition (for example, dislodged or improperly positioned sensor).

Referring to FIG. 17, when it is determined that the monitored adverse data condition occurrence exceeds a predetermined number of occurrences during a predefined time period (1730), a notification is generated and provided to the user to either replace the sensor, or to perform one or more verifications to confirm, for example, but not limited to, that the sensor is properly inserted and positioned, the transmitter unit is in proper contact with the sensor (1740).

On the other hand, if the number of adverse data condition occurrences has not occurred during the predefined time period, in one aspect, the routine continues to monitor for the occurrence of such condition during the set time period. In one aspect, the predetermined time period during which the occurrence of adverse data condition occurrence may be approximately one hour from the initial sensor positioning. Alternatively, this time period may be shorter or longer, depending upon the particular system configuration.

In this manner, in the event that the adverse condition related to the sensor is determined and persists for a given time period from the initial sensor insertion, the user or the patient is notified to either replace the sensor or to perform one or more troubleshooting steps to make sure that the components of the analyte monitoring system are functioning properly. Indeed, in one aspect, when an adverse condition related to the sensor is identified early on, the user is not inconvenienced by continuing to maintain the sensor in position even though the sensor may be defective or improperly positioned, or is associated with one or more other adverse conditions that will not allow the sensor to function properly.

FIG. 18 illustrates uncertainty estimation associated with glucose level rate of change determination in one aspect of the present disclosure. Referring to FIG. 18, based on the monitored glucose level from the glucose sensor, a rate of change estimate of the glucose level fluctuation is determined (1810). Further, an estimation of an uncertainty range or level associated with the determined rate of change of the glucose level is determined (1820). That is, in one aspect, a predefined rate of uncertainty determination may be performed, such as for example, a rate of change variance calculation. If the uncertainty determination is within a predetermined threshold level (1830), then an output is generated and/or provided to the user (1840).

For example, when it is determined that the determined uncertainty measure is within the threshold level, the analyte monitoring system may be configured to display or output an indication to the user or the patient, such as a glucose level trend indicator (for example, a visual trend arrow or a distinctive audible alert (increasing or decreasing tone, etc)). On the other hand, if it is determined that the uncertainty measure related to the rate of change estimate exceeds the predetermined threshold, the determined rate of change of glucose level may be rejected or discarded (or stored but not output to the user or the patient). In one aspect, the uncertainty measure may include a predefined tolerance parameter associated with the accuracy of the determined rate of change of the monitored glucose level.

In one aspect, the uncertainty measure or the tolerance level related to the rate of change of monitored glucose level may include, but is not limited to, corrupt or erroneous data associated with the monitored glucose level, unacceptably large number of missing data associated with the monitored glucose level, rate of acceleration or deceleration of the monitored glucose level that exceeds a defined or acceptable threshold level, or any other parameters that may contribute to potential inaccuracy in the determined rate of change of the monitored glucose level.

Accordingly, in one aspect, the accuracy of the analyte monitoring system may be maintained by, for example, disabling the output function associated with the rate of change determination related to the monitored glucose level, so that the user or the patient does not take corrective actions based on potentially inaccurate information. That is, as discussed above, in the event when it is determined that the determined uncertainty measure or parameter exceeds an acceptable tolerance range, the output function on the receiver unit 104/106 in the analyte monitoring system 100 may be disabled temporarily, or until the uncertainty measure of parameter related to the rate of change of the glucose level being monitored is within the acceptable tolerance range.

When the monitored rate of change of the glucose level is steady (or within a defined range) and medically significant with respect to the monitored glucose measurement, a prediction of future or anticipated glucose level may be considered reliable based on the determined rate of change level. However, the monitored glucose level time series is such that the determined rate of change estimate may be less certain.

Accordingly, in one aspect, the present disclosure accounts for the rate of change estimates having varying degrees of certainty. Since clinical treatment decisions may be made based on these estimates, it is important to discount, or not display or output to the user, the determined rate of change estimates with a high degree of uncertainty.

In one aspect, the rate of change value and its uncertainty determine a probability distribution. This distribution may be assumed to be Gaussian, for example. Within the scope of the present disclosure, the uncertainty measure may be calculated in various ways. In one embodiment, it may include a standard deviation determination. Another possibility is to use the coefficient of variation (CV), which is the standard deviation of the rate of change divided by the rate of change. A combination of these uncertainty measures may also be used.

In one aspect, various ranges of rates of change may be combined into bins. For example, bin edges at ±2 mg/dL and at ±1 mg/dL may be defined in one embodiment resulting in five bins. Each bin may be represented by a position of a trend arrow indicator, associated with the monitored glucose level. When the rate of change is included in one of the determined bins, the associated trend arrow position may be displayed.

Further, the presence of uncertainty may modify the trend arrow position that is displayed to the user or the patient. In one aspect, a determination that involves the uncertainty measure results in a metric value which may be a simple comparison of the uncertainty value to a predefined threshold. There are also other possible metrics. Another approach may use a different predefined threshold value for each bin.

In one aspect, an unacceptable metric value may cause no trend arrow indicator to be displayed. Alternatively, this condition may be indicated by a change in the characteristics of the display to the user or the patient. For example, the trend arrow indicator may flash, change color, change shape, change size, change length or change width, among others. A further embodiment may include the trend arrow indicator showing no significant rate-of-change. Within the scope of the present disclosure, other user output configurations including audible and/or vibratory output are contemplated.

In one aspect, the uncertainty measure may be characterized a number of ways. One is the standard deviation of the monitored glucose levels over the period in which the rate of change is estimated. Another is the coefficient of variation (CV), which, as discussed above, is the standard deviation of the monitored glucose trend divided by the rate of change value. A further characterization may include a probabilistic likelihood estimate. Yet a further characterization is the output of a statistical filter or estimator such as a Kalman filter. The uncertainty comparison may be based on one of these techniques or a combination of two or more of these techniques. Also, different uncertainty characteristics may be used for different rate-of-change results. For instance, in one embodiment, a CV formulation may be used for high glucose values and a standard deviation formulation may be used for low glucose values.

FIG. 19 illustrates glucose trend determination in accordance with one embodiment of the present disclosure. Referring to FIG. 19, a current value associated with a monitored glucose level is received (1910). One or more prior values associated with the monitored glucose level (previously stored, for example) is retrieved (1920). With the current and prior values associated with the monitored glucose level, a most recent calibration scale factor is applied to the current and prior values associated with the monitored glucose level (1930). After applying the calibration scale factor to the current and prior values, the trend associated with the monitored glucose level is determined (1940).

In this manner, in one aspect, with the updated calibration of the glucose sensor including a newly determined sensitivity, buffered or stored values associated with the monitored glucose level may be updated using, for example, the updated calibration information, resulting, for example, in revised or modified prior values associated with the monitored glucose level. As such, in one embodiment, stored or buffered values associated with the monitored glucose level may be updated and, the updated values may be used to determine glucose trend information or rate of change of glucose level calculation. In this manner, accuracy of the glucose trend information may be improved by applying the most recent calibration parameters to previously detected and stored values associated with the monitored glucose level, when, for example, the previously detected and stored values are used for further analysis, such as, glucose trend determination or rate of change of glucose level calculation.

FIG. 20 illustrates glucose trend determination in accordance with another embodiment of the present disclosure. Referring to FIG. 20, a current value associated with a monitored glucose level is received (2010). One or more prior values associated with the monitored glucose level (previously stored, for example) is retrieved (2020). With the current and prior values associated with the monitored glucose level, a rate of change estimate of the monitored glucose level is determined (2030). Referring back to FIG. 20, an uncertainty parameter associated with the rate of change estimate is determined (2040).

In one aspect, an uncertainty parameter may be predetermined and programmed into the analyte monitoring system 100 (for example, in the receiver unit 104/106). Alternatively, the uncertainty parameter may be dynamically configured to vary depending upon the number of data available for determination of the glucose level rate of change determination, or upon other programmable parameters that may include user specified uncertainty parameters. Within the scope of the present disclosure, the uncertainty parameter may include the number of acceptable missing or unavailable values when performing the monitored glucose level rate of change estimation. Referring back to FIG. 20, when it is determined that the uncertainty parameter is within an acceptable predetermined tolerance range, the rate of change of the monitored glucose level is determined and output to the user or the patient (2050).

In one embodiment, the uncertainty parameter may be associated with the time spacing of the current and prior values, such that when the rate of change estimation requires a preset number of values, and no more than a predetermined number of values (optionally consecutively, or non consecutively) are unavailable, the rate of change estimation is performed. In this manner, for example, when a large number of values associated with the monitored glucose level (for example, 5 consecutive one minute data—tolerance range) are unavailable, corrupt or otherwise unusable for purposes of rate of change determination, the uncertainty parameter is deemed to exceed the predetermined tolerance range, and the rate of change calculation may not be performed, or may be postponed.

As discussed, the rate of change in glucose for a patient or a user may be used by glucose monitoring devices to direct glucose trend indicators for display to the patient or the user such that the patient or the user may base treatment decisions not only on the current glucose levels but also on the current direction or change in the glucose level. The rate of change estimate may also be used to project into the future if a predetermined glucose threshold (upper or lower range or limit) is not exceeded within a specific time period based on the current glucose level and rate of change information. Within the scope of the present disclosure, other projection approaches may be based on higher order derivatives of the rate of change, and/or other statistical likelihood formulations that can be contemplated for prediction of a future event.

One approach to determine the rate of change is to calculate the difference between two glucose samples and dividing the result by the time difference between the samples. Another approach may be to fit a time series of glucose readings to a function, such as a polynomial, using techniques such as the least squares techniques. The number of samples and the time period of the samples may impact the accuracy of the rate of change estimate in the form of a trade off between noise reduction properties and lag introduced.

Referring again to the Figures, in one aspect, the transmitter unit 102 may be configured to perform one or more periodic or routine data quality checks or verification before transmitting the data packet to the receiver/monitor unit 104/106. For example, in one aspect, for each data transmission (e.g., every 60 seconds, or some other predetermined transmission time interval), the transmitter data quality flags in the data packet are reset, then it is determined whether any data field in the transmission data packet includes an error flag. If one error flag is detected, then in one aspect, the entire data packet may be considered corrupt, and this determination is transmitted to the receiver/monitor unit 104/106. Alternatively, the determination that the entire data packet is corrupt may be performed by the receiver/monitor unit 104/106. Accordingly, in one aspect, when at least one data quality check fails in the transmitter data packet, the entire packet is deemed to be in error, and the associated monitored analyte level is discarded, and not further processed by the receiver/monitor unit 104/106.

In another aspect, the data quality check in the transmitter unit 102 data packet may be performed so as to identify each error flag in the data packet, and these identified error flags are transmitted to the receiver/monitor unit 104/106 in addition to the associated monitored analyte level information. In this manner, in one aspect, if the error flag is detected in the transmitter data packet which is not relevant to the accuracy of the data associated with the monitored analyte level, the error indication is flagged and transmitted to the receiver/monitor unit 104/106 in addition to the data indicating the monitored analyte level.

In one aspect, examples of error condition that may be detected or flagged in the transmitter unit 102 data packet include sensor connection fault verification by, for example, determining, among others, whether the counter electrode voltage signal is within a predetermined range, resolution of the data associated with the monitored analyte level, transmitter unit temperature (ambient and/or on-skin temperature) out of range, and the like. As discussed above, the data quality check in the transmitter unit 102 may be performed serially, such that detection of an error condition or an error flag renders the entire data packet invalid or deemed corrupt. In this case, such data is reported as including error to the receiver/monitor unit 104/106, but not used to process the associated monitored analyte level. In another aspect, all data quality fields in the data packet of the transmitter unit 102 may be checked for error flags, and if there are error flags detected, the indication of the detected error flags is transmitted with the data packet to the receiver/monitor unit 104/106 for further processing.

In one embodiment, on the receiver/monitor unit 104/106 side, for each periodic data packet received (for example every 60 seconds or some other predetermined time interval), the receiver/monitor unit 104/106 may be configured to receive the raw glucose data including any data quality check flags from the transmitter unit 102, and to apply temperature compensation and/or calibration to the raw data to determine the corresponding glucose data (with any data quality flags as may have been identified). The unfiltered, temperature compensated and/or calibrated glucose data is stored along with any data quality flags in a FIFO buffer (including, for example, any invalid data identifier). Alternatively, a further data quality check may be performed on the temperature compensated and calibrated glucose data to determine the rate of change or variance of the measured glucose data. For example, in one embodiment, a high variance check or verification is performed on 30 minutes of glucose data stored in the FIFO buffer. If it is determined that the rate of variance exceeds a predetermined threshold, then the data packet in process may be deemed invalid. On the other hand, if the rate of variance does not exceed the predetermined threshold, the results including the glucose data and any associated validity or error flags are stored in the FIFO buffer.

Thereafter, the data processing is performed on the stored data to determine, for example, the respective glucose level estimation or calculation. That is, the stored data in the FIFO buffer in one embodiment is filtered to reduce unwanted variation in signal measurements due to noise or time delay, among others. In one aspect, when the rate of change or variance of glucose data stored in the FIFO buffer, for example, is within a predetermined limit, the glucose measurements are filtered over a 15 minute period. On the other hand, if it is determined that the rate of change is greater than the predetermined limit, a more responsive 2 minute filtering is performed. In one aspect, the filtering is performed for each 60 second glucose data. In this manner, in one embodiment, a rate variance filter is provided that may be configured to smooth out the variation in the glucose measurement when the glucose level is relatively stable, and further, that can respond quickly when the glucose level is changing rapidly. The rate variance filter may be implemented in firmware as an FIR filter which is stable and easy to implement in integer-based firmware, for example, implemented in fixed point math processor.

In one embodiment, for each 60 second glucose data received, two filtered values and two additional parameters are determined. That is, using an FIR filter, for example, a weighted average for a 15 minute filtered average glucose value and a 2 minute average filtered glucose value are determined. In addition, a rate of change based on 15 minutes of data as well as a standard deviation associated with the rate estimate is determined. To determine the final filtered glucose value for output and/or display to the user, a weighted average of the two determined filtered glucose values is determined, where when the rate of change of the glucose values is high, then weighting is configured to tend towards the 2 minute filtered value, while when the rate of change of the glucose value is low the weighting tends towards the 15 minute filtered value. In this manner, when the rate of change is high, the 2 minute filtered value is weighted more heavily (as the 15 minute filtered average value potentially introduces lag, which at higher rates of change, likely results in large error).

Referring back, during the calibration routine, in one embodiment, when the discrete blood glucose value is received for purposes of calibration of the glucose data from the sensor 101 (FIG. 1), the processing unit of the receiver/monitor unit 104/106 is configured to retrieve from the FIFO buffer two of the last five valid transmitter data packet that does not include any data quality flags associated with the respective data packets. In this manner, in one aspect, calibration validation check may be performed when the blood glucose value is provided to the receiver/monitor unit 104/106 determined using, for example, a blood glucose meter. In the event that two valid data packets from the last five data packets cannot be determined, the receiver/monitor unit 104/106 is configured to alarm or notify the user, and the calibration routine is terminated.

On the other hand, if the calibration validation check is successful, the sensitivity associated with the sensor 101 (FIG. 1) is determined, and its range verified. In one aspect, if the sensitivity range check fails, again, the receiver/monitor unit 104/106 may be configured to alarm or otherwise notify the user and terminate the calibration routine. Otherwise, the determined sensitivity is used for subsequent glucose data measurement and processing (until a subsequent calibration is performed).

Referring back to the Figures, in one aspect, determination of optimal sensitivity evaluates one or more potential error sources or conditions present in blood glucose value for calibration and the potential sensitivity drift. Accordingly, using a weighted average of the current sensitivity determined for calibration and previously determined sensitivity, the sensitivity accuracy may be optimized. For example, in one embodiment, a weighted average of the two most recent sensitivities determined used for calibration may be used to determine a composite sensitivity determination to improve accuracy and reduce calibration errors. In this aspect, earlier blood glucose values used for calibration are discarded to accommodate for sensitivity drift. In one embodiment, the number of blood glucose values used for determining the weighted average, and also, the weighting itself may be varied using one or more approaches including, for example, a time based technique.

For example, for each sensor calibration routine, the sensitivity derived from the current blood glucose value from the current blood glucose test and the stored sensitivity value associated with the most recent prior stored blood glucose value may be used to determine a weighted average value that is optimized for accuracy. Within the scope of the present disclosure, as discussed above, the weighting routine may be time based such that if the earlier stored blood glucose value used for prior calibration is greater than a predetermined number of hours, then the weighting value assigned to the earlier stored blood glucose may be less heavy, and a more significant weighting value may be given to the current blood glucose value to determine the composite sensitivity value.

In one embodiment, a lookup table may be provided for determining the composite sensitivity determination based on a variable weighting average which provides a non-linear correction to reduce errors and improve accuracy of the sensor sensitivity.

The determined composite sensitivity in one embodiment may be used to convert the sensor ADC counts to the corresponding calibrated glucose value. In one aspect, the composite sensitivity determined may be used to minimize outlier calibrations and unstable sensitivity during, for example, the initial use periods. That is, during the data validation routines, outlier check may be performed to determine whether the sensitivity associated with each successive calibration is within a predetermined threshold or range.

For example, the sensor 101 (FIG. 1) may require a predetermined number of baseline calibrations during its use. For a five day operational lifetime of a sensor, four calibrations may be required at different times during the five day period. Moreover, during this time period, additional stability related calibrations may be required if the sensor sensitivity is determined to be unstable after the second baseline calibration is performed, for example, at the 12th hour (or other suitable time frame) of the sensor usage after the initial calibration within the first 10 hours of sensor deployment.

In one aspect, during the outlier check routine, it is determined whether the sensitivity variance between two successive calibrations are within a predetermined acceptable range. If it is determined that the variance is within the predetermined range, then the outlier check is confirmed, and a new composite sensitivity value is determined based on a weighted average of the two sensitivity values. As discussed above, the weighted average may include a time based function or any other suitable discrete weighting parameters.

If on the other hand, the variance between the two sensitivities is determined to be outside of the predetermined acceptable range, then the second (more recent) sensitivity value is considered to be an outlier (for example, due to ESA, change in sensitivity or due to bad or erroneous blood glucose value), and the user is prompted to perform another fingerstick testing to enter a new blood glucose value (for example, using a blood glucose meter). If the second current sensitivity associated with the new blood glucose value is determined to be within the predetermined acceptable range from the prior sensitivity, then the earlier current sensitivity value is discarded, and the composite sensitivity is determined based on applying a weighting function or parameter on the prior sensitivity value, and the second current sensitivity value (discarding the first current sensitivity value which is outside the predetermined acceptable range and considered to be an outlier).

On the other hand, when the second current sensitivity value is determined to be within the predetermined acceptable range of the first current sensitivity value, but not within the predetermined acceptable range of the prior sensitivity value (of the two successive calibrations described above), then it is determined in one embodiment that a sensitivity shift, rather than an outlier, has occurred or is detected from the first current sensitivity value to the second current sensitivity value. Accordingly, the composite sensitivity may be determined based, in this case, on the first and second current sensitivity values (and discarding the prior sensitivity).

If, for example, the second current sensitivity value is determined to be outside the predetermined range of both of the two successive sensitivities described above, then the user in one embodiment is prompted to perform yet another blood glucose test to input another current blood glucose value, and the routine described above is repeated.

Furthermore, in accordance with another aspect, the determination of the sensitivity variance between two successive calibrations are within a predetermined acceptable range may be performed prior to the outlier check routine.

Referring to the Figures, during the period of use, as discussed above, the sensor 101 (FIG. 1) is periodically calibrated at predetermined time intervals. In one aspect, after the second baseline calibration (for example, at the 12th hour of sensor 101 transcutaneously positioned in fluid contact with the user's analyte), sensor sensitivity stability verifications may be performed to determine whether, for example, additional stability calibrations may be necessary before the third baseline calibration is due. In one aspect, the sensitivity stability verification may be performed after the outlier checks as described above is performed, and a new composite sensitivity is determined, and prior to the third scheduled baseline calibration at the 24th hour (or at another suitable scheduled time period).

That is, the sensor sensitivity may be attenuated (e.g., ESA) early in the life of the positioned sensor 101 (FIG. 1), and if not sufficiently dissipated by the time of the first baseline calibration, for example, at the 10th hour (or later), and even by the time of the second calibration at the 12th hour. As such, in one aspect, a relative difference between the two sensitivities associated with the two calibrations is determined. If the determined relative difference is within a predefined threshold or range (for example, approximately 26% variation), then it is determined that the sufficient stability point has been reached. On the other hand, if the relative difference determined is beyond the predefined threshold, then the user is prompted to perform additional calibrations at a timed interval (for example, at each subsequent 2 hour period) to determine the relative difference in the sensitivity compared to the predefined range. This may be repeated for each two hour interval, for example, until an acceptable stability point has been reached, or alternatively, until the time period for the third baseline calibration is reached, for example, at the 24th hour of sensor 101 (FIG. 1) use.

In this manner, in one aspect, the stability verification may be monitored as the sensitivity attenuation is dissipating over a given time period. While the description above is provided with particular time periods for baseline calibrations and additional calibration prompts for stability checks, for example, within the scope of the present disclosure, other time periods or calibration schedule including stability verifications may be used. In addition, other suitable predefined threshold or range of the relative sensitivity difference to determine acceptable attenuation dissipation other than approximately 26% may be used. Moreover, as discussed above, the predetermined calibration schedule for each sensor 101 (FIG. 1) may be modified from the example provided above, based on, for example, the system design and/or sensor 101 (FIG. 1) configuration.

Additionally, in one aspect, the user may be prompted to perform the various scheduled calibrations based on the calibration schedule provided. In the case where the scheduled calibration is not performed, in one embodiment, the glucose value determination for user display or output (on the receiver/monitor unit 104/106, for example) based on the received sensor data may be disabled after a predetermined time period has lapsed. Further, the glucose value determination may be configured to resume when the prompted calibration is successfully completed.

In a further aspect, the scheduled calibration timing may be relative to the prior calibration time periods, starting with the initial sensor positioning. That is, after the initial transcutaneous positioning of the sensor 101 (FIG. 1) and the scheduled time period has elapsed to allow the sensor 101 to reach a certain stability point, the user may be prompted to perform the first baseline calibration as described above (for example, at the 10th hour since the initial sensor placement). Thereafter, in the case when the user waits until the 11th hour to perform the initial baseline calibration, the second scheduled calibration at the 12th hour, for example, may be performed at the 13th hour, so that the two hour spacing between the two calibrations are maintained, and the second calibration timing is based on the timing of the first successful baseline calibration performed. In an alternate embodiment, each scheduled calibration time period may be based on the timing of the initial sensor positioning. That is, rather than determining the appropriate subsequent calibration time periods based on the prior calibration performed, the timing of the scheduled calibration time periods may be made to be absolute and based from the time of the initial sensor placement.

Furthermore, in one aspect, when the scheduled calibration is not performed at the scheduled time periods, the glucose values may nevertheless be determined based on the sensor data for display to the user for a limited time period (for example, for no more than two hours from when the scheduled calibration time period is reached). In this manner, a calibration time window may be established or provided to the user with flexibility in performing the scheduled calibration and during which the glucose values are determined for output display to the user, for example. In one aspect, if within the calibration time window for the scheduled calibrations are not performed, the glucose values may be deemed in error, and thus not provided to the user or determined until the calibration is performed.

For example, after the initial successful baseline calibration at the 10th hour, for example, or at any other suitable scheduled initial baseline calibration time, glucose values are displayed or output to the user and stored in a memory. Thereafter, at the next scheduled calibration time period (for example, at the 12th hour), the user may be prompted to perform the second calibration. If the user does not perform the second calibration, a grace period of two hours, for example, is provided during which valid glucose values are provided to the user (for example, on the display unit of the receiver/monitor unit 104/106) based on the prior calibration parameters (for example, the initial baseline calibration performed at the 10th hour). However, if the second calibration is still not performed after the grace period, in one aspect, no additional glucose values are provided to the user, until the scheduled calibration is performed.

In still another aspect, the user may supplement the scheduled calibrations, and perform manual calibration based on the information that the user has received. For example, in the case that the user determines that the calibration performed and determined to be successful by the receiver/monitor unit 104/106, for example, is not sufficiently accurate, rather than replacing the sensor, the user may recalibrate the sensor even if the scheduled calibration time has not been reached. For example, based on a blood glucose test result, if the determined blood glucose level is not close to or within an acceptable range as compared to the sensor data, the user may determine that additional calibration may be needed.

Indeed, as the sensitivity value of a given sensor tends to stabilize over time, a manual user forced calibration later in the sensor's life may provide improved accuracy in the determined glucose values, as compared to the values based on calibrations performed in accordance with the prescribed or predetermined calibration schedule. Accordingly, in one aspect, additional manual calibrations may be performed in addition to the calibrations based on the predetermined calibration schedule.

In a further aspect, user notification functions may be programmed in the receiver/monitor unit 104/106, or in the transmitter unit 102 (FIG. 1) to notify the user of initial conditions associated with the sensor 101 (FIG. 1) performance or integrity. That is, alarms or alerts, visual, auditory, and/or vibratory may be configured to be triggered when conditions related to the performance of the sensor are detected. For example, during the initial one hour period (or some other suitable time period) from the sensor insertion, in the case where data quality flags/conditions (described above) are detected, or in the case where low or no signal from the sensor is detected from a given period of time, an associated alarm or notification may be initiated or triggered to notify the user to verify the sensor position, the sensor contacts with the transmitter unit 102 (FIG. 1), or alternatively, to replace the sensor with a new sensor. In this manner, rather than waiting a longer period until the acceptable sensor stability point has been reached, the user may be provided at an early stage during the sensor usage that the positioned sensor may be defective or has failed.

In addition, other detected conditions related to the performance of the sensor, calibration, or detected errors associated with the glucose value determination may be provided to the user using one or more alarm or alert features. For example, when the scheduled calibration has been timely performed, and the grace period as described above has expired, in one embodiment, the glucose value is not processed for display or output to the user anymore. In this case, an alarm or alert notifying the user that the glucose value cannot be calculated is provided so that the user may timely take corrective actions such as performing the scheduled calibration. In addition, when other parameters that are monitored such as the temperature, sensor data, and other variables that are used to determine the glucose value, include error or otherwise is deemed to be corrupt, the user may be notified that the associated glucose value cannot be determined, so that the user may take corrective actions such as, for example, replacing the sensor, verifying the contacts between the sensor and the transmitter unit, and the like.

In this manner, in one embodiment, there is provided an alarm or notification function that detects or monitors one or more conditions associated with the glucose value determination, and notifies the user of the same when such condition is detected. Since the alarms or notifications associated with the glucose levels (such as, for example, alarms associated with potential hyperglycemic, hypoglycemic, or programmed trend or rate of change glucose level conditions) will be inactive if the underlying glucose values cannot be determined, by providing a timely notification or alarm to the user that the glucose value cannot be determined, the user can determine or prompted/notified that these alarms associated with glucose levels are inactive.

In one aspect of the present disclosure, glucose trend information may be determined and provided to the user, for example, on the receiver/monitor unit 104/106. For example, trend information in one aspect is based on the prior monitored glucose levels. When calibration is performed, the scaling used to determine the glucose levels may change. If the scaling for the prior glucose data (for example, one minute prior) is not changed, then in one aspect, the trend determination may be deemed more error prone. Accordingly, in one aspect, to determine accurate and improved trend determination, the glucose level determination is performed retrospectively for a 15 minute time interval based on the current glucose data when each successive glucose level is determined.

That is, in one aspect, with each minute determination of the real time glucose level, to determine the associated glucose trend information, the stored past 15 minute data associated with the determined glucose level is retrieved, including the current glucose level. In this manner, the buffered prior glucose levels may be updated with new calibration to improve accuracy of the glucose trend information.

In one aspect, the glucose trend information is determined based on the past 15 minutes (or some other predetermined time interval) of glucose data including, for example, the current calibration parameter such as current sensitivity. Thereafter, when the next glucose data is received (at the next minute or based on some other timed interval), a new sensitivity is determined based on the new data point associated with the new glucose data. Also, the trend information may be determined based on the new glucose data and the past 14 minutes of glucose data (to total 15 minutes of glucose data). It is to be noted that while the trend information is determined based on 15 minutes of data as described above, within the scope of the present disclosure, other time intervals may be used to determine the trend information, including, for example, 30 minutes of glucose data, 10 minutes of glucose data, 20 minutes of glucose data, or any other appropriate time intervals to attain an accurate estimation of the glucose trend information.

In this manner, in one aspect of the present disclosure, the trend information for the historical glucose information may be updated based on each new glucose data received, retrospectively, based on the new or current glucose level information, and the prior 14 glucose data points (or other suitable number of past glucose level information). In another aspect, the trend information may be updated based on a select number of recent glucose level information such that, it is updated periodically based on a predetermined number of determined glucose level information for display or output to the user.

In still another aspect, in wireless communication systems such as the data monitoring and management system 100 (FIG. 1), the devices or components intended for wireless communication may periodically be out of communication range. For example, the receiver/monitor unit 104/106 may be placed out of the RF communication range of the transmitter unit 102 (FIG. 1). In such cases, the transmitted data packet from the transmitter unit 102 may not be received by the receiver/monitor unit 104/106, or due to the weak signaling between the devices, the received data may be invalid or corrupt. In such cases, while there may be missing data points associated with the periodically monitored glucose levels, the trend information may be nevertheless determined, as the trend information is determined based on a predetermined number of past or prior glucose data points (for example, the past 15 minutes of glucose data).

That is, in one aspect, even if there are a certain number of glucose data points within the 15 minute time frame that may be either not received by the receiver/monitor unit 104/106, or alternatively be corrupt or otherwise invalid due to, for example, weakness in the communication link, the trend information may be determined. For example, given the 15 minutes of glucose data, if three or less non consecutive data points are not received or otherwise corrupt, the receiver/monitor unit 104/106 may determine the glucose trend information based on the prior 12 glucose data points that are received and considered to be accurate. As such, the features or aspects of the analyte monitoring system which are associated with the determined trend information may continue to function or operate as programmed.

That is, the projected alarms or alerts programmed into the receiver/monitor unit 104/106, or any other alarm conditions associated with the detection of impending hyperglycemia, impending hypoglycemia, hyperglycemic condition or hypoglycemic condition (or any other alarm or notification conditions) may continue to operate as programmed even when there are a predetermined number or less of glucose data points. However, if and when the number of missing glucose data points exceed the tolerance threshold so as to accurately estimate or determine, for example, the glucose trend information, or any other associated alarm conditions, the display or output of the associated glucose trend information or the alarm conditions may be disabled.

For example, in one aspect, the glucose trend information and the rate of change of the glucose level (which is used to determine the trend information) may be based on 15 minute data (or data based on any other suitable time period) of the monitored glucose levels, where a predetermined number of missing data points within the 15 minutes may be tolerated. Moreover, using least squares approach, the rate of change of the monitored glucose level may be determined to estimate the trend, where the monitored glucose data are not evenly spaced in time. In this approach, the least squares approach may provide an uncertainty measure of the rate of change of the monitored glucose level. The uncertainty measure, in turn, may be partially dependent upon the number of data points available.

Indeed, using the approaches described above, the trend information or the rate of change of the glucose level may be estimated or determined without the need to determine which data point or glucose level is tolerable, and which data point is not tolerable. For example, in one embodiment, the glucose data for each minute including the missing date is retrieved for a predetermined time period (for example, 15 minute time period). Thereafter, least squares technique is applied to the 15 minute data points. Based on the least squares (or any other appropriate) technique, the uncertainty or a probability of potential variance or error of the rate of glucose level change is determined. For example, the rate of change may be determined to be approximately 1.5 mg/dL/minute+/−0.1 mg/dL/minute. In such a case, the 0.1 mg/dL/minute may represent the uncertainty information discussed above, and may be higher or lower depending upon the number of data points in the 15 minutes of data that are missing or corrupt.

In this manner, in one aspect, the glucose trend information and/or the rate of change of monitored glucose level may be determined based on a predefined number of past monitored glucose level data points, even when a subset of the predefined number of past monitored glucose level data points are missing or otherwise determined to be corrupt. On the other hand, when the number of past glucose level data points based on which the glucose trend information is determined, exceeds the tolerance or acceptance level, for example, the display or output of the glucose trend information may be disabled. Additionally, in a further aspect, if it is determined that the underlying data points associated with the monitored glucose level based on which the trend information is determined, includes uncertainty or error factor that exceeds the tolerance level (for example, when there are more than a predetermined number of data points which deviate from a predefined level), the receiver/monitor unit 104/106, for example, may be configured to disable or disallow the display or output of the glucose trend information.

For example, when the 15 minute glucose data including the current glucose level as well as the past 14 minutes of glucose level data is to be displayed or output to the user, and the determined rate variance of the 15 data points exceeds a preset threshold level (for example, 3.0), the glucose trend information display function may be disabled. In one aspect, the variance may be determined based on the square function of the standard deviation of the 15 data points. In one aspect, this approach may be performed substantially on a real time basis for each minute of glucose data. Accordingly, as discussed above, the glucose trend information may be output or displayed substantially in real time, and based on each new glucose data point received from the sensor/transmitter unit.

Additionally, when it is determined that the 15 data points (or any other suitable number of data points for determining glucose trend information, for example), deviate beyond a predetermined tolerance range, in one aspect, the 15 minute data may be deemed error prone or inaccurate. In this case, rather than outputting or displaying glucose trend information that may be erroneous, the receiver/monitor unit 104/106 may be configured to display the output or display function related to the output or display of the determined glucose trend information. The same may apply to the output or display of projected alarms whose estimates may be based in part, on the determined trend information. Accordingly, in one aspect, there may be instances when the projected alarm feature may be temporarily disabled where the underlying monitored glucose data points are considered to include more than an acceptable level of uncertainty or error.

In a further aspect, it is desired to determine an estimate of sensor sensitivity, and/or a range of acceptable or reasonable sensitivity. For example, during determination or verification of the glucose rate of change prior to calibration, the estimated sensor sensitivity information is necessary, for example, to determine whether the rate of change is within or below an acceptable threshold level, and/or further, within a desired range. Moreover, when determining whether the sensor sensitivity is within an acceptable or reasonable level, it may be necessary to ascertain a range of reasonable or acceptable sensitivity—for example, a verification range for the sensitivity value for a given sensor or batch of sensors.

Accordingly, in one aspect, during sensor manufacturing process, a predetermined number of sensor samples (for example, 16 samples) may be evaluated from each manufacturing lot of sensors (which may include, for example, approximately 500 sensors) and the nominal sensitivity for each lot (based, for example, on a mean calculation) may be determined. For example, during the manufacturing process, the predetermined number of sensors (for example, the 16 sensors) are sampled, and the sensitivity of each sampled sensor is measured in vitro. Thereafter, a mean sensitivity may be determined as an average value of the 16 sampled sensor's measured sensitivity, and thereafter, the corresponding sensor code is determined where the determined mean sensitivity falls within the preassigned sensitivity range. Based on the determined sensor code, the sensor packaging is labeled with the sensor code.

For example, each sensor code value (e.g., 105, 106, 107 or any suitable predetermined number or code) may be preassigned a sensitivity range (For example, code 105: S1-S2, code 106: S2-S3, and code 107:S3-S4), where each sensitivity range (e.g., S1-S2, or S2-S3, or S3-S4) is approximately over a 10 percent increment (for example, S1 is approximately 90% of S2). Also, each sensor code (e.g., 105, 106, 107 etc) is assigned a nominal sensitivity value (Sn) that is within the respective preassigned sensitivity range.

Referring back, when the user inserts the sensor or positions the sensor transcutaneously in place, the receiver/monitor unit 104/106 in one embodiment prompts the user to enter the associated sensor code. When the user enters the sensor code (as derived from the sensor packing label discussed above), the receiver/monitor unit 104/106 is configured to retrieve or look up the nominal sensitivity associated with the user input sensor code (and the nominal sensitivity which falls within the preassigned sensitivity range associated with that sensor code, as described above). Thereafter, the receiver/monitor unit 104/106 may be configured to use the sensor code in performing associate routines such as glucose rate of change verification, data quality checks discussed above, and/or sensor sensitivity range acceptability or confirmation.

In a further aspect, the sensor codes may be associated with a coefficient of variation of the predetermined number of sampled sensors discussed above in addition to using the mean value determined as discussed above. In one embodiment, the coefficient of variation may be determined from the predetermined number of sampled sensors during the manufacturing process. In addition, the mean response time of the sampled sensors may be used by separately measuring the predetermined number of sampled sensors which may be used for lag correction adjustments and the like.

In this manner, in one aspect, the manufacturing process control described above ensures that the coefficient of variation of the sampled sensors is within a threshold value. That is, the value of the nominal sensitivity is used to determine a sensor code, selected or looked up from a predetermined table, and that is assigned to the sensors from the respective sensor lot in manufacturing. The user then enters the sensor code into the receiver/monitor unit that uses the sensor code to determine the glucose rate of change for purposes of data quality checking, for example, and also to determine validity or reasonableness of the sensitivity that is determined.

In one embodiment, a method may comprise receiving glucose related data from an in vivo analyte sensor, determining a first filtered value associated with the received data based on a first predetermined time period and the received data, determining a second filtered value associated with the received data based on a second predetermined time period and the received data, determining a rate of change of the glucose level based at least in part on the received data, generating a weighted average value based upon the first filtered value and the second filtered value, and determining a filtered glucose value based at least in part on the weighted average value and a predetermined parameter.

The first predetermined time period may be greater than the second predetermined time period.

The weighted average value may be based at least in part on a relative weighting parameter associated with each of the first filtered value and the second filtered value.

The weighted average value may be based at least in part on the determined rate of change of the glucose level.

The relative weighted parameter associated with the first filtered value may be different from the relative weighting parameter associated with the second filtered value.

The relative weighting parameter may be varied in proportion to the determined rate of change of the glucose level.

Determining the filtered glucose value may include performing a rate variance filtering based on one or more of the first filtered value, the second filtered value, the determined rate of change of the glucose level, and the predetermined parameter.

Rate variance filtering may be proportional to the rate of change of the glucose level.

One aspect may include determining a standard deviation of the rate of change of the glucose level based on the received data.

The weighted average value may be based at least in part on a relative weighting parameter, and further, wherein the relative weighting parameter is based on one or more of the rate of change of the glucose level or the determined standard deviation of the rate of change.

One aspect may include positioning at least a portion of the analyte sensor in continuous fluid contact with an analyte of an individual over a predetermined time period.

The predetermined time period may be approximately three days.

The predetermined time period may be approximately five days.

The predetermined time period may be approximately seven days.

In one embodiment, an apparatus including a glucose monitoring device may comprise a communication unit to receive glucose related data from a transcutaneously positioned in vivo glucose sensor, and a processing unit coupled to the communication unit, the processing unit configured to determine a first filtered value associated with the received data based on a first predetermined time period and the received data, to determine a second filtered value associated with the received data based on a second predetermined time period and the received data, to determine a rate of change of the glucose level based at least in part on the received data, to generate a weighted average value based upon the first filtered value and the second filtered value, and to determine a filtered glucose value based at least in part on the weighted average value and a predetermined parameter.

The first predetermined time period may be greater than the second predetermined time period.

The weighted average value may be based at least in part on a relative weighting parameter associated with each of the first filtered value and the second filtered value.

The weighted average value may be based at least in part on the determined rate of change of the glucose level.

The relative weighted parameter associated with the first filtered value may be different from the relative weighting parameter associated with the second filtered value.

The processor unit may vary the relative weighting parameter in proportion to the determined rate of change of the glucose level.

The processing unit may be configured to perform a rate variance filtering based on one or more of the first filtered value, the second filtered value, the determined rate of change of the glucose level, and the predetermined parameter.

Rate variance filtering may be proportional to the rate of change of the glucose level.

The processing unit may determine a standard deviation of the rate of change of the glucose level based on the received data.

The processing unit may be configured to determine the weighted average value based at least in part on a relative weighting parameter, wherein the relative weighting parameter is based on one or more of the rate of change of the glucose level or the determined standard deviation of the rate of change.

The communication unit may be configured to substantially continuously receive the glucose related data from the glucose sensor during a predetermined time period.

The predetermined time period may be one of approximately three days, five days, or seven days.

Various other modifications and alterations in the structure and method of operation of this invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. It is intended that the following claims define the scope of the present disclosure and that structures and methods within the scope of these claims and their equivalents be covered thereby.

Claims

1. A method of indicating a rate of change in a user's analyte level with reduced noise-induced variation, comprising: determining, with a processor, a first filtered value associated with analyte related data measured by an in vivo sensor during a first predetermined time period;determining, with the processor, a second filtered value associated with analyte related data measured by the in vivo sensor during a second predetermined time period, wherein the first predetermined time period is greater than the second predetermined time period;determining, with the processor, (a) a rate of change of an analyte level based, at least in part, on the analyte related data, and (b) a rate of change variation;generating, with the processor, a weighted average value based upon the first filtered value and the second filtered value such that the first filtered value is weighted more than the second filtered value when the rate of change is greater than the rate of change variation and such that the second filtered value is weighted more than the first filtered value when the rate of change is less than the rate of change variation;determining, with the processor, a filtered analyte value based at least in part on the weighted average value and a predetermined parameter to reduce noise-induced variation; anddynamically displaying an indication based on the filtered analyte value to a user on a display of an analyte monitoring device.
2. The method of claim 1, wherein the indication is a trend arrow.
3. The method of claim 1, wherein the first predetermined time period includes the second predetermined time period.
4. The method of claim 1, wherein the first predetermined time period is fifteen minutes and the second predetermined time period is two minutes.
5. The method of claim 1, wherein determining the filtered rate of change value includes performing a rate variance filtering.
6. The method of claim 1, wherein the rate of change variation is a standard deviation.
7. The method of claim 1, wherein the analyte related data is glucose related data and the analyte level is a glucose level.
8. An apparatus including an analyte monitoring device, comprising: a communication unit adapted to receive analyte related data from an in vivo analyte sensor positioned in a body of a user; anda processor coupled to the communication unit, the processor configured to: determine a first filtered value associated with received analyte related data measured by the in vivo analyte sensor during a first predetermined time period;determine a second filtered value associated with received analyte related data measured by the in vivo analyte sensor over a second predetermined time period, wherein the first predetermined time period is greater than the second predetermined time period;determine (a) a rate of change of analyte level based, at least in part, on the received analyte related data, and (b) a rate of change variation;generate a weighted average value based upon the first filtered value and the second filtered value such that the first filtered value is weighted more than the second filtered value when the rate of change is greater than the rate of change variation and such that the second filtered value is weighted more than the first filtered value when the rate of change is less than the rate of change variation;determine a filtered analyte value based at least in part on the weighted average value and a predetermined parameter to reduce noise-induced variation; andcause the dynamic display of an indication based on the filtered analyte value to a user.
9. The apparatus of claim 8, wherein the indication is a trend arrow.
10. The apparatus of claim 8, wherein the first predetermined time period includes the second predetermined time period.
11. The apparatus of claim 8, wherein the first predetermined time period is fifteen minutes and the second predetermined time period is two minutes.
12. The apparatus of claim 8, wherein the processing unit is configured to determine the filtered rate of change value by performance of a rate variance filtering.
13. The apparatus of claim 8, wherein the rate of change variation is a standard deviation.
14. The apparatus of claim 8, wherein the analyte related data is glucose related data and the analyte level is a glucose level.

RELATED APPLICATIONS

The present application is a continuation of U.S. patent application Ser. No. 13/898,139 filed May 20, 2013, now U.S. Pat. No. 9,483,608, which is a continuation of U.S. patent application Ser. No. 12/152,650 filed May 14, 2008, now U.S. Pat. No. 8,444,560, which claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Application No. 60/917,873 filed May 14, 2007, entitled “Method And Apparatus For Providing Data Processing And Control In A Medical Communication System”, and assigned to the Assignee of the present application, Abbott Diabetes Care Inc. of Alameda, Calif., the disclosures of each of which are incorporated herein by reference for all purposes.

US Referenced Citations (1115)

Number	Name	Date	Kind
3581062	Aston	May 1971	A
3926760	Allen et al.	Dec 1975	A
3949388	Fuller	Apr 1976	A
3960497	Acord et al.	Jun 1976	A
4033330	Willis et al.	Jul 1977	A
4036749	Anderson	Jul 1977	A
4055175	Clemens et al.	Oct 1977	A
4129128	McFarlane	Dec 1978	A
4245634	Albisser et al.	Jan 1981	A
4327725	Cortese et al.	May 1982	A
4344438	Schultz	Aug 1982	A
4349728	Phillips et al.	Sep 1982	A
4373527	Fischell	Feb 1983	A
4392849	Petre et al.	Jul 1983	A
4425920	Bourland et al.	Jan 1984	A
4431004	Bessman et al.	Feb 1984	A
4441968	Emmer et al.	Apr 1984	A
4464170	Clemens et al.	Aug 1984	A
4478976	Goertz et al.	Oct 1984	A
4494950	Fischell	Jan 1985	A
4509531	Ward	Apr 1985	A
4527240	Kvitash	Jul 1985	A
4538616	Rogoff	Sep 1985	A
4619793	Lee	Oct 1986	A
4671288	Gough	Jun 1987	A
4703756	Gough et al.	Nov 1987	A
4731726	Allen, III	Mar 1988	A
4749985	Corsberg	Jun 1988	A
4757022	Shults et al.	Jul 1988	A
4777953	Ash et al.	Oct 1988	A
4779618	Mund et al.	Oct 1988	A
4847785	Stephens	Jul 1989	A
4854322	Ash et al.	Aug 1989	A
4871351	Feingold	Oct 1989	A
4890620	Gough	Jan 1990	A
4925268	Iyer et al.	May 1990	A
4953552	DeMarzo	Sep 1990	A
4986271	Wilkins	Jan 1991	A
4995402	Smith et al.	Feb 1991	A
5000180	Kuypers et al.	Mar 1991	A
5002054	Ash et al.	Mar 1991	A
5019974	Beckers	May 1991	A
5050612	Matsumura	Sep 1991	A
5051688	Murase et al.	Sep 1991	A
5055171	Peck	Oct 1991	A
5068536	Rosenthal	Nov 1991	A
5082550	Rishpon et al.	Jan 1992	A
5106365	Hernandez	Apr 1992	A
5122925	Inpyn	Jun 1992	A
5135004	Adams et al.	Aug 1992	A
5165407	Wilson et al.	Nov 1992	A
5202261	Musho et al.	Apr 1993	A
5204264	Kaminer et al.	Apr 1993	A
5210778	Massart	May 1993	A
5228449	Christ et al.	Jul 1993	A
5231988	Wernicke et al.	Aug 1993	A
5243696	Carr et al.	Sep 1993	A
5246867	Lakowicz et al.	Sep 1993	A
5251126	Kahn et al.	Oct 1993	A
5262035	Gregg et al.	Nov 1993	A
5262305	Heller et al.	Nov 1993	A
5264104	Gregg et al.	Nov 1993	A
5264105	Gregg et al.	Nov 1993	A
5279294	Anderson et al.	Jan 1994	A
5285792	Sjoquist et al.	Feb 1994	A
5293877	O'Hara et al.	Mar 1994	A
5299571	Mastrototaro	Apr 1994	A
5320725	Gregg et al.	Jun 1994	A
5322063	Allen et al.	Jun 1994	A
5330634	Wong et al.	Jul 1994	A
5340722	Wolfbeis et al.	Aug 1994	A
5342789	Chick et al.	Aug 1994	A
5356786	Heller et al.	Oct 1994	A
5360404	Novacek et al.	Nov 1994	A
5372427	Padovani et al.	Dec 1994	A
5379238	Stark	Jan 1995	A
5384547	Lynk et al.	Jan 1995	A
5390671	Lord et al.	Feb 1995	A
5391250	Cheney, II et al.	Feb 1995	A
5408999	Singh et al.	Apr 1995	A
5410326	Goldstein	Apr 1995	A
5411647	Johnson et al.	May 1995	A
5425868	Pedersen	Jun 1995	A
5429602	Hauser	Jul 1995	A
5431160	Wilkins	Jul 1995	A
5431921	Thombre	Jul 1995	A
5438983	Falcone	Aug 1995	A
5462645	Albery et al.	Oct 1995	A
5472317	Field et al.	Dec 1995	A
5489414	Schreiber et al.	Feb 1996	A
5497772	Schulman et al.	Mar 1996	A
5505828	Wong et al.	Apr 1996	A
5507288	Bocker et al.	Apr 1996	A
5509410	Hill et al.	Apr 1996	A
5514718	Lewis et al.	May 1996	A
5531878	Vadgama et al.	Jul 1996	A
5532686	Urbas et al.	Jul 1996	A
5552997	Massart	Sep 1996	A
5555190	Derby et al.	Sep 1996	A
5564434	Halperin et al.	Oct 1996	A
5568400	Stark et al.	Oct 1996	A
5568806	Cheney, II et al.	Oct 1996	A
5569186	Lord et al.	Oct 1996	A
5582184	Erickson et al.	Dec 1996	A
5586553	Halili et al.	Dec 1996	A
5593852	Heller et al.	Jan 1997	A
5601435	Quy	Feb 1997	A
5609575	Larson et al.	Mar 1997	A
5628310	Rao et al.	May 1997	A
5634468	Platt et al.	Jun 1997	A
5653239	Pompei et al.	Aug 1997	A
5660163	Schulman et al.	Aug 1997	A
5665222	Heller et al.	Sep 1997	A
5707502	McCaffrey et al.	Jan 1998	A
5711001	Bussan et al.	Jan 1998	A
5711861	Ward et al.	Jan 1998	A
5724030	Urbas et al.	Mar 1998	A
5726646	Bane et al.	Mar 1998	A
5733259	Valcke et al.	Mar 1998	A
5735285	Albert et al.	Apr 1998	A
5748103	Flach et al.	May 1998	A
5749907	Mann	May 1998	A
5772586	Heinonen et al.	Jun 1998	A
5791344	Schulman et al.	Aug 1998	A
5804047	Karube et al.	Sep 1998	A
5833603	Kovacs et al.	Nov 1998	A
5842189	Keeler et al.	Nov 1998	A
5891049	Cyrus et al.	Apr 1999	A
5899855	Brown	May 1999	A
5914026	Blubaugh, Jr. et al.	Jun 1999	A
5919141	Money et al.	Jul 1999	A
5925021	Castellano et al.	Jul 1999	A
5935224	Svancarek et al.	Aug 1999	A
5942979	Luppino	Aug 1999	A
5951485	Cyrus et al.	Sep 1999	A
5957854	Besson et al.	Sep 1999	A
5961451	Reber et al.	Oct 1999	A
5964993	Blubaugh, Jr. et al.	Oct 1999	A
5965380	Heller et al.	Oct 1999	A
5971922	Arita et al.	Oct 1999	A
5980708	Champagne et al.	Nov 1999	A
5995860	Sun et al.	Nov 1999	A
6001067	Shults et al.	Dec 1999	A
6024699	Surwit et al.	Feb 2000	A
6028413	Brockmann	Feb 2000	A
6049727	Crothall	Apr 2000	A
6052565	Ishikura et al.	Apr 2000	A
6066243	Anderson et al.	May 2000	A
6083710	Heller et al.	Jul 2000	A
6088608	Schulman et al.	Jul 2000	A
6091976	Pfeiffer et al.	Jul 2000	A
6091987	Thompson	Jul 2000	A
6093172	Funderburk et al.	Jul 2000	A
6096364	Bok et al.	Aug 2000	A
6103033	Say et al.	Aug 2000	A
6117290	Say et al.	Sep 2000	A
6119028	Schulman et al.	Sep 2000	A
6120676	Heller et al.	Sep 2000	A
6121009	Heller et al.	Sep 2000	A
6121611	Lindsay et al.	Sep 2000	A
6122351	Schlueter, Jr. et al.	Sep 2000	A
6130623	MacLellan et al.	Oct 2000	A
6134461	Say et al.	Oct 2000	A
6143164	Heller et al.	Nov 2000	A
6144871	Saito et al.	Nov 2000	A
6157850	Diab et al.	Dec 2000	A
6159147	Lichter et al.	Dec 2000	A
6162611	Heller et al.	Dec 2000	A
6175752	Say et al.	Jan 2001	B1
6200265	Walsh et al.	Mar 2001	B1
6212416	Ward et al.	Apr 2001	B1
6219574	Cormier et al.	Apr 2001	B1
6223283	Chaiken et al.	Apr 2001	B1
6233471	Berner et al.	May 2001	B1
6248067	Causey, III et al.	Jun 2001	B1
6254586	Mann et al.	Jul 2001	B1
6270455	Brown	Aug 2001	B1
6275717	Gross et al.	Aug 2001	B1
6283761	Joao	Sep 2001	B1
6284478	Heller et al.	Sep 2001	B1
6291200	LeJeune et al.	Sep 2001	B1
6293925	Safabash et al.	Sep 2001	B1
6294997	Paratore et al.	Sep 2001	B1
6295506	Heinonen et al.	Sep 2001	B1
6299347	Pompei	Oct 2001	B1
6306104	Cunningham et al.	Oct 2001	B1
6309884	Cooper et al.	Oct 2001	B1
6314317	Willis	Nov 2001	B1
6329161	Heller et al.	Dec 2001	B1
6348640	Navot et al.	Feb 2002	B1
6359270	Bridson	Mar 2002	B1
6359444	Grimes	Mar 2002	B1
6360888	McIvor et al.	Mar 2002	B1
6366794	Moussy et al.	Apr 2002	B1
6377828	Chaiken et al.	Apr 2002	B1
6379301	Worthington et al.	Apr 2002	B1
6387048	Schulman et al.	May 2002	B1
6400974	Lesho	Jun 2002	B1
6405066	Essenpreis et al.	Jun 2002	B1
6413393	Van Antwerp et al.	Jul 2002	B1
6416471	Kumar et al.	Jul 2002	B1
6418346	Nelson et al.	Jul 2002	B1
6424847	Mastrototaro et al.	Jul 2002	B1
6427088	Bowman, IV et al.	Jul 2002	B1
6440068	Brown et al.	Aug 2002	B1
6471689	Joseph et al.	Oct 2002	B1
6478736	Mault	Nov 2002	B1
6484046	Say et al.	Nov 2002	B1
6493069	Nagashimada et al.	Dec 2002	B1
6496729	Thompson	Dec 2002	B2
6497655	Linberg et al.	Dec 2002	B1
6498043	Schulman et al.	Dec 2002	B1
6514718	Heller et al.	Feb 2003	B2
6520326	McIvor et al.	Feb 2003	B2
6544212	Galley et al.	Apr 2003	B2
6546268	Ishikawa et al.	Apr 2003	B1
6549796	Sohrab	Apr 2003	B2
6551494	Heller et al.	Apr 2003	B1
6554798	Mann et al.	Apr 2003	B1
6558320	Causey, III et al.	May 2003	B1
6558321	Burd et al.	May 2003	B1
6558351	Steil et al.	May 2003	B1
6560471	Heller et al.	May 2003	B1
6561975	Pool et al.	May 2003	B1
6561978	Conn et al.	May 2003	B1
6562001	Lebel et al.	May 2003	B2
6564105	Starkweather et al.	May 2003	B2
6565509	Say et al.	May 2003	B1
6571128	Lebel et al.	May 2003	B2
6572545	Knobbe et al.	Jun 2003	B2
6574490	Abbink et al.	Jun 2003	B2
6574510	Von Arx et al.	Jun 2003	B2
6576101	Heller et al.	Jun 2003	B1
6577899	Lebel et al.	Jun 2003	B2
6579231	Phipps	Jun 2003	B1
6579690	Bonnecaze et al.	Jun 2003	B1
6585644	Lebel et al.	Jul 2003	B2
6591125	Buse et al.	Jul 2003	B1
6595919	Berner et al.	Jul 2003	B2
6605200	Mao et al.	Aug 2003	B1
6605201	Mao et al.	Aug 2003	B1
6607509	Bobroff et al.	Aug 2003	B2
6610012	Mault	Aug 2003	B2
6631281	Kastle	Oct 2003	B1
6633772	Ford et al.	Oct 2003	B2
6635014	Starkweather et al.	Oct 2003	B2
6635167	Batman et al.	Oct 2003	B1
6641533	Causey, III et al.	Nov 2003	B2
6648821	Lebel et al.	Nov 2003	B2
6654625	Say et al.	Nov 2003	B1
6656114	Poulsen et al.	Dec 2003	B1
6658396	Tang et al.	Dec 2003	B1
6659948	Lebel et al.	Dec 2003	B2
6668196	Villegas et al.	Dec 2003	B1
6675030	Ciuczak et al.	Jan 2004	B2
6676816	Mao et al.	Jan 2004	B2
6687546	Lebel et al.	Feb 2004	B2
6689056	Kilcoyne et al.	Feb 2004	B1
6694191	Starkweather et al.	Feb 2004	B2
6695860	Ward et al.	Feb 2004	B1
6698269	Baber et al.	Mar 2004	B2
6702857	Brauker et al.	Mar 2004	B2
6721582	Trepagnier et al.	Apr 2004	B2
6730025	Platt	May 2004	B1
6731976	Penn et al.	May 2004	B2
6733446	Lebel et al.	May 2004	B2
6735183	O'Toole et al.	May 2004	B2
6740075	Lebel et al.	May 2004	B2
6740518	Duong et al.	May 2004	B1
6741877	Shults et al.	May 2004	B1
6746582	Heller et al.	Jun 2004	B2
6758810	Lebel et al.	Jul 2004	B2
6770030	Schaupp et al.	Aug 2004	B1
6789195	Prihoda et al.	Sep 2004	B1
6790178	Mault et al.	Sep 2004	B1
6804558	Haller et al.	Oct 2004	B2
6809653	Mann et al.	Oct 2004	B1
6810290	Lebel et al.	Oct 2004	B2
6811533	Lebel et al.	Nov 2004	B2
6811534	Bowman, IV et al.	Nov 2004	B2
6813519	Lebel et al.	Nov 2004	B2
6850790	Berner et al.	Feb 2005	B2
6862465	Shults et al.	Mar 2005	B2
6865407	Kimball et al.	Mar 2005	B2
6873268	Lebel et al.	Mar 2005	B2
6878112	Linberg et al.	Apr 2005	B2
6881551	Heller et al.	Apr 2005	B2
6882940	Potts et al.	Apr 2005	B2
6892085	McIvor et al.	May 2005	B2
6895263	Shin et al.	May 2005	B2
6895265	Silver	May 2005	B2
6923763	Kovatchev et al.	Aug 2005	B1
6923764	Aceti et al.	Aug 2005	B2
6931327	Goode, Jr. et al.	Aug 2005	B2
6932894	Mao et al.	Aug 2005	B2
6936006	Sabra	Aug 2005	B2
6940403	Kail, IV	Sep 2005	B2
6941163	Ford et al.	Sep 2005	B2
6942518	Liamos et al.	Sep 2005	B2
6950708	Bowman, IV et al.	Sep 2005	B2
6954662	Freger et al.	Oct 2005	B2
6958705	Lebel et al.	Oct 2005	B2
6968294	Gutta et al.	Nov 2005	B2
6971274	Olin	Dec 2005	B2
6974437	Lebel et al.	Dec 2005	B2
6983176	Gardner et al.	Jan 2006	B2
6990366	Say et al.	Jan 2006	B2
6997907	Safabash et al.	Feb 2006	B2
6998247	Monfre et al.	Feb 2006	B2
6999854	Roth	Feb 2006	B2
7003336	Holker et al.	Feb 2006	B2
7003340	Say et al.	Feb 2006	B2
7003341	Say et al.	Feb 2006	B2
7009511	Mazar et al.	Mar 2006	B2
7015817	Copley et al.	Mar 2006	B2
7016713	Gardner et al.	Mar 2006	B2
7020508	Stivoric et al.	Mar 2006	B2
7022072	Fox et al.	Apr 2006	B2
7022219	Mansouri et al.	Apr 2006	B2
7024236	Ford et al.	Apr 2006	B2
7024245	Lebel et al.	Apr 2006	B2
7025425	Kovatchev et al.	Apr 2006	B2
7027848	Robinson et al.	Apr 2006	B2
7027931	Jones et al.	Apr 2006	B1
7029444	Shin et al.	Apr 2006	B2
7041068	Freeman et al.	May 2006	B2
7041468	Drucker et al.	May 2006	B2
7043305	KenKnight et al.	May 2006	B2
7046153	Oja et al.	May 2006	B2
7052483	Wojcik	May 2006	B2
7056302	Douglas	Jun 2006	B2
7058453	Nelson et al.	Jun 2006	B2
7060031	Webb et al.	Jun 2006	B2
7074307	Simpson et al.	Jul 2006	B2
7081195	Simpson et al.	Jul 2006	B2
7082334	Boute et al.	Jul 2006	B2
7092891	Maus et al.	Aug 2006	B2
7098803	Mann et al.	Aug 2006	B2
7108778	Simpson et al.	Sep 2006	B2
7110803	Shults et al.	Sep 2006	B2
7113821	Sun et al.	Sep 2006	B1
7118667	Lee	Oct 2006	B2
7123950	Mannheimer	Oct 2006	B2
7125382	Zhou et al.	Oct 2006	B2
7134999	Brauker et al.	Nov 2006	B2
7136689	Shults et al.	Nov 2006	B2
7153265	Vachon	Dec 2006	B2
7155290	Von Arx et al.	Dec 2006	B2
7167818	Brown	Jan 2007	B2
7171274	Starkweather et al.	Jan 2007	B2
7179226	Crothall et al.	Feb 2007	B2
7190988	Say et al.	Mar 2007	B2
7192450	Brauker et al.	Mar 2007	B2
7198606	Boecker et al.	Apr 2007	B2
7203549	Schommer et al.	Apr 2007	B2
7207974	Safabash et al.	Apr 2007	B2
7225535	Feldman et al.	Jun 2007	B2
7226442	Sheppard et al.	Jun 2007	B2
7226978	Tapsak et al.	Jun 2007	B2
7228182	Healy et al.	Jun 2007	B2
7237712	DeRocco et al.	Jul 2007	B2
7258673	Racchini et al.	Aug 2007	B2
7267665	Steil et al.	Sep 2007	B2
7276029	Goode, Jr. et al.	Oct 2007	B2
7278983	Ireland et al.	Oct 2007	B2
7286894	Grant et al.	Oct 2007	B1
7295867	Berner et al.	Nov 2007	B2
7299082	Feldman et al.	Nov 2007	B2
7310544	Brister et al.	Dec 2007	B2
7317938	Lorenz et al.	Jan 2008	B2
7318816	Bobroff et al.	Jan 2008	B2
7324850	Persen et al.	Jan 2008	B2
7335294	Heller et al.	Feb 2008	B2
7347819	Lebel et al.	Mar 2008	B2
7354420	Steil et al.	Apr 2008	B2
7364592	Carr-Brendel et al.	Apr 2008	B2
7366556	Brister et al.	Apr 2008	B2
7379765	Petisce et al.	May 2008	B2
7384397	Zhang et al.	Jun 2008	B2
7387010	Sunshine et al.	Jun 2008	B2
7399277	Saidara et al.	Jul 2008	B2
7402153	Steil et al.	Jul 2008	B2
7404796	Ginsberg	Jul 2008	B2
7419573	Gundel	Sep 2008	B2
7424318	Brister et al.	Sep 2008	B2
7460898	Brister et al.	Dec 2008	B2
7467003	Brister et al.	Dec 2008	B2
7468125	Kraft et al.	Dec 2008	B2
7471972	Rhodes et al.	Dec 2008	B2
7474992	Ariyur	Jan 2009	B2
7492254	Bandy et al.	Feb 2009	B2
7494465	Brister et al.	Feb 2009	B2
7497827	Brister et al.	Mar 2009	B2
7519408	Rasdal et al.	Apr 2009	B2
7547281	Hayes et al.	Jun 2009	B2
7565197	Haubrich et al.	Jul 2009	B2
7569030	Lebel et al.	Aug 2009	B2
7574266	Dudding 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
7602310	Mann et al.	Oct 2009	B2
7604178	Stewart	Oct 2009	B2
7613491	Boock et al.	Nov 2009	B2
7615007	Shults et al.	Nov 2009	B2
7618369	Hayter et al.	Nov 2009	B2
7630748	Budiman	Dec 2009	B2
7632228	Brauker et al.	Dec 2009	B2
7635594	Holmes et al.	Dec 2009	B2
7637868	Saint et al.	Dec 2009	B2
7640048	Dobbles et al.	Dec 2009	B2
7651596	Petisce et al.	Jan 2010	B2
7651845	Doyle, III et al.	Jan 2010	B2
7653425	Hayter et al.	Jan 2010	B2
7654956	Brister et al.	Feb 2010	B2
7657297	Simpson et al.	Feb 2010	B2
7659823	Killian et al.	Feb 2010	B1
7668596	Von Arx et al.	Feb 2010	B2
7699775	Desai et al.	Apr 2010	B2
7699964	Feldman et al.	Apr 2010	B2
7711402	Shults et al.	May 2010	B2
7713574	Brister et al.	May 2010	B2
7715893	Kamath et al.	May 2010	B2
7736310	Taub et al.	Jun 2010	B2
7741734	Joannopoulos et al.	Jun 2010	B2
7766829	Sloan et al.	Aug 2010	B2
7768387	Fennell et al.	Aug 2010	B2
7771352	Shults et al.	Aug 2010	B2
7774145	Brauker et al.	Aug 2010	B2
7778680	Goode et al.	Aug 2010	B2
7779332	Karr et al.	Aug 2010	B2
7782192	Jeckelmann et al.	Aug 2010	B2
7783333	Brister et al.	Aug 2010	B2
7791467	Mazar et al.	Sep 2010	B2
7792562	Shults et al.	Sep 2010	B2
7811231	Jin et al.	Oct 2010	B2
7813809	Strother et al.	Oct 2010	B2
7826981	Goode, Jr. et al.	Nov 2010	B2
7831310	Lebel et al.	Nov 2010	B2
7860574	Von Arx et al.	Dec 2010	B2
7882611	Shah et al.	Feb 2011	B2
7889069	Fifolt et al.	Feb 2011	B2
7899511	Shults et al.	Mar 2011	B2
7899545	John	Mar 2011	B2
7905833	Brister et al.	Mar 2011	B2
7912674	Killoren Clark et al.	Mar 2011	B2
7914450	Goode, Jr. et al.	Mar 2011	B2
7916013	Stevenson	Mar 2011	B2
7920906	Goode et al.	Apr 2011	B2
7928850	Hayter et al.	Apr 2011	B2
7938797	Estes	May 2011	B2
7941200	Weinert et al.	May 2011	B2
7946985	Mastrototaro et al.	May 2011	B2
7955258	Goscha et al.	Jun 2011	B2
7970448	Shults et al.	Jun 2011	B2
7972296	Braig et al.	Jul 2011	B2
7974672	Shults et al.	Jul 2011	B2
7976466	Ward et al.	Jul 2011	B2
7978063	Baldus et al.	Jul 2011	B2
7996158	Hayter et al.	Aug 2011	B2
7999674	Kamen	Aug 2011	B2
8005524	Brauker et al.	Aug 2011	B2
8010174	Goode et al.	Aug 2011	B2
8010256	Oowada	Aug 2011	B2
8072310	Everhart	Dec 2011	B1
8090445	Ginggen	Jan 2012	B2
8093991	Stevenson et al.	Jan 2012	B2
8094009	Allen et al.	Jan 2012	B2
8098159	Batra et al.	Jan 2012	B2
8098160	Howarth et al.	Jan 2012	B2
8098161	Lavedas	Jan 2012	B2
8098201	Choi et al.	Jan 2012	B2
8098208	Ficker et al.	Jan 2012	B2
8102021	Degani	Jan 2012	B2
8102154	Bishop et al.	Jan 2012	B2
8102263	Yeo et al.	Jan 2012	B2
8102789	Rosar et al.	Jan 2012	B2
8103241	Young et al.	Jan 2012	B2
8103325	Swedlow et al.	Jan 2012	B2
8103471	Hayter	Jan 2012	B2
8111042	Bennett	Feb 2012	B2
8115488	McDowell	Feb 2012	B2
8116681	Baarman	Feb 2012	B2
8116683	Baarman	Feb 2012	B2
8117481	Anselmi et al.	Feb 2012	B2
8120493	Burr	Feb 2012	B2
8124452	Sheats	Feb 2012	B2
8130093	Mazar et al.	Mar 2012	B2
8131351	Kalgren et al.	Mar 2012	B2
8131365	Zhang et al.	Mar 2012	B2
8131565	Dicks et al.	Mar 2012	B2
8132037	Fehr et al.	Mar 2012	B2
8135352	Langsweirdt et al.	Mar 2012	B2
8136735	Arai et al.	Mar 2012	B2
8138925	Downie et al.	Mar 2012	B2
8140160	Pless et al.	Mar 2012	B2
8140168	Olson et al.	Mar 2012	B2
8140299	Siess	Mar 2012	B2
8140312	Hayter et al.	Mar 2012	B2
8150321	Winter et al.	Apr 2012	B2
8150516	Levine et al.	Apr 2012	B2
8179266	Hermle	May 2012	B2
8192394	Estes et al.	Jun 2012	B2
8216138	McGarraugh et al.	Jul 2012	B1
8239166	Hayter et al.	Aug 2012	B2
8255026	Al-Ali	Aug 2012	B1
8260558	Hayter et al.	Sep 2012	B2
8282549	Brauker et al.	Oct 2012	B2
8374668	Hayter et al.	Feb 2013	B1
8376945	Hayter et al.	Feb 2013	B2
8409093	Bugler	Apr 2013	B2
8444560	Hayter et al.	May 2013	B2
8461985	Fennell et al.	Jun 2013	B2
8484005	Hayter et al.	Jul 2013	B2
8560038	Hayter et al.	Oct 2013	B2
8571808	Hayter	Oct 2013	B2
8583205	Budiman et al.	Nov 2013	B2
8597570	Terashima et al.	Dec 2013	B2
8600681	Hayter et al.	Dec 2013	B2
8612163	Hayter et al.	Dec 2013	B2
8682615	Hayter et al.	Mar 2014	B2
8710993	Hayter et al.	Apr 2014	B2
8834366	Hayter et al.	Sep 2014	B2
8845536	Brauker et al.	Sep 2014	B2
9060719	Hayter et al.	Jun 2015	B2
9289179	Hayter et al.	Mar 2016	B2
9398872	Hayter et al.	Jul 2016	B2
9439586	Bugler	Sep 2016	B2
9483608	Hayter et al.	Nov 2016	B2
9558325	Hayter et al.	Jan 2017	B2
20010037366	Webb et al.	Nov 2001	A1
20020016534	Trepagnier et al.	Feb 2002	A1
20020019022	Dunn et al.	Feb 2002	A1
20020042090	Heller et al.	Apr 2002	A1
20020054320	Ogino	May 2002	A1
20020065454	Lebel et al.	May 2002	A1
20020068860	Clark	Jun 2002	A1
20020072784	Sheppard et al.	Jun 2002	A1
20020095076	Krausman et al.	Jul 2002	A1
20020103499	Perez et al.	Aug 2002	A1
20020106709	Potts et al.	Aug 2002	A1
20020117639	Paolini et al.	Aug 2002	A1
20020120186	Keimel	Aug 2002	A1
20020128594	Das et al.	Sep 2002	A1
20020147135	Schnell	Oct 2002	A1
20020161288	Shin et al.	Oct 2002	A1
20020169635	Shillingburg	Nov 2002	A1
20030004403	Drinan et al.	Jan 2003	A1
20030023317	Brauker et al.	Jan 2003	A1
20030023461	Quintanilla et al.	Jan 2003	A1
20030028089	Galley et al.	Feb 2003	A1
20030032077	Itoh et al.	Feb 2003	A1
20030032867	Crothall et al.	Feb 2003	A1
20030032874	Rhodes et al.	Feb 2003	A1
20030042137	Mao et al.	Mar 2003	A1
20030050546	Desai et al.	Mar 2003	A1
20030054428	Monfre et al.	Mar 2003	A1
20030060692	Ruchti et al.	Mar 2003	A1
20030060753	Starkweather et al.	Mar 2003	A1
20030065308	Lebel et al.	Apr 2003	A1
20030100040	Bonnecaze et al.	May 2003	A1
20030100821	Heller et al.	May 2003	A1
20030114897	Von Arx et al.	Jun 2003	A1
20030125612	Fox et al.	Jul 2003	A1
20030130616	Steil et al.	Jul 2003	A1
20030134347	Heller et al.	Jul 2003	A1
20030147515	Kai et al.	Aug 2003	A1
20030168338	Gao et al.	Sep 2003	A1
20030176933	Lebel et al.	Sep 2003	A1
20030187338	Say et al.	Oct 2003	A1
20030191377	Robinson et al.	Oct 2003	A1
20030199744	Buse et al.	Oct 2003	A1
20030199790	Boecker et al.	Oct 2003	A1
20030208113	Mault et al.	Nov 2003	A1
20030212317	Kovatchev et al.	Nov 2003	A1
20030212379	Bylund et al.	Nov 2003	A1
20030216630	Jersey-Willuhn et al.	Nov 2003	A1
20030217966	Tapsak et al.	Nov 2003	A1
20040010186	Kimball et al.	Jan 2004	A1
20040010207	Flaherty et al.	Jan 2004	A1
20040011671	Shults et al.	Jan 2004	A1
20040024553	Monfre et al.	Feb 2004	A1
20040039298	Abreu	Feb 2004	A1
20040040840	Mao et al.	Mar 2004	A1
20040041749	Dixon	Mar 2004	A1
20040045879	Shults et al.	Mar 2004	A1
20040054263	Moerman et al.	Mar 2004	A1
20040063435	Sakamoto et al.	Apr 2004	A1
20040064068	DeNuzzio et al.	Apr 2004	A1
20040099529	Mao et al.	May 2004	A1
20040106858	Say et al.	Jun 2004	A1
20040111017	Say et al.	Jun 2004	A1
20040117204	Mazar et al.	Jun 2004	A1
20040122353	Shahmirian et al.	Jun 2004	A1
20040133164	Funderburk et al.	Jul 2004	A1
20040133390	Osorio et al.	Jul 2004	A1
20040135571	Uutela et al.	Jul 2004	A1
20040135684	Steinthal et al.	Jul 2004	A1
20040138588	Saikley et al.	Jul 2004	A1
20040142403	Hetzel et al.	Jul 2004	A1
20040146909	Duong et al.	Jul 2004	A1
20040147872	Thompson	Jul 2004	A1
20040152622	Keith et al.	Aug 2004	A1
20040162678	Hetzel et al.	Aug 2004	A1
20040167464	Ireland et al.	Aug 2004	A1
20040167801	Say et al.	Aug 2004	A1
20040171921	Say et al.	Sep 2004	A1
20040176672	Silver et al.	Sep 2004	A1
20040186362	Brauker et al.	Sep 2004	A1
20040186365	Jin et al.	Sep 2004	A1
20040193020	Chiba et al.	Sep 2004	A1
20040193025	Steil et al.	Sep 2004	A1
20040193090	Lebel et al.	Sep 2004	A1
20040197846	Hockersmith et al.	Oct 2004	A1
20040199056	Husemann et al.	Oct 2004	A1
20040199059	Brauker et al.	Oct 2004	A1
20040204687	Mogensen et al.	Oct 2004	A1
20040204868	Maynard et al.	Oct 2004	A1
20040219664	Heller et al.	Nov 2004	A1
20040225338	Lebel et al.	Nov 2004	A1
20040236200	Say et al.	Nov 2004	A1
20040249253	Racchini et al.	Dec 2004	A1
20040254433	Bandis et al.	Dec 2004	A1
20040254434	Goodnow et al.	Dec 2004	A1
20040260478	Schwamm	Dec 2004	A1
20040267300	Mace	Dec 2004	A1
20050001024	Kusaka et al.	Jan 2005	A1
20050004439	Shin et al.	Jan 2005	A1
20050004494	Perez et al.	Jan 2005	A1
20050010269	Lebel et al.	Jan 2005	A1
20050017864	Tsoukalis	Jan 2005	A1
20050027177	Shin et al.	Feb 2005	A1
20050027180	Goode et al.	Feb 2005	A1
20050027181	Goode et al.	Feb 2005	A1
20050027462	Goode et al.	Feb 2005	A1
20050027463	Goode et al.	Feb 2005	A1
20050031689	Shults et al.	Feb 2005	A1
20050038332	Saidara et al.	Feb 2005	A1
20050043598	Goode, Jr. et al.	Feb 2005	A1
20050049179	Davidson et al.	Mar 2005	A1
20050070774	Addison et al.	Mar 2005	A1
20050070777	Cho et al.	Mar 2005	A1
20050090607	Tapsak et al.	Apr 2005	A1
20050096511	Fox et al.	May 2005	A1
20050096512	Fox et al.	May 2005	A1
20050096516	Soykan et al.	May 2005	A1
20050112169	Brauker et al.	May 2005	A1
20050113648	Yang et al.	May 2005	A1
20050113653	Fox et al.	May 2005	A1
20050113886	Fischell et al.	May 2005	A1
20050114068	Chey et al.	May 2005	A1
20050115832	Simpson et al.	Jun 2005	A1
20050116683	Cheng et al.	Jun 2005	A1
20050121322	Say et al.	Jun 2005	A1
20050131346	Douglas	Jun 2005	A1
20050134731	Lee et al.	Jun 2005	A1
20050137530	Campbell et al.	Jun 2005	A1
20050143635	Kamath et al.	Jun 2005	A1
20050154271	Rasdal et al.	Jul 2005	A1
20050176136	Burd et al.	Aug 2005	A1
20050177398	Watanabe et al.	Aug 2005	A1
20050182306	Sloan	Aug 2005	A1
20050187442	Cho et al.	Aug 2005	A1
20050187720	Goode, Jr. et al.	Aug 2005	A1
20050192494	Ginsberg	Sep 2005	A1
20050192557	Brauker et al.	Sep 2005	A1
20050195930	Spital et al.	Sep 2005	A1
20050197793	Baker, Jr.	Sep 2005	A1
20050199494	Say et al.	Sep 2005	A1
20050203360	Brauker et al.	Sep 2005	A1
20050204134	Von Arx et al.	Sep 2005	A1
20050214892	Kovatchev et al.	Sep 2005	A1
20050239154	Feldman et al.	Oct 2005	A1
20050239156	Drucker et al.	Oct 2005	A1
20050241957	Mao et al.	Nov 2005	A1
20050245795	Goode, Jr. et al.	Nov 2005	A1
20050245799	Brauker et al.	Nov 2005	A1
20050245839	Stivoric et al.	Nov 2005	A1
20050245904	Estes et al.	Nov 2005	A1
20050251033	Scarantino et al.	Nov 2005	A1
20050272985	Kotulla et al.	Dec 2005	A1
20050277164	Drucker et al.	Dec 2005	A1
20050277912	John	Dec 2005	A1
20050287620	Heller et al.	Dec 2005	A1
20060001538	Kraft et al.	Jan 2006	A1
20060001551	Kraft et al.	Jan 2006	A1
20060004270	Bedard et al.	Jan 2006	A1
20060010098	Goodnow et al.	Jan 2006	A1
20060015020	Neale et al.	Jan 2006	A1
20060015024	Brister et al.	Jan 2006	A1
20060016700	Brister et al.	Jan 2006	A1
20060017923	Ruchti 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
20060020300	Nghiem et al.	Jan 2006	A1
20060025663	Talbot et al.	Feb 2006	A1
20060029177	Cranford, Jr. et al.	Feb 2006	A1
20060031094	Cohen et al.	Feb 2006	A1
20060036139	Brister et al.	Feb 2006	A1
20060036140	Brister et al.	Feb 2006	A1
20060036141	Kamath et al.	Feb 2006	A1
20060036142	Brister et al.	Feb 2006	A1
20060036143	Brister et al.	Feb 2006	A1
20060036144	Brister et al.	Feb 2006	A1
20060036145	Brister et al.	Feb 2006	A1
20060058588	Zdeblick	Mar 2006	A1
20060079740	Silver et al.	Apr 2006	A1
20060091006	Wang et al.	May 2006	A1
20060142651	Brister et al.	Jun 2006	A1
20060154642	Scannell	Jul 2006	A1
20060155180	Brister et al.	Jul 2006	A1
20060156796	Burke et al.	Jul 2006	A1
20060166629	Reggiardo	Jul 2006	A1
20060173260	Gaoni et al.	Aug 2006	A1
20060173406	Hayes et al.	Aug 2006	A1
20060173444	Choy et al.	Aug 2006	A1
20060183984	Dobbles et al.	Aug 2006	A1
20060183985	Brister et al.	Aug 2006	A1
20060189851	Tvig et al.	Aug 2006	A1
20060189863	Peyser et al.	Aug 2006	A1
20060193375	Lee et al.	Aug 2006	A1
20060202805	Schulman et al.	Sep 2006	A1
20060211072	Ryan et al.	Sep 2006	A1
20060222566	Brauker et al.	Oct 2006	A1
20060224109	Steil et al.	Oct 2006	A1
20060224141	Rush et al.	Oct 2006	A1
20060229512	Petisce et al.	Oct 2006	A1
20060247508	Fennell	Nov 2006	A1
20060247710	Goetz et al.	Nov 2006	A1
20060247985	Liamos et al.	Nov 2006	A1
20060253296	Liisberg et al.	Nov 2006	A1
20060258929	Goode et al.	Nov 2006	A1
20060272652	Stocker et al.	Dec 2006	A1
20060281985	Ward et al.	Dec 2006	A1
20060287691	Drew	Dec 2006	A1
20060290496	Peeters et al.	Dec 2006	A1
20060293607	Alt et al.	Dec 2006	A1
20070010950	Abensour et al.	Jan 2007	A1
20070016381	Kamath et al.	Jan 2007	A1
20070017983	Frank et al.	Jan 2007	A1
20070027381	Stafford	Feb 2007	A1
20070027507	Burdett et al.	Feb 2007	A1
20070032706	Kamath et al.	Feb 2007	A1
20070032717	Brister et al.	Feb 2007	A1
20070033074	Nitzan et al.	Feb 2007	A1
20070038044	Dobbles et al.	Feb 2007	A1
20070055799	Koehler et al.	Mar 2007	A1
20070060803	Liljeryd et al.	Mar 2007	A1
20070060814	Stafford	Mar 2007	A1
20070060869	Tolle et al.	Mar 2007	A1
20070060979	Strother et al.	Mar 2007	A1
20070066873	Kamath et al.	Mar 2007	A1
20070066956	Finkel	Mar 2007	A1
20070071681	Gadkar et al.	Mar 2007	A1
20070073129	Shah et al.	Mar 2007	A1
20070078320	Stafford	Apr 2007	A1
20070078321	Mazza et al.	Apr 2007	A1
20070078322	Stafford	Apr 2007	A1
20070078323	Reggiardo et al.	Apr 2007	A1
20070078818	Zvitz et al.	Apr 2007	A1
20070093786	Goldsmith et al.	Apr 2007	A1
20070094216	Mathias et al.	Apr 2007	A1
20070100222	Mastrototaro et al.	May 2007	A1
20070106135	Sloan et al.	May 2007	A1
20070118405	Campbell et al.	May 2007	A1
20070124002	Estes et al.	May 2007	A1
20070129621	Kellogg et al.	Jun 2007	A1
20070149875	Ouyang et al.	Jun 2007	A1
20070156033	Causey, III et al.	Jul 2007	A1
20070163880	Woo et al.	Jul 2007	A1
20070168224	Letzt et al.	Jul 2007	A1
20070173706	Neinast et al.	Jul 2007	A1
20070173709	Petisce et al.	Jul 2007	A1
20070173710	Petisce et al.	Jul 2007	A1
20070173761	Kanderian et al.	Jul 2007	A1
20070179349	Hoyme et al.	Aug 2007	A1
20070179352	Randlov et al.	Aug 2007	A1
20070191701	Feldman et al.	Aug 2007	A1
20070191702	Yodfat et al.	Aug 2007	A1
20070202562	Curry et al.	Aug 2007	A1
20070203407	Hoss et al.	Aug 2007	A1
20070203966	Brauker et al.	Aug 2007	A1
20070208244	Brauker et al.	Sep 2007	A1
20070208246	Brauker et al.	Sep 2007	A1
20070213657	Jennewine et al.	Sep 2007	A1
20070228071	Kamen et al.	Oct 2007	A1
20070232878	Kovatchev et al.	Oct 2007	A1
20070232880	Siddiqui et al.	Oct 2007	A1
20070235331	Simpson et al.	Oct 2007	A1
20070244383	Talbot et al.	Oct 2007	A1
20070249922	Peyser et al.	Oct 2007	A1
20070253021	Mehta et al.	Nov 2007	A1
20070255321	Gelber et al.	Nov 2007	A1
20070255348	Holtzclaw	Nov 2007	A1
20070255531	Drew	Nov 2007	A1
20070258395	Jollota et al.	Nov 2007	A1
20070270672	Hayter	Nov 2007	A1
20070271285	Eichorn et al.	Nov 2007	A1
20070282299	Hellwig	Dec 2007	A1
20070285238	Batra	Dec 2007	A1
20070299617	Willis	Dec 2007	A1
20080004515	Jennewine et al.	Jan 2008	A1
20080004601	Jennewine et al.	Jan 2008	A1
20080009692	Stafford	Jan 2008	A1
20080017522	Heller et al.	Jan 2008	A1
20080018433	Pitt-Pladdy	Jan 2008	A1
20080021436	Wolpert et al.	Jan 2008	A1
20080021666	Goode, Jr. et al.	Jan 2008	A1
20080029391	Mao et al.	Feb 2008	A1
20080030369	Mann et al.	Feb 2008	A1
20080033254	Kamath et al.	Feb 2008	A1
20080039702	Hayter et al.	Feb 2008	A1
20080045824	Tapsak et al.	Feb 2008	A1
20080058625	McGarraugh et al.	Mar 2008	A1
20080058773	John	Mar 2008	A1
20080060955	Goodnow	Mar 2008	A1
20080061961	John	Mar 2008	A1
20080064937	McGarraugh et al.	Mar 2008	A1
20080064943	Talbot et al.	Mar 2008	A1
20080071156	Brister et al.	Mar 2008	A1
20080071157	McGarraugh et al.	Mar 2008	A1
20080071158	McGarraugh et al.	Mar 2008	A1
20080071328	Haubrich et al.	Mar 2008	A1
20080081977	Hayter et al.	Apr 2008	A1
20080083617	Simpson et al.	Apr 2008	A1
20080086042	Brister et al.	Apr 2008	A1
20080086044	Brister et al.	Apr 2008	A1
20080086273	Shults et al.	Apr 2008	A1
20080092638	Brenneman et al.	Apr 2008	A1
20080097289	Steil et al.	Apr 2008	A1
20080108942	Brister et al.	May 2008	A1
20080114228	McCluskey et al.	May 2008	A1
20080119705	Patel et al.	May 2008	A1
20080139910	Mastrototaro et al.	Jun 2008	A1
20080154513	Kovatchev et al.	Jun 2008	A1
20080161666	Feldman et al.	Jul 2008	A1
20080167543	Say et al.	Jul 2008	A1
20080167572	Stivoric et al.	Jul 2008	A1
20080172205	Breton et al.	Jul 2008	A1
20080177149	Weinert et al.	Jul 2008	A1
20080177165	Blomquist et al.	Jul 2008	A1
20080182537	Manku et al.	Jul 2008	A1
20080183060	Steil et al.	Jul 2008	A1
20080183061	Goode et al.	Jul 2008	A1
20080183399	Goode et al.	Jul 2008	A1
20080188731	Brister et al.	Aug 2008	A1
20080188796	Steil et al.	Aug 2008	A1
20080189051	Goode et al.	Aug 2008	A1
20080194934	Ray et al.	Aug 2008	A1
20080194935	Brister et al.	Aug 2008	A1
20080194936	Goode et al.	Aug 2008	A1
20080194937	Goode et al.	Aug 2008	A1
20080194938	Brister et al.	Aug 2008	A1
20080195232	Carr-Brendel et al.	Aug 2008	A1
20080195967	Goode et al.	Aug 2008	A1
20080197024	Simpson et al.	Aug 2008	A1
20080200788	Brister et al.	Aug 2008	A1
20080200789	Brister et al.	Aug 2008	A1
20080200791	Simpson et al.	Aug 2008	A1
20080201325	Doniger et al.	Aug 2008	A1
20080208025	Shults et al.	Aug 2008	A1
20080208026	Noujaim et al.	Aug 2008	A1
20080208113	Damiano et al.	Aug 2008	A1
20080214900	Fennell et al.	Sep 2008	A1
20080214910	Buck	Sep 2008	A1
20080214915	Brister et al.	Sep 2008	A1
20080214918	Brister et al.	Sep 2008	A1
20080228051	Shults et al.	Sep 2008	A1
20080228054	Shults et al.	Sep 2008	A1
20080228055	Sher	Sep 2008	A1
20080234663	Yodfat et al.	Sep 2008	A1
20080234943	Ray et al.	Sep 2008	A1
20080235469	Drew	Sep 2008	A1
20080242961	Brister et al.	Oct 2008	A1
20080242963	Essenpreis et al.	Oct 2008	A1
20080254544	Modzelewski et al.	Oct 2008	A1
20080255434	Hayter et al.	Oct 2008	A1
20080255437	Hayter	Oct 2008	A1
20080255438	Saidara et al.	Oct 2008	A1
20080255808	Hayter	Oct 2008	A1
20080256048	Hayter	Oct 2008	A1
20080262469	Brister et al.	Oct 2008	A1
20080269714	Mastrototaro et al.	Oct 2008	A1
20080269723	Mastrototaro et al.	Oct 2008	A1
20080275313	Brister et al.	Nov 2008	A1
20080287761	Hayter	Nov 2008	A1
20080287762	Hayter	Nov 2008	A1
20080287763	Hayter	Nov 2008	A1
20080287764	Rasdal et al.	Nov 2008	A1
20080287765	Rasdal et al.	Nov 2008	A1
20080287766	Rasdal et al.	Nov 2008	A1
20080288180	Hayter	Nov 2008	A1
20080288204	Hayter et al.	Nov 2008	A1
20080294024	Cosentino et al.	Nov 2008	A1
20080296155	Shults et al.	Dec 2008	A1
20080300572	Rankers et al.	Dec 2008	A1
20080306368	Goode et al.	Dec 2008	A1
20080306434	Dobbles et al.	Dec 2008	A1
20080306435	Kamath et al.	Dec 2008	A1
20080306444	Brister et al.	Dec 2008	A1
20080312518	Jina et al.	Dec 2008	A1
20080312841	Hayter	Dec 2008	A1
20080312842	Hayter	Dec 2008	A1
20080312844	Hayter et al.	Dec 2008	A1
20080312845	Hayter et al.	Dec 2008	A1
20080314395	Kovatchev et al.	Dec 2008	A1
20080319085	Wright et al.	Dec 2008	A1
20080319279	Ramsay et al.	Dec 2008	A1
20090005665	Hayter et al.	Jan 2009	A1
20090005666	Shin et al.	Jan 2009	A1
20090005729	Hendrixson et al.	Jan 2009	A1
20090006034	Hayter et al.	Jan 2009	A1
20090006061	Thukral et al.	Jan 2009	A1
20090006133	Weinert et al.	Jan 2009	A1
20090012376	Agus	Jan 2009	A1
20090012379	Goode et al.	Jan 2009	A1
20090018424	Kamath et al.	Jan 2009	A1
20090018425	Ouyang et al.	Jan 2009	A1
20090030293	Cooper et al.	Jan 2009	A1
20090030294	Petisce et al.	Jan 2009	A1
20090033482	Hayter et al.	Feb 2009	A1
20090036747	Hayter et al.	Feb 2009	A1
20090036758	Brauker et al.	Feb 2009	A1
20090036760	Hayter	Feb 2009	A1
20090036763	Brauker et al.	Feb 2009	A1
20090040022	Finkenzeller	Feb 2009	A1
20090043181	Brauker et al.	Feb 2009	A1
20090043182	Brauker et al.	Feb 2009	A1
20090043525	Brauker et al.	Feb 2009	A1
20090043541	Brauker et al.	Feb 2009	A1
20090043542	Brauker et al.	Feb 2009	A1
20090045055	Rhodes et al.	Feb 2009	A1
20090048503	Dalal et al.	Feb 2009	A1
20090054745	Jennewine et al.	Feb 2009	A1
20090054747	Fennell	Feb 2009	A1
20090054748	Feldman et al.	Feb 2009	A1
20090054753	Robinson et al.	Feb 2009	A1
20090055149	Hayter et al.	Feb 2009	A1
20090062633	Brauker et al.	Mar 2009	A1
20090062635	Brauker et al.	Mar 2009	A1
20090062767	VanAntwerp et al.	Mar 2009	A1
20090063402	Hayter	Mar 2009	A1
20090076356	Simpson et al.	Mar 2009	A1
20090076360	Brister et al.	Mar 2009	A1
20090076361	Kamath et al.	Mar 2009	A1
20090082693	Stafford	Mar 2009	A1
20090085768	Patel et al.	Apr 2009	A1
20090085873	Betts et al.	Apr 2009	A1
20090088614	Taub et al.	Apr 2009	A1
20090093687	Telfort et al.	Apr 2009	A1
20090099436	Brister et al.	Apr 2009	A1
20090105554	Stahmann et al.	Apr 2009	A1
20090105560	Solomon	Apr 2009	A1
20090105568	Bugler	Apr 2009	A1
20090105570	Sloan et al.	Apr 2009	A1
20090105571	Fennell et al.	Apr 2009	A1
20090105636	Hayter et al.	Apr 2009	A1
20090112478	Mueller, Jr. et al.	Apr 2009	A1
20090124877	Goode et al.	May 2009	A1
20090124878	Goode et al.	May 2009	A1
20090124879	Brister et al.	May 2009	A1
20090124964	Leach et al.	May 2009	A1
20090131768	Simpson et al.	May 2009	A1
20090131769	Leach et al.	May 2009	A1
20090131776	Simpson et al.	May 2009	A1
20090131777	Simpson et al.	May 2009	A1
20090137886	Shariati et al.	May 2009	A1
20090137887	Shariati et al.	May 2009	A1
20090143659	Li et al.	Jun 2009	A1
20090143660	Brister et al.	Jun 2009	A1
20090149728	Van Antwerp et al.	Jun 2009	A1
20090150186	Cohen et al.	Jun 2009	A1
20090156919	Brister et al.	Jun 2009	A1
20090156924	Shariati et al.	Jun 2009	A1
20090163790	Brister et al.	Jun 2009	A1
20090163791	Brister et al.	Jun 2009	A1
20090163855	Shin et al.	Jun 2009	A1
20090164190	Hayter	Jun 2009	A1
20090164239	Hayter et al.	Jun 2009	A1
20090164251	Hayter	Jun 2009	A1
20090177068	Stivoric et al.	Jul 2009	A1
20090178459	Li et al.	Jul 2009	A1
20090182217	Li et al.	Jul 2009	A1
20090189738	Hermle	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
20090198118	Hayter et al.	Aug 2009	A1
20090203981	Brauker et al.	Aug 2009	A1
20090204341	Brauker et al.	Aug 2009	A1
20090216100	Ebner et al.	Aug 2009	A1
20090216103	Brister et al.	Aug 2009	A1
20090227855	Hill et al.	Sep 2009	A1
20090234200	Husheer	Sep 2009	A1
20090240120	Mensinger et al.	Sep 2009	A1
20090240128	Mensinger et al.	Sep 2009	A1
20090240193	Mensinger et al.	Sep 2009	A1
20090240440	Shurabura et al.	Sep 2009	A1
20090242399	Kamath et al.	Oct 2009	A1
20090242425	Kamath et al.	Oct 2009	A1
20090247855	Boock et al.	Oct 2009	A1
20090247856	Boock et al.	Oct 2009	A1
20090247857	Harper et al.	Oct 2009	A1
20090247931	Damgaard-Sorensen	Oct 2009	A1
20090253973	Bashan et al.	Oct 2009	A1
20090267765	Greene et al.	Oct 2009	A1
20090287073	Boock et al.	Nov 2009	A1
20090287074	Shults et al.	Nov 2009	A1
20090289796	Blumberg	Nov 2009	A1
20090292188	Hoss et al.	Nov 2009	A1
20090296742	Sicurello et al.	Dec 2009	A1
20090298182	Schulat et al.	Dec 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
20100010329	Taub et al.	Jan 2010	A1
20100010331	Brauker et al.	Jan 2010	A1
20100010332	Brauker et al.	Jan 2010	A1
20100016687	Brauker et al.	Jan 2010	A1
20100016698	Rasdal et al.	Jan 2010	A1
20100022855	Brauker et al.	Jan 2010	A1
20100022988	Wochner et al.	Jan 2010	A1
20100030038	Brauker et al.	Feb 2010	A1
20100030053	Goode, Jr. et al.	Feb 2010	A1
20100030484	Brauker et al.	Feb 2010	A1
20100030485	Brauker et al.	Feb 2010	A1
20100036215	Goode, Jr. et al.	Feb 2010	A1
20100036216	Goode, Jr. et al.	Feb 2010	A1
20100036222	Goode, Jr. et al.	Feb 2010	A1
20100036223	Goode, Jr. et al.	Feb 2010	A1
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
20100057040	Hayter	Mar 2010	A1
20100057041	Hayter	Mar 2010	A1
20100057042	Hayter	Mar 2010	A1
20100057044	Hayter	Mar 2010	A1
20100057057	Hayter et al.	Mar 2010	A1
20100063373	Kamath et al.	Mar 2010	A1
20100076283	Simpson et al.	Mar 2010	A1
20100081906	Hayter et al.	Apr 2010	A1
20100081908	Dobbles et al.	Apr 2010	A1
20100081909	Budiman et al.	Apr 2010	A1
20100081910	Brister et al.	Apr 2010	A1
20100081953	Syeda-Mahmood et al.	Apr 2010	A1
20100087724	Brauker et al.	Apr 2010	A1
20100094251	Estes et al.	Apr 2010	A1
20100096259	Zhang et al.	Apr 2010	A1
20100099970	Shults et al.	Apr 2010	A1
20100099971	Shults et al.	Apr 2010	A1
20100105999	Dixon et al.	Apr 2010	A1
20100119693	Tapsak et al.	May 2010	A1
20100121169	Petisce et al.	May 2010	A1
20100141656	Krieftewirth	Jun 2010	A1
20100152554	Steine et al.	Jun 2010	A1
20100160759	Celentano et al.	Jun 2010	A1
20100168538	Keenan et al.	Jul 2010	A1
20100168546	Kamath et al.	Jul 2010	A1
20100174266	Estes	Jul 2010	A1
20100185175	Kamen et al.	Jul 2010	A1
20100190435	Cook et al.	Jul 2010	A1
20100191082	Brister et al.	Jul 2010	A1
20100191085	Budiman	Jul 2010	A1
20100191472	Doniger et al.	Jul 2010	A1
20100198142	Sloan et al.	Aug 2010	A1
20100204557	Kiaie et al.	Aug 2010	A1
20100213080	Celentano et al.	Aug 2010	A1
20100234710	Budiman et al.	Sep 2010	A1
20100240975	Goode et al.	Sep 2010	A1
20100274111	Say et al.	Oct 2010	A1
20100312176	Lauer et al.	Dec 2010	A1
20100313105	Nekoomaram et al.	Dec 2010	A1
20110004085	Mensinger et al.	Jan 2011	A1
20110004276	Blair et al.	Jan 2011	A1
20110024043	Boock et al.	Feb 2011	A1
20110024307	Simpson et al.	Feb 2011	A1
20110027127	Simpson et al.	Feb 2011	A1
20110027453	Boock et al.	Feb 2011	A1
20110027458	Boock et al.	Feb 2011	A1
20110028815	Simpson et al.	Feb 2011	A1
20110028816	Simpson et al.	Feb 2011	A1
20110031986	Bhat et al.	Feb 2011	A1
20110040163	Telson et al.	Feb 2011	A1
20110077490	Simpson et al.	Mar 2011	A1
20110112696	Yodfat et al.	May 2011	A1
20110148905	Simmons et al.	Jun 2011	A1
20110152637	Kateraas et al.	Jun 2011	A1
20110208027	Wagner et al.	Aug 2011	A1
20110257895	Brauker et al.	Oct 2011	A1
20110282327	Kellogg et al.	Nov 2011	A1
20110287528	Fern et al.	Nov 2011	A1
20110289497	Kiaie et al.	Nov 2011	A1
20110320130	Valdes et al.	Dec 2011	A1
20110320167	Budiman	Dec 2011	A1
20120078071	Bohm et al.	Mar 2012	A1
20120108934	Valdes et al.	May 2012	A1
20120165626	Irina et al.	Jun 2012	A1
20120165640	Galley et al.	Jun 2012	A1
20120173200	Breton et al.	Jul 2012	A1
20130035575	Mayou et al.	Feb 2013	A1
20130225959	Bugler	Aug 2013	A1
20130235166	Jones et al.	Sep 2013	A1
20150241407	Ou et al.	Aug 2015	A1

Foreign Referenced Citations (57)

Number	Date	Country
2143172	Jul 2005	CA
2396613	Mar 2008	CA
2413148	Aug 2010	CA
4401400	Jul 1995	DE
0098592	Jan 1984	EP
0127958	Dec 1984	EP
0320109	Jun 1989	EP
0353328	Feb 1990	EP
0390390	Oct 1990	EP
0396788	Nov 1990	EP
0286118	Jan 1995	EP
0724859	Aug 1996	EP
0678308	May 2000	EP
1048264	Nov 2000	EP
1292218	Mar 2003	EP
1077634	Jul 2003	EP
1568309	Aug 2005	EP
1666091	Jun 2006	EP
1703697	Sep 2006	EP
1704893	Sep 2006	EP
1897487	Nov 2009	EP
1897492	Nov 2009	EP
2113864	Nov 2009	EP
1897488	Dec 2009	EP
1681992	Apr 2010	EP
1971396	Aug 2010	EP
2201969	Mar 2011	EP
2153382	Feb 2012	EP
2284773	Feb 2012	EP
2409951	Jul 2005	GB
WO-1993006237	Apr 1993	WO
WO-1996025089	Aug 1996	WO
WO-1996035370	Nov 1996	WO
WO-1997033513	Sep 1997	WO
WO-2000049940	Aug 2000	WO
WO-2000059370	Oct 2000	WO
WO-2000074753	Dec 2000	WO
WO-2001052935	Jul 2001	WO
WO-2001054753	Aug 2001	WO
WO-2002016905	Feb 2002	WO
WO-2003076893	Sep 2003	WO
WO-2003082091	Oct 2003	WO
WO-2004047445	Jun 2004	WO
WO-2005010756	Feb 2005	WO
WO-2005040404	May 2005	WO
WO-2005045744	May 2005	WO
WO-2005119238	Dec 2005	WO
WO-2006024671	Mar 2006	WO
WO-2006032653	Mar 2006	WO
WO-2006051466	May 2006	WO
WO-2006064397	Jun 2006	WO
WO-2006124099	Nov 2006	WO
WO-2007007459	Jan 2007	WO
WO-2007097754	Aug 2007	WO
WO-2008086541	Jul 2008	WO
WO-2010077329	Jul 2010	WO
WO-2011022418	Feb 2011	WO

Non-Patent Literature Citations (222)

Entry
U.S. Appl. No. 14/028,358, Office Action dated Nov. 2, 2016.
U.S. Appl. No. 14/094,721, Office Action dated Nov. 17, 2016.
U.S. Appl. No. 14/223,893, Office Action dated Nov. 14, 2016.
U.S. Appl. No. 14/223,893, Office Action dated Nov. 7, 2016.
Armour, J. C., et al., “Application of Chronic Intravascular Blood Glucose Sensor in Dogs”, Diabetes, vol. 39, 1990, pp. 1519-1526.
Arnold, M. A., et al., “Selectivity Assessment of Noninvasive Glucose Measurements Based on Analysis of Multivariate Calibration Vectors”, Journal of Diabetes Science and Technology, vol. 1, No. 4, 2007, pp. 454-462.
Aussedat, B., et al., “A User-Friendly Method for Calibrating a Subcutaneous Glucose Sensor-Based Hypoglycemic Alarm”, Biosensors & Bioelectronics, vol. 12, No. 11, 1997, pp. 1061-1070.
Bennion, N., et al., “Alternate Site Glucose Testing: A Crossover Design”, Diabetes Technology & Therapeutics, vol. 4, No. 1, 2002, pp. 25-33.
Blank, T. B., et al., “Clinical Results From a Non-Invasive Blood Glucose Monitor”, Optical Diagnostics and Sensing of Biological Fluids and Glucose and Cholesterol Monitoring II, Proceedings of SPIE, vol. 4624, 2002, pp. 1-10.
Boyne, M. S., et al., “Timing of Changes in Interstitial and Venous Blood Glucose Measured With a Continuous Subcutaneous Glucose Sensor”, Diabetes, vol. 52, Nov. 2003, pp. 2790-2794.
Bremer, T. M., et al., “Benchmark Data from the Literature for Evaluation of New Glucose Sensing Technologies”, Diabetes Technology & Therapeutics, vol. 3, No. 3, 2001, pp. 409-418.
Brooks, S. L., et al., “Development of an On-Line Glucose Sensor for Fermentation Monitoring”, Biosensors, vol. 3, 1987/88, pp. 45-56.
Cass, A. E., et al., “Ferrocene-Medicated Enzyme Electrode for Amperometric Determination of Glucose”, Analytical Chemistry, vol. 56, No. 4, 1984, 667-671.
Cheyne, E. H., et al., “Performance of a Continuous Glucose Monitoring System During Controlled Hypoglycaemia in Healthy Volunteers”, Diabetes Technology & Therapeutics, vol. 4, No. 5, 2002, pp. 607-613.
Csoregi, E., et al., “Design and Optimization of a Selective Subcutaneously Implantable Glucose Electrode Based on ‘Wired’ Glucose Oxidase”, Analytical Chemistry, vol. 67, No. 7, 1995, pp. 1240-1244.
El-Khatib, F. H, et al., “Adaptive Closed-Loop Control Provides Blood-Glucose Regulation Using Subcutaneous Insulin and Glucagon Infusion in Diabetic Swine”, Journal of Diabetes Science and Technology, vol. 1, No. 2, 2007, pp. 181-192.
Eren-Oruklu, M., et al., “Estimation of Future Glucose Concentrations with Subject-Specific Recursive Linear Models”, Diabetes Technology & Therapeutics vol. 11(4), 2009, pp. 243-253.
Feldman, B., et al., “A Continuous Glucose Sensor Based on Wired Enzyme™ Technology—Results from a 3-Day Trial in Patients with Type 1 Diabetes”, Diabetes Technology & Therapeutics, vol. 5, No. 5, 2003, pp. 769-779.
Feldman, B., et al., “Correlation of Glucose Concentrations in Interstitial Fluid and Venous Blood During Periods of Rapid Glucose Change”, Abbott Diabetes Care, Inc. Freestyle Navigator Continuous Glucose Monitor Pamphlet, 2004.
Garg, S., et al., “Improvement in Glycemic Excursions with a Transcutaneous, Real-Time Continuous Glucose Sensor”, Diabetes Care, vol. 29, No. 1, 2006, pp. 44-50.
Hovorka, R., et al., “Nonlinear Model Predictive Control of Glucose Concentration in Subjects with Type 1 Diabetes”, Physiological Measurement, vol. 55, Jul. 2004, pp. 905-920.
Isermann, R., “Supervision, Fault-Detection and Fault-Diagnosis Methods—An Introduction”, Control Engineering Practice, vol. 5, No. 5, 1997, pp. 639-652.
Isermann, R., et al., “Trends in the Application of Model-Based Fault Detection and Diagnosis of Technical Processes”, Control Engineering Practice, vol. 5, No. 5, 1997, pp. 709-719.
Johnson, P. C., “Peripheral Circulation”, John Wiley & Sons, 1978, pp. 198.
Jungheim, K., et al., “How Rapid Does Glucose Concentration Change in Daily Life of Patients with Type 1 Diabetes?”, 2002, pp. 250.
Jungheim, K., et al., “Risky Delay of Hypoglycemia Detection by Glucose Monitoring at the Arm”, Diabetes Care, vol. 24, No. 7, 2001, pp. 1303-1304.
Kaplan, S. M., “Wiley Electrical and Electronics Engineering Dictionary”, IEEE Press, 2004, pp. 141, 142, 548, 549.
Kuure-Kinsey, M., et al., “A Dual-Rate Kalman Filter for Continuous Glucose Monitoring”, Proceedings of the 28th IEEE, EMBS Annual International Conference, New York City, 2006, pp. 63-66.
Li, Y., et al., “In Vivo Release From a Drug Delivery MEMS Device”, Journal of Controlled Release, vol. 100, 2004, pp. 211-219.
Lo, B., et al., “Key Technical Challenges and Current Implementations of Body Sensor Networks”, Body Sensor Networks, 2005, pp. 1-5.
Lodwig, V., et al., “Continuous Glucose Monitoring with Glucose Sensors: Calibration and Assessment Criteria”, Diabetes Technology & Therapeutics, vol. 5, No. 4, 2003, pp. 573-587.
Lortz, J., et al., “What is Bluetooth? We Explain the Newest Short-Range Connectivity Technology”, Smart Computing Learning Series, Wireless Computing, vol. 8, Issue 5, 2002, pp. 72-74.
Malin, S. F., et al., “Noninvasive Prediction of Glucose by Near-Infrared Diffuse Reflectance Spectroscopy”, Clinical Chemistry, vol. 45, No. 9, 1999, pp. 1651-1658.
McGarraugh, G., et al., “Glucose Measurements Using Blood Extracted from the Forearm and the Finger”, TheraSense, Inc., 2001, 16 Pages.
McGarraugh, G., et al., “Physiological Influences on Off-Finger Glucose Testing”, Diabetes Technology & Therapeutics, vol. 3, No. 3, 2001, pp. 367-376.
McKean, B. D., et al., “A Telemetry-Instrumentation System for Chronically Implanted Glucose and Oxygen Sensors”, IEEE Transactions on Biomedical Engineering, vol. 35, No. 7, 1988, pp. 526-532.
Morbiducci, U, et al., “Improved Usability of the Minimal Model of Insulin Sensitivity Based On an Automated Approach and Genetic Algorithms for Parameter Estimation”, Clinical Science, vol. 112, 2007, pp. 257-263.
Mougiakakou, et al., “A Real Time Simulation Model of Glucose-Insulin Metabolism for Type 1 Diabetes Patients”, Proceedings of the 2005 IEEE, 2005, pp. 298-301.
Panteleon, A. E., et al., “The Role of the Independent Variable to Glucose Sensor Calibration”, Diabetes Technology & Therapeutics, vol. 5, No. 3, 2003, pp. 401-410.
Parker, R., et al., “Robust H∞ Glucose Control in Diabetes Using a Physiological Model”, AIChE Journal, vol. 46, No. 12, 2000, pp. 2537-2549.
Pickup, J., et al., “Implantable Glucose Sensors: Choosing the Appropriate Sensing Strategy”, Biosensors, vol. 3, 1987/88, pp. 335-346.
Pickup, J., et al., “In Vivo Molecular Sensing in Diabetes Mellitus: An Implantable Glucose Sensor with Direct Electron Transfer”, Diabetologia, vol. 32, 1989, pp. 213-217.
Pishko, M. V., et al., “Amperometric Glucose Microelectrodes Prepared Through Immobilization of Glucose Oxidase in Redox Hydrogels”, Analytical Chemistry, vol. 63, No. 20, 1991, pp. 2268-2272.
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, 1995, E155-E161.
Rodriguez, N., et al., “Flexible Communication and Control Protocol for Injectable Neuromuscular Interfaces”, IEEE Transactions on Biomedical Circuits and Systems, vol. 1, No. 1, 2007, pp. 19-27.
Roe, J. N., et al., “Bloodless Glucose Measurements”, Critical Review in Therapeutic Drug Carrier Systems, vol. 15, Issue 3, 1998, pp. 199-241.
Sakakida, M., et al., “Development of Ferrocene-Mediated Needle-Type Glucose Sensor as a Measure of True Subcutaneous Tissue Glucose Concentrations”, Artificial Organs Today, vol. 2, No. 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.
Salehi, C., et al., “A Telemetry-Instrumentation System for Long-Term Implantable Glucose and Oxygen Sensors”, Analytical Letters, vol. 29, No. 13, 1996, pp. 2289-2308.
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, 1998, pp. 294-299.
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., “In Vivo Characteristics of Needle-Type Glucose Sensor—Measurements of Subcutaneous Glucose Concentrations in Human Volunteers”, Hormone and Metabolic Research Supplement Series, vol. 20, 1988, pp. 17-20.
Shichiri, M., et al., “Membrane Design for Extending the Long-Life of an Implantable Glucose Sensor”, Diabetes Nutrition and Metabolism, vol. 2, 1989, pp. 309-313.
Shichiri, M., et al., “Needle-type Glucose Sensor for Wearable Artificial Endocrine Pancreas”, Implantable Sensors for Closed-Loop Prosthetic Systems, 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, No. 3, 1986, pp. 298-301.
Shichiri, M., et al., “Wearable Artificial Endocrine Pancreas With Needle-Type Glucose Sensor”, The Lancet, 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, No. 10, 1994, pp. 937-942.
Steil, G. M., et al., “Closed-Loop Insulin Delivery—the Path of Physiological Glucose Control”, Advanced Drug Delivery Reviews, vol. 56, 2004, pp. 125-144.
Steil, G. M., et al., “Determination of Plasma Glucose During Rapid Glucose Excursions with a Subcutaneous Glucose Sensor”, Diabetes Technology & Therapeutics, vol. 5, No. 1, 2003, pp. 27-31.
Sternberg, R., et al., “Study and Development of Multilayer Needle-Type Enzyme-Based Glucose Microsensors”, Biosensors, vol. 4, 1988, pp. 27-40.
Thompson, M., et al., “In Vivo Probes: Problems and Perspectives”, Clinical Biochemistry, vol. 19, 1986, pp. 255-261.
Turner, A., et al., “Diabetes Mellitus: Biosensors for Research and Management”, Biosensors, vol. 1, 1985, pp. 85-115.
Updike, S. J., et al., “Principles of Long-Term Fully Implanted Sensors with Emphasis on Radiotelemetric Monitoring of Blood Glucose from Inside a Subcutaneous Foreign Body Capsule (FBC)”, Biosensors in the Body: Continuous in vivo Monitoring, Chapter 4, 1997, pp. 117-137.
Velho, G., et al., “Strategies for Calibrating a Subcutaneous Glucose Sensor”, Biomedica Biochimica Acta, vol. 48, 1989, pp. 957-964.
Wilson, G. S., et al., “Progress Toward the Development of an Implantable Sensor for Glucose”, Clinical Chemistry, vol. 38, No. 9, 1992, pp. 1613-1617.
Canadian Patent Application No. 2,683,930, Examiner's Report dated Aug. 17, 2015.
Canadian Patent Application No. 2,683,930, Examiner's Report dated Jul. 22, 2014.
European Patent Application No. 08745803.0, Extended European Search Report dated Sep. 27, 2012.
European Patent Application No. 08745805.5, Examination Report dated Jan. 30, 2015.
European Patent Application No. 08745805.5, Extended European Search Report dated May 23, 2012.
European Patent Application No. 08745807.1, Extended European Search Report dated Oct. 8, 2012.
European Patent Application No. 08745809.7, Extended European Search Report dated Jul. 2, 2012.
European Patent Application No. 08754499.5, Extended European Search Report dated Sep. 20, 2012.
European Patent Application No. 08796500.0, Examination Report dated Dec. 4, 2014.
European Patent Application No. 08796500.0, Extended European Search Report dated Jan. 14, 2014.
European Patent Application No. 08871628.7, Extended European Search Report dated Oct. 15, 2012.
PCT Application No. PCT/US2008/006247, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority dated Nov. 26, 2009.
PCT Application No. PCT/US2008/006247, International Search Report and Written Opinion of the International Searching Authority dated Sep. 5, 2008.
PCT Application No. PCT/US2008/060277, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority dated Oct. 29, 2009.
PCT Application No. PCT/US2008/060277, International Search Report and Written Opinion of the International Searching Authority dated Sep. 22, 2008.
PCT Application No. PCT/US2008/060279, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority dated Oct. 29, 2009.
PCT Application No. PCT/US2008/060279, International Search Report and Written Opinion of the International Searching Authority dated Jul. 14, 2008.
PCT Application No. PCT/US2008/060281, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority dated Oct. 29, 2009.
PCT Application No. PCT/US2008/060281, International Search Report and Written Opinion of the International Searching Authority dated Sep. 23, 2008.
PCT Application No. PCT/US2008/060282, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority dated Oct. 29, 2009.
PCT Application No. PCT/US2008/060282, International Search Report and Written Opinion of the International Searching Authority dated Jun. 18, 2009.
PCT Application No. PCT/US2008/060284, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority dated Oct. 29, 2009.
PCT Application No. PCT/US2008/060284, International Search Report and Written Opinion of the International Searching Authority dated Sep. 23, 2008.
PCT Application No. PCT/US2008/070923, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority, dated Feb. 11, 2010.
PCT Application No. PCT/US2008/070923, International Search Report and Written Opinion of the International Searching Authority dated Oct. 1, 2008.
PCT Application No. PCT/US2009/032756, International Preliminary Report on Patentability and Written Opinion of the International Searching Authority, dated Aug. 12, 2010.
PCT Application No. PCT/US2009/032756, International Search Report and Written Opinion of the International Searching Authority dated Apr. 7, 2009.
U.S. Appl. No. 11/831,866, Notice of Allowance dated May 26, 2010.
U.S. Appl. No. 11/831,866, Office Action dated Jun. 25, 2009.
U.S. Appl. No. 11/831,866, Supplemental Office Action dated Dec. 9, 2009.
U.S. Appl. No. 11/831,881, Advisory Action dated Aug. 23, 2013.
U.S. Appl. No. 11/831,881, Notice of Allowance dated Jun. 20, 2014.
U.S. Appl. No. 11/831,881, Office Action dated Jun. 21, 2011.
U.S. Appl. No. 11/831,881, Office Action dated Mar. 13, 2014.
U.S. Appl. No. 11/831,881, Office Action dated May 23, 2013.
U.S. Appl. No. 11/831,881, Office Action dated Nov. 17, 2011.
U.S. Appl. No. 11/831,881, Office Action dated Oct. 1, 2012.
U.S. Appl. No. 11/831,895, Advisory Action dated Apr. 22, 2015.
U.S. Appl. No. 11/831,895, Advisory Action dated Aug. 5, 2013.
U.S. Appl. No. 11/831,895, Advisory Action dated Jan. 18, 2012.
U.S. Appl. No. 11/831,895, Advisory Action dated Jan. 25, 2012.
U.S. Appl. No. 11/831,895, Office Action dated Feb. 13, 2015.
U.S. Appl. No. 11/831,895, Office Action dated Jul. 17, 2014.
U.S. Appl. No. 11/831,895, Office Action dated Jul. 20, 2012.
U.S. Appl. No. 11/831,895, Office Action dated Mar. 21, 2016.
U.S. Appl. No. 11/831,895, Office Action dated May 16, 2013.
U.S. Appl. No. 11/831,895, Office Action dated May 25, 2011.
U.S. Appl. No. 11/831,895, Office Action dated Oct. 1, 2013.
U.S. Appl. No. 11/831,895, Office Action dated Oct. 14, 2011.
U.S. Appl. No. 12/024,101, Notice of Allowance dated Jan. 9, 2012.
U.S. Appl. No. 12/024,101, Office Action dated Feb. 17, 2011.
U.S. Appl. No. 12/024,101, Office Action dated Oct. 17, 2011.
U.S. Appl. No. 12/102,839, Advisory Action dated May 1, 2013.
U.S. Appl. No. 12/102,839, Notice of Allowance dated Oct. 30, 2015.
U.S. Appl. No. 12/102,839, Office Action dated Aug. 1, 2013.
U.S. Appl. No. 12/102,839, Office Action dated Aug. 5, 2010.
U.S. Appl. No. 12/102,839, Office Action dated Dec. 14, 2009.
U.S. Appl. No. 12/102,839, Office Action dated Dec. 14, 2012.
U.S. Appl. No. 12/102,839, Office Action dated Dec. 5, 2013.
U.S. Appl. No. 12/102,839, Office Action dated Jan. 25, 2011.
U.S. Appl. No. 12/102,839, Office Action dated Jul. 17, 2015.
U.S. Appl. No. 12/102,839, Office Action dated May 25, 2012.
U.S. Appl. No. 12/102,839, Office Action dated Oct. 27, 2011.
U.S. Appl. No. 12/102,844, Notice of Allowance dated Jan. 10, 2012.
U.S. Appl. No. 12/102,844, Office Action dated Aug. 17, 2011.
U.S. Appl. No. 12/102,847, Advisory Action dated Aug. 27, 2014.
U.S. Appl. No. 12/102,847, Office Action dated Apr. 24, 2014.
U.S. Appl. No. 12/102,847, Office Action dated Aug. 18, 2011.
U.S. Appl. No. 12/102,847, Office Action dated Aug. 3, 2015.
U.S. Appl. No. 12/102,847, Office Action dated Dec. 31, 2015.
U.S. Appl. No. 12/102,847, Office Action dated Feb. 12, 2015.
U.S. Appl. No. 12/102,847, Office Action dated Jan. 10, 2012.
U.S. Appl. No. 12/102,847, Office Action dated Jun. 16, 2014.
U.S. Appl. No. 12/102,855, Office Action dated Aug. 24, 2011.
U.S. Appl. No. 12/102,855, Office Action dated Jan. 10, 2012.
U.S. Appl. No. 12/102,855, Office Action dated Jun. 11, 2014.
U.S. Appl. No. 12/102,855, Office Action dated Mar. 23, 2016.
U.S. Appl. No. 12/102,855, Office Action dated May 13, 2015.
U.S. Appl. No. 12/102,855, Office Action dated Oct. 24, 2014.
U.S. Appl. No. 12/102,855, Office Action dated Sep. 2, 2015.
U.S. Appl. No. 12/102,856, Notice of Allowance dated Feb. 25, 2015.
U.S. Appl. No. 12/102,856, Office Action dated Aug. 17, 2011.
U.S. Appl. No. 12/102,856, Office Action dated Jan. 10, 2012.
U.S. Appl. No. 12/102,856, Office Action dated May 7, 2014.
U.S. Appl. No. 12/102,856, Office Action dated Nov. 25, 2014.
U.S. Appl. No. 12/152,623, Notice of Allowance dated Nov. 3, 2011.
U.S. Appl. No. 12/152,623, Office Action dated May 26, 2011.
U.S. Appl. No. 12/152,636, Advisory Action dated Jan. 19, 2012.
U.S. Appl. No. 12/152,636, Advisory Action dated Jan. 6, 2012.
U.S. Appl. No. 12/152,636, Notice of Allowance dated Jun. 19, 2012.
U.S. Appl. No. 12/152,636, Office Action dated Dec. 27, 2010.
U.S. Appl. No. 12/152,636, Office Action dated Sep. 20, 2011.
U.S. Appl. No. 12/152,648, Notice of Allowance dated Aug. 2, 2013.
U.S. Appl. No. 12/152,648, Office Action dated Aug. 12, 2011.
U.S. Appl. No. 12/152,648, Office Action dated Aug. 29, 2012.
U.S. Appl. No. 12/152,648, Office Action dated Jan. 27, 2012.
U.S. Appl. No. 12/152,648, Office Action dated Mar. 13, 2013.
U.S. Appl. No. 12/152,649, Notice of Allowance dated Jul. 1, 2013.
U.S. Appl. No. 12/152,649, Office Action dated Aug. 5, 2011.
U.S. Appl. No. 12/152,649, Office Action dated Jan. 27, 2012.
U.S. Appl. No. 12/152,649, Office Action dated Nov. 5, 2012.
U.S. Appl. No. 12/152,650, Notice of Allowance dated Jan. 22, 2013.
U.S. Appl. No. 12/152,650, Office Action dated Aug. 11, 2011.
U.S. Appl. No. 12/152,650, Office Action dated Jan. 26, 2012.
U.S. Appl. No. 12/152,650, Office Action dated Jul. 25, 2012.
U.S. Appl. No. 12/152,652, Advisory Action dated Jan. 13, 2012.
U.S. Appl. No. 12/152,652, Notice of Allowance dated May 3, 2012.
U.S. Appl. No. 12/152,652, Office Action dated Jun. 23, 2011.
U.S. Appl. No. 12/152,652, Office Action dated Nov. 1, 2011.
U.S. Appl. No. 12/152,657, Notice of Allowance dated Jul. 10, 2015.
U.S. Appl. No. 12/152,657, Office Action dated Apr. 24, 2015.
U.S. Appl. No. 12/152,657, Office Action dated Aug. 11, 2011.
U.S. Appl. No. 12/152,657, Office Action dated Jan. 26, 2012.
U.S. Appl. No. 12/152,657, Office Action dated Sep. 18, 2014.
U.S. Appl. No. 12/152,662, Advisory Action dated Sep. 3, 2014.
U.S. Appl. No. 12/152,662, Office Action dated Aug. 19, 2011.
U.S. Appl. No. 12/152,662, Office Action dated Aug. 19, 2015.
U.S. Appl. No. 12/152,662, Office Action dated Jan. 11, 2012.
U.S. Appl. No. 12/152,662, Office Action dated Jan. 23, 2015.
U.S. Appl. No. 12/152,662, Office Action dated Jun. 12, 2014.
U.S. Appl. No. 12/152,662, Office Action dated Mar. 9, 2016.
U.S. Appl. No. 12/152,670, Notice of Allowance dated Jun. 20, 2011.
U.S. Appl. No. 12/152,670, Office Action dated Jan. 7, 2011.
U.S. Appl. No. 12/152,673, Advisory Action dated Apr. 9, 2013.
U.S. Appl. No. 12/152,673, Office Action dated Aug. 26, 2011.
U.S. Appl. No. 12/152,673, Office Action dated Jan. 30, 2013.
U.S. Appl. No. 12/152,673, Office Action dated Jan. 5, 2012.
U.S. Appl. No. 12/152,673, Office Action dated Jul. 11, 2012.
U.S. Appl. No. 13/356,598, Notice of Allowance dated Jul. 11, 2013.
U.S. Appl. No. 13/356,598, Office Action dated Aug. 30, 2012.
U.S. Appl. No. 13/356,598, Office Action dated May 2, 2013.
U.S. Appl. No. 13/424,291, Notice of Allowance dated Apr. 24, 2013.
U.S. Appl. No. 13/424,291, Office Action dated Feb. 6, 2013.
U.S. Appl. No. 13/424,291, Office Action dated Jul. 31, 2012.
U.S. Appl. No. 13/567,038, Notice of Allowance dated Nov. 22, 2013.
U.S. Appl. No. 13/567,038, Office Action dated Jun. 6, 2013.
U.S. Appl. No. 13/567,038, Office Action dated Oct. 10, 2013.
U.S. Appl. No. 13/599,847, Notice of Allowance dated Aug. 21, 2013.
U.S. Appl. No. 13/599,847, Office Action dated Jan. 29, 2013.
U.S. Appl. No. 13/898,139, Notice of Allowance dated Sep. 15, 2016.
U.S. Appl. No. 13/898,139, Office Action dated Jan. 21, 2016.
U.S. Appl. No. 13/925,685, Office Action dated May 16, 2016.
U.S. Appl. No. 14/094,721, Office Action dated Feb. 25, 2016.
U.S. Appl. No. 14/106,000, Notice of Allowance dated Apr. 24, 2015.
U.S. Appl. No. 14/106,000, Office Action dated Aug. 26, 2014.
U.S. Appl. No. 14/106,000, Office Action dated Jun. 17, 2014.
U.S. Appl. No. 14/106,000, Office Action dated Nov. 26, 2014.
U.S. Appl. No. 14/472,341, Notice of Allowance dated Mar. 28, 2016.
U.S. Appl. No. 14/472,341, Office Action dated Apr. 10, 2015.
U.S. Appl. No. 14/472,341, Office Action dated Dec. 23, 2014.
U.S. Appl. No. 14/472,341, Office Action dated Oct. 9, 2015.
U.S. Appl. No. 14/741,457, Office Action dated Apr. 8, 2016.
U.S. Appl. No. 14/028,358, Office Action dated Mar. 22, 2017.
U.S. Appl. No. 14/052,381, Office Action dated Feb. 21, 2017.
U.S. Appl. No. 14/094,721, Office Action dated Mar. 17, 2107.
U.S. Appl. No. 14/223,893, Office Action dated Mar. 28, 2017.

Related Publications (1)

	Number	Date	Country
	20170027484 A1	Feb 2017	US

Provisional Applications (1)

	Number	Date	Country
	60917873	May 2007	US

Continuations (2)

	Number	Date	Country
Parent	13898139	May 2013	US
Child	15294683		US
Parent	12152650	May 2008	US
Child	13898139		US

Method and apparatus for providing data processing and control in a medical communication system

Information

Patent Number

Date Filed

Date Issued

Inventors

Original Assignees

Examiners

Agents

CPC

Field of Search

US

International Classifications

Abstract