END OF LIFE DETECTION FOR ANALYTE SENSORS

• US 20160302701A1
• Filed: 06/28/2016
• Published: 10/20/2016
• Est. Priority Date: 01/03/2013
• Status: Abandoned Application

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Bhavaraju, Naresh C., Garcia, Arturo, Hampapuram, Hari, Kamath, Apurv Ullas, Mahalingam, Aarthi, Sokolovskyy, Dmytro, Vanslyke, Stephen J.
• Application Number:
  US15/195,613
• Publication Number:
  US 20160302701A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/0266 for monitoring or limiting apparatus function
• CPC Class Codes: A61B 2560/0276 Determining malfunction
• CPC Class Codes: A61B 2560/028 Arrangements to prevent overuse, e.g. by counting the number of uses
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: G01M 99/008 by doing functionality tests
• CPC Class Codes: G01N 33/48792 Data management, e.g. communication with processing unit for in vivo diagnostics A61B5/0002; transmission systems for measured values G08C
• CPC Class Codes: G01N 33/49 Blood chemical methods for determining blood cell populations G01N33/5094; chemical analysis of blood groups or blood types G01N33/80
• CPC Class Codes: G01N 33/66 involving blood sugars, e.g. galactose
• CPC Class Codes: G16C 20/80 Data visualisation
• CPC Class Codes: G16C 99/00 Subject matter not provided for in other groups of this subclass

Abstract

Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes evaluating a plurality of risk factors using an end of life function to determine an end of life status of the sensor and providing an output related to the end of life status of the sensor. The plurality of risk factors may be selected from the list including the number of days the sensor has been in use, whether there has been a decrease in signal sensitivity, whether there is a predetermined noise pattern, whether there is a predetermined oxygen concentration pattern, and error between reference BG values and EGV sensor values.

Claims

1. A system for determining if a continuous analyte sensor has been reused, the system comprising sensor electronics configured to be operably connected to a continuous analyte sensor, the sensor electronics configured to:

evaluate a plurality of risk factors associated with end of life symptoms of the sensor;

determine an end of life status of the sensor by performing an end of life function based on the evaluation of the plurality of risk factors; and

provide an output related to sensor reuse of the sensor within a predetermined time frame after sensor initialization if the end of life status meets one or more predetermined sensor reuse criteria,

wherein the plurality of risk factors comprise at least two risk factors selected from the group consisting of a number of days the sensor has been in use, a rate of change of sensor sensitivity, end of life noise, oxygen concentration, glucose patterns, error between reference values, and sensor values in clinical units.

2. The system of claim 1, wherein one of the at least two risk factors comprises a rate of change of sensor sensitivity, and wherein the sensor electronics are configured to evaluate a rate of change of sensor sensitivity by evaluating at least one of a direction of rate of change of sensor sensitivity, an amplitude of rate of change of sensor sensitivity, a derivative of rate of change of sensor sensitivity, or a comparison of the rate of change of sensor sensitivity to a priori rate of change sensitivity information.

3. The system of claim 1, wherein one of the at least two risk factors comprises end of life noise, and wherein the sensor electronics are configured to evaluate end of life noise by evaluating at least one of duration of noise, a magnitude of noise, a history of noise, a spectral content of a signal from the sensor, spikes in the signal from the sensor, skewness of the signal of the sensor, or noise patterns by pattern recognition algorithms.

4. The system of claim 1, wherein one of the at least two risk factors comprises end of life noise, and wherein the sensor electronics are configured to evaluate end of life noise by evaluating at least two of duration of noise, a magnitude of noise, a history of noise, a spectral content of a signal from the sensor, spikes in the signal from the sensor, skewness of the signal of the sensor, or noise patterns by pattern recognition algorithms.

5. The system of claim 1, wherein one of the at least two risk factors comprises glucose patterns, and wherein the sensor electronics are configured to evaluate glucose patterns by evaluating at least one of mean glucose, glucose variability, peak-to-peak glucose excursions, or expected versus unexpected glucose trends based on timing.

6. The system of claim 1, wherein one of the at least two risk factors comprises error between reference values and sensor values in clinical units, and wherein the sensor electronics are configured to evaluate error between reference values and sensor values in clinical units by evaluating at least one of a direction of error between reference values and sensor values in clinical units, or a linearity of the sensor and an error at calibration.

7. The system of claim 1, wherein the sensor electronics comprise a processor module, the processor module comprising instructions stored in computer memory, wherein the instructions, when executed by the processor module, cause the sensor electronics to perform the evaluating and the providing.

8. The system of claim 1, wherein the sensor electronics are configured to provide an output by disabling display of sensor data responsive to the end of life status meeting the one or more predetermined sensor reuse criteria.

9. The system of claim 1, wherein the sensor initialization is determined by the sensor electronics in response to an event that indicates a new sensor has been implanted, including one or more of:

a user providing input to a sensor system that a new sensor has been implanted, the sensor system detecting electrical connection to a sensor, a predetermined amount of time transpiring since the system prompted a user to use a new sensor.

10. The system of claim 1, wherein the sensor electronics are configured to collect a data point or series of data points from the analyte sensor being used, and wherein the evaluation of a plurality of risk factors associated with end of life symptoms of the sensor comprises evaluation of the collected data point or series of data points.

11. A method for determining if a continuous analyte sensor has been reused, comprising:

evaluating a plurality of risk factors associated with end of life symptoms of a sensor;

determining an end of life status of the sensor by performing an end of life function based on the evaluation of the plurality of risk factors; and

providing an output related to a sensor reuse within a predetermined time frame after sensor initialization if the end of life status meets one or more predetermined sensor reuse criteria,

wherein the plurality of risk factors comprise at least two risk factors selected from the group consisting of a number of days the sensor has been in use, a rate of change of sensor sensitivity, end of life noise, oxygen concentration, glucose patterns, error between reference values, and sensor values in clinical units.

12. The method of claim 11, wherein one of the at least two risk factors comprises a rate of change of sensor sensitivity, and wherein evaluating a rate of change of sensor sensitivity comprises evaluating at least one of a direction of rate of change of sensor sensitivity, an amplitude of rate of change of sensor sensitivity, a derivative of rate of change of sensor sensitivity or a comparison of the rate of change of sensor sensitivity to a priori rate of change sensitivity information.

13. The method of claim 11, wherein one of the at least two risk factors comprises end of life noise, and wherein evaluating end of life noise comprises evaluating at least one of duration of noise, a magnitude of noise, a history of noise, a spectral content of a signal from the sensor, spikes in the signal from the sensor, skewness of the signal of the sensor or noise patterns by pattern recognition algorithms.

14. The method of claim 11, wherein one of the at least two risk factors comprises end of life noise, and wherein evaluating end of life noise comprises evaluating at least two of duration of noise, a magnitude of noise, a history of noise, a spectral content of a signal from the sensor, spikes in the signal from the sensor, skewness of the signal of the sensor or noise patterns by pattern recognition algorithms.

15. The method of claim 11, wherein one of the at least two risk factors comprises glucose patterns, and wherein evaluating glucose patterns comprises evaluating at least one of mean glucose, glucose variability, peak-to-peak glucose excursions, or expected versus unexpected glucose trends based on timing.

16. The method of claim 11, wherein one of the at least two risk factors comprises error between reference values and sensor values in clinical units, and wherein evaluating error between reference values and sensor values in clinical units comprises evaluating at least one of a direction of error between reference values and sensor values in clinical units, a linearity of the sensor, or an error at calibration.

17. The method of claim 11, wherein the providing an output comprises disabling display of sensor data responsive to the end of life status meeting the one or more predetermined sensor reuse criteria.

18. The method of claim 11, comprising determining sensor initialization in response to an event that indicates a new sensor has been implanted, including one or more of:

a user providing input to a sensor system that a new sensor has been implanted, the sensor system detecting electrical connection to a sensor, a predetermined amount of time transpiring since the system prompted a user to use a new sensor.

19. The method of claim 11, comprising collecting a data point or series of data points from the analyte sensor being used, wherein the evaluating a plurality of risk factors associated with end of life symptoms of the sensor comprises evaluating the collected data point or series of data points.

20. The method of claim 19, comprising performing an initial calibration using the collected data to produce an initial calibration.