End of life detection for analyte sensors

• US 9,585,609 B2
• Filed: 10/24/2014
• Issued: 03/07/2017
• Est. Priority Date: 01/03/2013
• Status: Active Grant

• 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.
• Primary Examiner(s): Larkin, Daniel S
• Assistant Examiner(s): Megna Fuentes, Anthony W
• Application Number:
  US14/523,323
• Publication Number:
  US 20150046113A1
• Time in Patent Office: 865 Days
• Field of Search: 600/316, 600/319, 600/347, 600364-365, 600323-340, 702/104, 73 101- 189
• 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 based on an end of sensor life evaluation, the system comprising sensor electronics configured to be operably connected to a continuous analyte sensor, the sensor electronics configured to:

evaluate sensor data obtained by the continuous analyte sensor with a plurality of risk factors associated with end of life symptoms of a previously-used sensor, wherein the plurality of risk factors comprise at least two risk factors selected from the group consisting of a rate of change of sensor sensitivity, end of life noise, a magnitude of sensor values in clinical units, analyte patterns, and error between reference values and sensor values in clinical units;

produce a sensor profile of the continuous analyte sensor by performing an end of life function on the evaluated sensor data with the plurality of risk factors, the produced sensor profile including two or more metrics associated with sensor sensitivity, noise, signal magnitude, analyte pattern, or calibration error;

determine a sensor reuse status of the continuous analyte sensor by comparing the sensor profile to a standard profile of a sensor associated with a new sensor session; and

provide an output related to the reuse status of the continuous analyte sensor;

wherein the sensor electronics is configured to disable displaying of sensor data in response to the provided output.

2. The system of claim 1, wherein one of the at least two risk factors comprises the rate of change of sensor sensitivity, and wherein the sensor electronics are configured to evaluate the 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 the end of life noise, and wherein the sensor electronics are configured to evaluate the 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 the end of life noise, and wherein the sensor electronics are configured to evaluate the 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 an analyte sensed by the continuous analyte sensor includes glucose, wherein one of the at least two risk factors comprises the glucose patterns, and wherein the sensor electronics are configured to evaluate the 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 the error between reference values and sensor values in clinical units, and wherein the sensor electronics are configured to evaluate the 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 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.

8. The system of claim 1, wherein the sensor electronics are configured to collect a data point or series of data points from the continuous analyte sensor being used, and perform an initial calibration using the collected data to produce an initial calibration, and wherein evaluation of the sensor data with the plurality of risk factors associated with end of life symptoms of the previously-used sensor comprises evaluation of the initially calibrated data with the plurality of risk factors.

9. A method for determining if a continuous analyte sensor has been reused based on an end of sensor life evaluation, comprising:

evaluating sensor data of the continuous analyte sensor with a plurality of risk factors associated with end of life symptoms of a previously-used sensor, wherein the plurality of risk factors comprise at least two risk factors selected from the group consisting of a rate of change of sensor sensitivity, end of life noise, a magnitude of sensor values in clinical units, analyte patterns, and error between reference values and sensor values in clinical units;

producing a sensor profile of the continuous analyte sensor by performing an end of life function on the evaluated sensor data with the plurality of risk factors, the produced sensor profile including two or more of metrics associated with sensor sensitivity, noise, signal magnitude, analyte pattern, or calibration error;

determining a sensor reuse status of the continuous analyte sensor by comparing the sensor profile to a standard profile of a sensor associated with a new sensor session; and

providing an output related to the sensor reuse status of the continuous analyte sensor;

wherein the providing an output comprises disabling display sensor data.

10. The method of claim 9, wherein one of the at least two risk factors comprises the rate of change of sensor sensitivity, and wherein evaluating the 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.

11. The method of claim 9, wherein one of the at least two risk factors comprises the end of life noise, and wherein evaluating the 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.

12. The method of claim 9, wherein one of the at least two risk factors comprises the end of life noise, and wherein evaluating the 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.

13. The method of claim 9, wherein an analyte sensed by the continuous analyte sensor includes glucose, wherein one of the at least two risk factors comprises the glucose patterns, and wherein evaluating the glucose patterns comprises evaluating at least one of mean glucose, glucose variability, peak-to-peak glucose excursions, or expected versus unexpected glucose strands based on timing.

14. The method of claim 9, wherein one of the at least two risk factors comprises the error between reference values and sensor values in clinical units, and wherein evaluating the 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.

15. The method of claim 9, 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.

16. The method of claim 9, comprising collecting a data point or series of data points from the continuous analyte sensor being used;

and performing an initial calibration using the collected data to produce an initial calibration, wherein the evaluating the sensor data with the plurality of risk factors associated with end of life symptoms of the previously-used sensor comprises evaluating the initially calibrated data with the plurality of risk factors.