SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM

• US 20100235106A1
• Filed: 05/25/2010
• Published: 09/16/2010
• Est. Priority Date: 08/22/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Brauker, James H., Carr-Brendel, Victoria, Thrower, James Patrick, Kamath, Apurv U., Goode, Paul V. JR.
• Granted Patent: US 8,073,520 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2562/0247 Pressure sensors
• CPC Class Codes: A61B 2562/0271 Thermal or temperature sensors
• CPC Class Codes: A61B 2562/08 Sensors provided with means for identification, e.g. barcodes or memory chips
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/1473 invasive, e.g. introduced into the body by a catheter A61B5/1482 takes precedence
• CPC Class Codes: A61B 5/14865 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick

Abstract

Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.

Claims

1. A method for processing continuous glucose sensor data, the method comprising:

receiving sensor data generated by a glucose sensor during a first time period;

evaluating the sensor data; and

selectively applying at least one of a plurality of predetermined signal estimation algorithm factors to the sensor data based on the evaluation of the sensor data.

2. The method of claim 1, wherein the plurality of predetermined signal estimation algorithm factors comprises a plurality of predetermined parameters that are selectively applied to a predetermined algorithm.

3. The method of claim 2, wherein the predetermined algorithm comprises at least one filter selected from the group consisting of a non-recursive filter and a recursive filter.

4. The method of claim 1, wherein the plurality of predetermined signal estimation algorithm factors comprises a plurality of different predetermined algorithms.

5. The method of claim 4, wherein the plurality of different predetermined algorithms comprises at least one filter selected from the group consisting of a non-recursive filter and a recursive filter.

6. The method of claim 1, wherein selectively applying the at least one of the plurality of predetermined signal estimation algorithm factors is performed substantially continually.

7. The method of claim 1, wherein evaluating the sensor data comprises evaluating a rate of change of the sensor data.

8. The method of claim 7, wherein selectively applying the at least one of the plurality of predetermined signal estimation algorithm factors to the sensor data is based on the rate of change.

9. The method of claim 1, wherein evaluating the sensor data comprises detecting transient non-glucose related signal artifacts in the data stream.

10. The method of claim 9, wherein detecting transient non-glucose related signal artifacts in the data stream comprises determining a severity of the signal artifacts.

11. The method of claim 10, wherein selectively applying the at least one of the plurality of predetermined signal estimation algorithm factors to the sensor data is based on the severity of the signal artifacts.

12. The method of claim 10, wherein determining the severity of the signal artifacts is based on at least one factor selected from the group consisting of an amplitude of the signal artifacts, a duration of the signal artifacts, a rate of change of the signal artifacts, and a frequency content of the signal artifacts.

13. The method of claim 10, wherein selectively applying the at least one of the plurality of predetermined signal estimation algorithm factors is initiated when the severity of signal artifacts meets a first predetermined criterion.

14. The method of claim 13, wherein selectively applying the at least one of the plurality of predetermined signal estimation algorithm factors is terminated when the severity of signal artifacts meets a second predetermined criterion, wherein the second predetermined criterion is different from the first predetermined criterion or the same as the first predetermined criterion.

15. The method of claim 1, further comprising:

receiving sensor data generated by the glucose sensor during a second time period;

evaluating the sensor data generated during the second time period; and

selectively applying at least one of the plurality of predetermined signal algorithm factors to the sensor data generated during the second time period based on the evaluation of the sensor data generated during the second time period,

wherein the at least one predetermined estimation algorithm factor applied to the sensor data generated during the first time period is different than at least one predetermined estimation algorithm factor applied to the sensor data generated during the second time period.

16. A system for processing sensor data obtained from a glucose sensor, the system comprising:

a sensor data module configured to receive sensor data generated by a glucose sensor during a first time period; and

a processor module configured to evaluate the sensor data and to selectively apply at least one of a plurality of predetermined signal estimation algorithm factors to the sensor data based on the evaluation of the sensor data.

17. The system of claim 16, wherein the processor module is configured to selectively apply the at least one of a plurality of predetermined signal estimation algorithm factors to the sensor data by selectively applying a plurality of predetermined parameters to a predetermined algorithm.

18. The system of claim 17, wherein the predetermined algorithm comprises at least one filter selected from the group consisting of a non-recursive filter and a recursive filter.

19. The system of claim 16, wherein the processor module is configured to selectively apply the at least one of the plurality of predetermined signal estimation algorithm factors to the sensor data by selectively applying a plurality of different predetermined algorithms.

20. The system of claim 17, wherein the plurality of different predetermined algorithms comprises at least one filter selected from the group consisting of non-recursive filters and recursive filters.

21. The system of claim 16, wherein the processor module is configured to substantially continually selectively apply at least one of the plurality of predetermined signal estimation algorithm factors.

22. The system of claim 16, wherein the processor module is configured to evaluate the sensor data by evaluating a rate of change of the sensor data.

23. The system of claim 16, wherein the processor module is configured to selectively apply one of the plurality of predetermined signal estimation algorithm factors to the sensor data based on the rate of change.

24. The system of claim 16, wherein the processor module is configured to evaluate the sensor data by detecting transient non-glucose related signal artifacts in the data stream.

25. The system of claim 24, wherein the processor module is configured to determine a severity of the signal artifacts.

26. The system of claim 25, wherein the processor module is configured to selectively apply at least one of the plurality of predetermined signal estimation algorithm factors to the sensor data based on the severity of the signal artifacts.

27. The system of claim 25, wherein the processor module is configured to determine a severity of the signal artifacts based on at least one factor selected from the group consisting of an amplitude of the signal artifacts, a duration of the signal artifacts, a rate of change of the signal artifacts, and a frequency content of the signal artifacts.

28. The system of claim 25, wherein the processor module is configured to initiate the selective application of the at least one of the plurality of predetermined signal estimation algorithm factors when the severity of the signal artifacts meets a first predetermined criterion.

29. The system of claim 28, wherein the processor module is configured to terminate the selective application of the at least one of the plurality of predetermined signal estimation algorithm factors when the severity of the signal artifacts meets a second predetermined criterion, wherein the second predetermined criterion is different from or the same as the first predetermined criterion.