Systems and methods for processing sensor data

Patent metadata

Field	Value
Publication number	US-10827980-B2
Application number	US-201213473206-A
Country	US
Kind code	B2
Filing date	May 16, 2012
Priority date	Dec 17, 2007
Publication date	Nov 10, 2020
Grant date	Nov 10, 2020

Abstract

Systems and methods for processing sensor data are provided. In some embodiments, systems and methods are provided for calibration of a continuous analyte sensor. In some embodiments, systems and methods are provided for classification of a level of noise on a sensor signal. In some embodiments, systems and methods are provided for determining a rate of change for analyte concentration based on a continuous sensor signal. In some embodiments, systems and methods for alerting or alarming a patient based on prediction of glucose concentration are provided.

First claim

What is claimed is:

1. A method for classifying a level of noise in a signal obtained from a continuous glucose sensor, the method comprising:
receiving a raw signal from a continuous glucose sensor during a sensor session, using electronic circuitry operably connected to the continuous glucose sensor, wherein the raw signal is indicative of the glucose level in a host;
classifying a level of transient, non-glucose related noise in the raw signal into one of a plurality of groups during the sensor session based on one or more noise thresholds, wherein the classifying comprises deriving a noise signal from the raw signal by comparing the raw signal to a smooth or filtered signal, determining a level and/or indicator of noise in the noise signal and comparing the level and/or indicator of noise to one or more noise classification thresholds and/or criteria that are adaptively determined during the sensor session; and
controlling administration of a medicament using a medicament dispensing device responsive to the classifying the level of the transient, non-glucose related noise in the raw signal.

2. The method of claim 1 , further comprising determining a signal strength of the raw signal from the continuous glucose sensor during the sensor session.

3. The method of claim 2 , wherein the determining the signal strength comprises applying a low pass filter to the raw signal.

4. The method of claim 2 , wherein the classifying comprises adaptively determining the one or more noise thresholds and/or criteria based the signal strength of the raw signal.

5. The method of claim 2 , wherein the one or more noise thresholds and/or criteria are based on a percentage of the signal strength.

6. The method of claim 1 , wherein determining the level and/or indicator of noise in the noise signal comprises applying one or more low pass filters to the noise signal.

7. The method of claim 1 , wherein deriving the noise signal comprises obtaining a low-pass filtered signal by applying a low-pass filter to the raw signal and subtracting the low-pass filtered signal from the raw signal.

8. The method of claim 1 , wherein the controlling further comprises outputting information indicative of the noise classification to an external device.

9. The method of claim 1 , wherein the controlling further comprises displaying information indicative of the noise classification on a user interface.

10. The method of claim 1 , further comprising controlling decision making for at least one of displaying, calibrating, alarming, sensor diagnostics or insulin delivery.

11. The method of claim 1 , further comprising controlling a display of rate of change information.

12. The method of claim 1 , further comprising controlling an alarm indicative of at least one of hypoglycemia, hyperglycemia, predicted hypoglycemia, or predicted hyperglycemia.

13. The method of claim 1 , further comprising controlling forming or modifying medicament therapy instructions based on the noise classification and wherein the medicament delivery device administers the medicament according to the formed or modified medicament therapy instructions.

14. The method of claim 1 , wherein the classifying into a plurality of groups classifies the level of noise into three groups.

15. The method of claim 1 , further comprising using hysteresis in the classifying step to avoid waver between noise level classifications.

16. A system for classifying a level of noise in a signal obtained from a continuous glucose sensor, the system comprising:
a continuous glucose sensor configured to provide a signal indicative of a glucose concentration in a host;
a computer system operably connected to the continuous glucose sensor and configured to receive a raw signal from the continuous glucose sensor during a sensor session, to derive a noise signal from the raw signal by comparing the raw signal to a smooth or filtered signal, to classify a level of transient, non-glucose related noise in the raw signal into one of a plurality of groups during the sensor session based on one or more noise thresholds by determining a level and/or indicator of noise in the noise signal and comparing the level and/or indicator of noise to one or more noise classification thresholds and/or criteria, and to control an output responsive to classification of the level of the transient, non-glucose related noise in the raw signal, wherein the one or more noise thresholds and/or criteria are adaptively determined during the sensor session; and
a medicament delivery pump configured to receive the output and administer medicament to the host responsive to the output.

17. The system of claim 16 , wherein the computer system is configured to determine a signal strength of the raw signal from the continuous glucose sensor during the sensor session.

18. The system of claim 17 , wherein the computer system is configured to determine the signal strength by applying a low pass filter to the raw signal.

19. The system of claim 17 , wherein the computer system is configured to adaptively determine the one or more noise thresholds and/or criteria for classification of the level of noise in the raw signal based on the signal strength of the raw signal.

20. The system of claim 17 , wherein the computer system is configured to adaptively determine the one or more noise thresholds and/or criteria for classification of the level of noise on the raw signal based on a percentage of the signal strength.

21. The system of claim 16 , wherein the computer system is configured to determine the level and/or indicator of noise in the noise signal by applying one or more low pass filters to the noise signal.

22. The system of claim 16 , wherein the computer system is configured to obtain a low-pass filtered signal by applying a low-pass filter to the raw signal, and to derive the noise signal by subtracting the low-pass filtered signal from the raw signal.

23. The system of claim 16 , wherein the output comprises information indicative of the noise classification.

24. The system of claim 16 , wherein the computer system comprises a user interface, and wherein the output is displayed via the user interface.

25. The system of claim 16 , wherein the computer system is further configured to at least one of display, calibrate, alarm, perform sensor diagnostics or deliver insulin based on the output.

26. The system of claim 16 , wherein the computer system is further configured to control a display of rate of change information based on the output.

27. The system of claim 16 , wherein the computer system is further configured to control an alarm indicative of at least one of hypoglycemia, hyperglycemia, predicted hypoglycemia, or predicted hyperglycemia based on the output.

28. The system of claim 16 , wherein the output comprises medicament therapy instructions.

29. The system of claim 16 , wherein the computer system is further configured to classify the level of noise into three groups.

30. The system of claim 16 , wherein the computer system is further configured to use a first predetermined condition to detect an onset of a noise episode, and use a second predetermined condition to detect an offset of the noise episode, and wherein the first predetermined condition is different from the second predetermined condition.

Assignees

• Shariati Mohammad Ali
• Kamath Apurv Ullas
• Dobbles J Michael
• Mahalingam Aarthi
• Dexcom Inc

Inventors

• Shariati Mohammad Ali
• Kamath Apurv Ullas
• Dobbles J Michael
• Mahalingam Aarthi

Classifications

• A61B5/1495

  Calibrating or testing of in-vivo probes · CPC title

• A61B5/14542

  for measuring blood gases (A61B5/14551 takes precedence) · CPC title

• A61B5/01

  Measuring temperature of body parts {; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue} (clinical contact thermometers G01K13/20) · CPC title

• G16H20/17 Primary

  delivered via infusion or injection · CPC title

• A61B2562/085

  combined with means for recording calibration data · CPC title