SYSTEMS AND METHODS FOR PROCESSING SENSOR DATA

• US 20090192380A1
• Filed: 10/24/2008
• Published: 07/30/2009
• Est. Priority Date: 07/25/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Dobbles, J. Michael, Kamath, Apurv Ullas, Mahalingam, Aarthi, Shariati, Mohammad Ali
• Granted Patent: US 8,423,113 B2
• Time in Patent Office: Days
• US Class Current: 600/365
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/04 Constructional details of apparatus
• CPC Class Codes: A61B 2562/085 combined with means for recording calibration data
• CPC Class Codes: A61B 5/0008 Temperature signals
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• 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 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/6848 Needles
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 : ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/17 : delivered via infusion or injection
• CPC Class Codes: G16H 40/40 : for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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.

Claims

1. A method for classifying a level of noise in a signal obtained from a continuous glucose sensor, the method comprising:

receiving a signal from a continuous glucose sensor; and

classifying a level of noise on the signal.

2. The method of claim 1, wherein the step of classifying comprises applying a low pass filter to the signal to determine a signal strength.

3. The method of claim 2, wherein the step of classifying comprises defining one or more noise thresholds for classification of the level of noise on the signal, wherein the one or more noise thresholds are based at least in part on a percentage of the signal strength.

4. The method of claim 3, wherein the step of classifying comprises applying one or more low pass filters to the noise signal to obtain one or more noise indicators and comparing the noise indicators with the one or more noise thresholds.

5. The method of claim 1, further comprising determining a noise signal from the sensor signal, and wherein the step of classifying comprises applying one or more filters to the noise signal to obtain one or more noise indicators and comparing the noise indicators with one or more noise thresholds.

6. The method of claim 1, wherein the step of classifying comprises performing spectral analysis to determine at least one of a signal strength and a noise indicator.

7. The method of claim 1, wherein the step of classifying a level of noise comprises using hysteresis.

8. The method of claim 1, further comprising controlling an output based at least in part on the level of noise.

9. The method of claim 1, further comprising controlling a display based at least in part on the level of noise.

10. The method of claim 9, wherein the step of controlling a display comprises controlling the display of raw and/or filtered data based at least in part on the level of noise.

11. The method of claim 9, wherein the step of controlling a display comprises displaying rate of change information based at least in part on the level of noise.

12. The method of claim 1, further comprising a step of controlling at least one alarm indicative of at least one of hypoglycemia, hyperglycemia, predicted hypoglycemia, and predicted hyperglycemia based at least in part on the level of noise.

13. The method of claim 1, further comprising a step of controlling medicament delivery and/or medicament therapy instructions based at least in part on the level of noise.

14. The method of claim 1, further comprising a step of diagnosing a sensor condition based at least in part on the level of noise.

15. The method of claim 1, further comprising a step of suspending display of sensor data based at least in part on the level of noise.

16. The method of claim 1, further comprising a step of shutting down a sensor session based at least in part on the level of noise.

17. The method of claim 1, further comprising a step of displaying the level of noise on the user interface.

18. The method of claim 1, further comprising a step of displaying information indicative of the level of noise on the sensor signal.

19. The method of claim 1, further comprising a step of displaying information indicative of an amount of time that the signal has been classified as having a level of noise.

20. A system for classifying a level of noise in a signal obtained from a continuous glucose sensor, the system comprising:

a continuous glucose sensor that provides a signal indicative of a glucose concentration in a host; and

a computer system that classifies a level of noise on the signal.

21. The system of claim 20, wherein the computer system filters the signal by applying a low pass filter to the signal to determine a signal strength.

22. The system of claim 21, wherein the computer system defines one or more noise thresholds for classification of the level of noise on the signal, and wherein the one or more noise thresholds are based at least in part on a percentage of the signal strength.

23. The system of claim 22, wherein the computer system classifies the level of noise by applying one or more low pass filters to the noise signal to obtain one or more noise indicators and comparing the noise indicators to the one or more noise thresholds.

24. The system of claim 20, wherein the computer system classifies a level of noise by applying one or more filters to the noise signal to obtain one or more noise indicators and comparing the noise indicators with one or more noise thresholds.

25. The system of claim 20, wherein the computer system classifies a level of noise by performing spectral analysis to determine at least one of a signal strength and a noise indicator.

26. The system of claim 20, wherein the computer system uses hysteresis to classify the level of noise.

27. The system of claim 20, wherein the computer system provides an output based at least in part on the level of noise.

28. The system of claim 20, further comprising a user interface configured to display the glucose concentration to the host, wherein the computer system is configured to control the display based at least in part on the level of noise.

29. The system of claim 28, wherein the computer system controls the display of raw and/or filtered data based at least in part on the level of noise.

30. The system of claim 28, wherein the computer system controls the display of rate of change information based at least in part on the level of noise.

31. The system of claim 20, wherein the computer system is configured to control alarms indicative of at least one of hypoglycemia, hyperglycemia, predicted hypoglycemia, and predicted hyperglycemia based at least in part on the level of noise.

32. The system of claim 20, wherein the computer system is configured to control medicament delivery and/or medicament therapy instructions based at least in part on the level of noise.

33. The system of claim 20, wherein the computer system is configured to diagnose a sensor condition based at least in part on the level of noise.

34. The system of claim 20, wherein the computer system is configured to suspend display of a glucose concentration based at least in part on the level of noise.

35. The system of claim 20, wherein the computer system is configured to shut down a sensor session based at least in part on the level of noise.

36. The system of claim 20, wherein the computer system is configured to display the level of noise on the user interface.

37. The system of claim 20, wherein the computer system is configured to display information indicative of the level of noise on the sensor signal.

38. The system of claim 20, wherein the computer system is configured to display information indicative of an amount of time the signal has been classified as having a level of noise.