System and methods for processing analyte sensor data

• US 8,700,117 B2
• Filed: 12/08/2009
• Issued: 04/15/2014
• Est. Priority Date: 08/01/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Kamath, Apurv Ullas, Goode, Paul V., Brauker, James H.
• Primary Examiner(s): D'ANGELO, MICHAEL J
• Application Number:
  US12/633,654
• Publication Number:
  US 20100161269A1
• Time in Patent Office: 1,589 Days
• Field of Search: 600/309, 600/316, 600345-347, 600/365, 435/4, 435/14, 436/68, 422/50, 422420-429, 20440301-40315, 702/23, 604 64- 66, 606/167, 606181-183
• US Class Current: 600/347
• 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 3/10 Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/1433 provided with locking means details of syringes A61M5/315
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1468 using chemical or electrochemical methods, e.g. by polarographic means A61B5/1486 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 5/150022 for capillary blood or interstitial fluid
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: G01N 33/48707 by electrical means G01N33/49, G01N33/493 take precedence
• 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 analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.

Claims

1. A method for calibrating an analyte sensor, the method comprising:

receiving sensor data from an analyte sensor, wherein the sensor data comprises one or more sensor data points;

receiving reference data from a reference analyte monitor, wherein the reference data comprises a reference data point;

predicting an estimated sensor data point from the one or more sensor data points for a time corresponding to a time stamp of the reference data point;

matching the reference data point to the predicted, estimated sensor data point to compensate for a time lag of the one or more sensor data points relative to the reference data point;

forming a calibration set comprising the reference data point and the predicted, estimated sensor data point;

creating a conversion function based at least in part on the calibration set; and

converting, using a processor, the sensor data into calibrated data using the conversion function, wherein the sensor data points are smoothed using a data smoothing filter, and wherein the time lag compensation is based at least in part on a time delay introduced by the data smoothing filter.

2. The method of claim 1, wherein the received one or more sensor data points are smoothed sensor data points.

3. The method of claim 1, further comprising smoothing the one or more sensor data points using the data smoothing filter, whereby smoothed sensor data points are obtained.

4. The method of claim 1, wherein the time delay is variable based on the data smoothing filter.

5. The method of claim 1, wherein the time delay is approximately 10 minutes.

6. The method of claim 1, wherein the data smoothing filter is a recursive filter.

7. The method of claim 1, wherein the data smoothing filter is a non-recursive filter.

8. The method of claim 1, wherein the analyte sensor is a glucose sensor.

9. A method for calibrating an analyte sensor, the method comprising:

receiving sensor data associated with a data stream from an analyte sensor, wherein the sensor data comprises one or more sensor data points;

receiving reference data from a reference analyte monitor, wherein the reference data comprises a reference data point;

predicting an estimated sensor data point from the one or more sensor data points for a time corresponding to a time stamp of the reference data point

matching the reference data point to the predicted, estimated sensor data point to compensate for a time lag of the one or more sensor data points relative to the reference data point;

forming a calibration set comprising the reference data point and the predicted, estimated sensor data point;

creating a conversion function based at least in part on the calibration set; and

converting, using a processor, sensor data into calibrated data using the conversion function.

10. The method of claim 9, wherein the analyte sensor is a glucose sensor.

11. The method of claim 9, wherein the substantial time correspondence is variable.

12. A system for calibrating an analyte sensor, the system comprising:

a sensor data receiving module configured to receive sensor data from an analyte sensor, wherein the sensor data comprises one or more sensor data points;

a reference data receiving module configured to receive reference data from a reference analyte monitor, wherein the reference data comprises a reference data point; and

a processor module configured to predict an estimated sensor data point from the one or more sensor data points for a time corresponding to a time stamp of the reference data point, match the reference data point to the predicted, estimated sensor data point to compensate for a time lag of the one or more sensor data points relative to the reference data point, form a calibration set comprising the reference data point and the matched predicted, estimated sensor data point, create a conversion function based on the calibration set, and convert sensor data into calibrated data using the conversion function, wherein the sensor data points are smoothed using a data smoothing filter, and wherein the time lag compensation is based at least in part on a time delay introduced by the data smoothing filter.

13. The system of claim 12, wherein the one or more sensor data points are smoothed sensor data points.

14. The system of claim 12, wherein the processor module is configured to smooth the one or more sensor data points using the data smoothing filter, whereby the smoothed sensor data points are obtained.

15. The system of claim 12, wherein the time delay is variable based on the data smoothing filter.

16. The system of claim 12, wherein the time delay is approximately 10 minutes.

17. The system of claim 12, wherein the data smoothing filter is a recursive filter.

18. The system of claim 12, wherein the data smoothing filter is a non-recursive filter.

19. The system of claim 12, wherein the analyte sensor is a glucose sensor.

20. A system for calibrating an analyte sensor, the method comprising:

a sensor data receiving module configured to receive sensor data from an analyte sensor, wherein the sensor data comprises one or more sensor data points;

a reference data receiving module configured to receive reference data from a reference analyte monitor, wherein the reference data comprises a reference data point;

a processor module configured to predict an estimated sensor data point from the one or more sensor data points for a time corresponding to a time stamp of the reference data point, match the reference data point to the predicted, estimated sensor data point to compensate for a time lag of the one or more sensor data points relative to the reference data point, form a calibration set comprising the reference data point and the predicted, estimated sensor data point, create a conversion function based at least in part on the calibration set, and convert sensor data into calibrated data using the conversion function.

21. The system of claim 20, wherein the analyte sensor is a glucose sensor.

22. The system of claim 20, wherein the substantial time correspondence is variable.