SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA

• US 20120215461A1
• Filed: 04/27/2012
• Published: 08/23/2012
• Est. Priority Date: 08/01/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Goode, Paul V. Jr., Brauker, James H., Kamath, Apurv U., Thrower, James P.
• Granted Patent: US 8,801,612 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 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 processing at least one of reference glucose data or sensor glucose data, the method comprising:

receiving sensor data from a continuous glucose sensor, the sensor data comprising one or more sensor data points;

receiving reference data from a reference glucose monitor, the reference data comprising one or more reference data points;

forming, using a processor module, a matched data pair by matching at least one sensor data point to at least one substantially time corresponding reference data point;

determining, using the processor module, a zone out of a plurality of predetermined zones into which the matched data pair falls based on a deviation of the sensor data and the reference data of the matched data pair and a user'"'"'s blood glucose concentration value as indicated by at least one of the reference data and the sensor data, wherein the plurality of zones comprises at least one zone of a first type and at least one zone of a second type; and

processing, using the processor module, at least one of the one or more sensor data points and the one or more reference data points responsive to the type of zone in which the matched data pair is determined to fall.

2. The method of claim 1, further comprising validating one or more of the reference data points as a valid entry, wherein validating comprises determining that the matched data pair falls into a zone of the first type.

3. The method of claim 2, further comprising accepting one or more valid reference data points for use in calibration of the continuous glucose sensor, wherein the validating is performed prior to the accepting.

4. The method of claim 2, wherein the validating further comprises determining if the one or more sensor data points or one or more reference data points are physiologically feasible based on one or more previous sensor data points or one or more previous reference data points.

5. The method of claim 2, further comprising predicting future glucose values, wherein the validating further comprises comparing a current glucose value to a time corresponding predicted glucose value.

6. The method of claim 1, wherein determining the zone into which the matched data pair falls comprises plotting a data point corresponding to the sensor data and reference data values of the matched data pair on a grid having the plurality of zones.

7. The method of claim 6, wherein the grid is one of a Clarke Error Grid and a Consensus Grid.

8. The method of claim 1, wherein the plurality of zones comprises at least two non-adjacent zones of the second type.

9. The method of claim 1, further comprising determining that the reference data is clinically acceptable when the matched data pair falls within a zone of the first type and determining that the reference data is clinically unacceptable when the matched data pair falls within a zone of the second type.

10. The method of claim 1, wherein processing comprises using the reference data and the sensor data to generated estimated glucose concentration values when the matched data pair falls within a zone of the first type and prompting a user via a user interface for additional reference data when the matched data pair falls within a zone of the second type.

11. The method of claim 1, wherein each zone of the plurality of zones comprises varying ranges of values, wherein the range of values vary depending upon the user'"'"'s blood glucose concentration value as indicated by the least one of the reference data and the sensor data.

12. The method of claim 1, wherein the sensor data and the reference data of the matched data pair are in units of blood glucose concentration.

13. The method of claim 1, wherein the determining is performed in real time during continuous glucose sensing of the glucose sensor.

14. The method of claim 1, wherein the reference glucose monitor comprises a self-monitored blood analyte test meter and wherein the continuous glucose sensor comprises an implantable glucose sensor.

15. The method of claim 1, wherein the reference data is received periodically during real-time continuous glucose sensing of the glucose sensor.

16. The method of claim 1, wherein processing comprises calculating a conversion function based on the matched data pair and converting the sensor data to one or more estimated blood glucose concentration values based on the conversion function when the matched data pair falls within a zone of the first type.

17. The method of claim 16, wherein processing further comprises causing a display to display information representative of the one or more estimated blood glucose concentration values on a user interface.

18. A system for processing at least one of reference glucose data or sensor glucose data, the system comprising:

a sensor data module configured to receive sensor data from a continuous glucose sensor, the sensor data comprising one or more sensor data points;

a reference input module configured to receive reference data from a reference glucose monitor, the reference data comprising one or more reference data points; and

a processor module configured to (i) form a matched data pair by matching at least one sensor data point of the sensor data to at least one substantially time corresponding reference data point of the reference data, (ii) determine a zone out of a plurality of predetermined zones into which the matched data pair falls based on a deviation of the sensor data and reference data of the matched data pair and a user'"'"'s blood glucose concentration value as indicated by at least one of the reference data and the sensor data, wherein the plurality of zones comprises at least one zone of a first type and at least one zone of a second type, and (iii) process at least one of the one or more sensor data points or the one or more reference data points responsive to the type of zone into which matched data pair is determined to fall.

19. The system of claim 18, wherein the processor module is further configured to validate one or more reference data points as a valid entry, wherein the validation comprises determining that the matched data falls into the zone of the first type.

20. The system of claim 19, wherein the processor module is further configured to accept the one or more reference data points for calibrating the continuous glucose sensor after validating the one or more reference data points.

21. The system of claim 18, wherein the processor module is further configured to predict or to estimate a one or more future glucose values based on previous sensor data, and wherein the processor module is configured to validate at least one of the one or more sensor data points or the one or more reference data points based additionally on a comparison of a current glucose value to at least one of a time corresponding predicted glucose value or an estimated glucose value.

22. The system of claim 18, wherein determining the zone into which the matched data pair falls comprises plotting a data point corresponding to the sensor data and reference data values on a grid having the plurality of zones.

23. The system of claim 22, wherein the grid is one of a Clarke Error Grid and a Consensus Grid.

24. The system of claim 18, wherein the processor module is further configured to determine that the reference data is clinically acceptable when the matched data pair falls within a zone of the first type and determining that the reference data is clinically unacceptable when the matched data pair falls within a zone of the second type.

25. The system of claim 18, wherein the plurality of zones comprises at least two non-adjacent zones of the second type.

26. The system of claim 18, further comprising a user interface, wherein the processor is further configured to prompt a user via the user interface for additional reference data when the matched data pair falls within a zone of the second type.

27. The system of claim 18, wherein each of the plurality of zones comprises ranges of values, wherein the ranges of values vary depending upon the user'"'"'s blood glucose concentration value as indicated by at least one of the reference data and the sensor data.

28. The system of claim 18, wherein the sensor data and the reference data of the matched data pair are in units of blood glucose concentration.

29. The system of claim 18, wherein the determining is performed in real time during continuous glucose sensing of the glucose sensor.

30. The system of claim 18, wherein the reference glucose monitor is a self-monitored blood analyte test and wherein the continuous glucose sensor is an implantable glucose sensor.

31. The system of claim 18, wherein the processor module is further configured to calculate a conversion function based on the matched data pair and convert the sensor data to a blood glucose concentration value using the conversion function when the matched data pair falls within a zone of the first type.

32. The system of claim 31, further comprising a display, wherein the processor module is configured to cause the display to display information representative of the blood glucose concentration value.

33. The system of claim 32, wherein the blood glucose concentration value is a real-time blood glucose concentration value.

34. The system of claim 18, wherein the processor module is further configured to calibrate the continuous analyte sensor using a conversion function, wherein the processor module forms or modifies the conversion function based on a statistical association of the matched data pair and one or more additional matched data pairs.