SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA

• US 20080306368A1
• Filed: 08/21/2008
• Published: 12/11/2008
• Est. Priority Date: 08/01/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Brauker, James H., Kamath, Apurv U., Goode, Paul V. JR.
• Granted Patent: US 8,442,610 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 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 a substantially continuous analyte sensor, the method comprising:

receiving a data stream from an analyte sensor, including one or more sensor data points;

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

providing at least one matched data pair by matching reference analyte data to substantially time corresponding sensor data;

creating a conversion function based on said at least one matched data pair;

evaluating said at least one matched data pair, including ensuring said at least one matched data pair is substantially distributed with additional matched data pairs, if present, between high and low matched data pairs over a predetermined time range, wherein the step of evaluating said at least one matched data pair further comprises at least one of evaluating a rate of change of the analyte concentration, evaluating a congruence of respective sensor and reference data in a matched data pair, and evaluating physiological changes; and

subsequently modifying said conversion function if such modification is required by said evaluation.

2. The method of claim 1, wherein the step of evaluating comprises evaluating an initial matched data pair.

3. The method of claim 1, wherein the step of evaluating comprises evaluating at least one subsequently received matched data pair.

4. The method of claim 1, wherein the step of evaluating comprises evaluating a plurality of matched data pairs.

5. The method of claim 1, wherein the step of receiving receiving a data stream comprises receiving a data stream from an implantable analyte sensor.

6. The method of claim 1, wherein the step of receiving a data stream comprises receiving a data stream that has been algorithmically smoothed.

7. The method of claim 1, wherein the step of receiving a sensor data stream comprises algorithmically smoothing said data stream.

8. The method of claim 1, wherein the step of receiving reference data comprises downloading reference data via a wireless connection.

9. The method of claim 1, wherein the step of receiving reference data comprises downloading reference data via a wireless connection.

10. The method of claim 1, wherein the step of receiving reference data from a reference analyte monitor comprises receiving within a receiver internal communication from a reference analyte monitor integral with said receiver.

11. The method of claim 1, wherein the reference analyte monitor is configured for self-monitoring of a blood analyte.

12. The method of claim 1, wherein the step of creating a conversion function comprises performing a linear regression.

13. The method of claim 1, wherein the step of creating a conversion function comprises performing a non-linear regression.

14. The method of claim 1, wherein the step of creating a conversion function utilizes from one matched data pair to six matched data pairs.

15. The method of claim 1, wherein the step of creating a conversion function utilizes at least two matched data pairs.

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

receiving sensor data comprising at least one sensor data point from a substantially continuous analyte sensor;

receiving reference analyte data comprising at least one data point from a reference monitor;

matching one data point of the reference analyte data to one substantially time corresponding data point of the sensor data to create a matched data pair;

creating a conversion function based on at least the matched data pair;

evaluating the matched data pair to determine whether modification of the conversion function is required by ensuring the matched data pair is substantially distributed with any additional matched data pairs present and by ensuring the matched data pair is substantially distributed between any high and low matched data pairs over a predetermined time range, and evaluating at least one of a rate of change of the analyte concentration, a congruence of respective sensor data and reference data in a matched data pair, and physiological changes; and

subsequently modifying the conversion function if modification is required.

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

matching at least one data point of reference analyte data obtained by a reference analyte monitor to one substantially time corresponding data point of sensor data obtained from a substantially continuous analyte sensor to create at least one matched data pair;

creating a conversion function based on the matched data pair; and

modifying the conversion function, if necessary, in response to evaluating the matched data pair to determine whether the matched data pair is substantially distributed with additional matched data pairs present and is substantially distributed between high and low matched data pairs over a predetermined time range, and evaluating at least one of a rate of change of the analyte concentration, a congruence of respective sensor data and reference data in a matched data pair, and physiological changes.