SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA

• US 20100168541A1
• Filed: 12/11/2009
• Published: 07/01/2010
• Est. Priority Date: 08/01/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Kamath, Apurv Ullas, Brauker, James H., Goode, Paul V. JR.
• Granted Patent: US 8,788,006 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 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes

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 predicting future data from real-time continuous analyte sensor data, the method comprising:

receiving, with an electronic device, sensor data from a continuous analyte sensor, wherein the sensor data comprises one or more sensor data points; and

predicting one or more analyte values for a future time.

2. The method of claim 1, further comprising:

receiving reference data from a reference analyte monitor, wherein the reference data comprises one or more reference data points;

forming at least one matched pair by pairing one or more sensor data points with one or more reference data points; and

forming a conversion function based, at least in part, on the at least one matched pair, wherein predicting one or more analyte values comprises calculating one or more future analyte values based, at least in part, on the conversion function.

3. The method of claim 1, further comprising alerting a user when one or more predicted analyte values indicates an upcoming hypoglycemic event or an upcoming hyperglycemic event.

4. The method of claim 1, further comprising compensating for a time lag by estimating one or more analyte values for a future time.

5. The method of claim 4, further comprising displaying the analyte values for a future time on a user interface.

6. The method of claim 1, further comprising:

receiving reference data from a reference analyte monitor, wherein the reference data comprises one or more reference data points;

predicting one or more analyte values based at least in part on the one or more sensor data points; and

forming one or more matched pairs by pairing the one or more predicted analyte values with the one or more reference data points.

7. The method of claim 6, further comprising converting the one or more sensor data points into one or more calibrated sensor data points based at least in part on the one or more matched pairs.

8. The method of claim 6, wherein the analyte is glucose.

9. A system for predicting future data from a real-time continuous analyte sensor data, the system comprising:

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

a processor module configured to predict one or more analyte values for a future time.

10. The system of claim 9, further comprising:

a reference input module configured to receive reference data from a reference analyte monitor, wherein the reference data comprises one or more reference data points;

wherein the processor module is further configured to form at least one matched pair by pairing one or more sensor data points with one or more reference data points and form a conversion function based, at least in part, on the at least one matched pair, and wherein the processor module is further configured to predict one or more analyte values by calculating the one or more predicted analyte values based, at least in part, on the conversion function.

11. The system of claim 9, further comprising an output module configured to alert a user when one or more predicted analyte values indicates an upcoming hypoglycemic event or an upcoming hyperglycemic event.

12. The system of claim 9, wherein the processor module is further configured to compensate for a time lag by estimating one or more analyte values for a future time.

13. The system of claim 12, further comprising an output module configured to display the estimated analyte values for a future time on a user interface.

14. The system of claim 9, wherein the processor module is configured to process the sensor data to compensate for a time lag associated with the sensor data by estimating one or more analyte values for a future time period, whereby the one or more analyte values for a future time period are matched to one or more reference values for sensor calibration.

15. The system of claim 9, wherein the processor module is configured to convert the sensor data into calibrated sensor data based on the sensor calibration.

16. The system of claim 9, wherein the analyte is glucose.