ADVANCED CALIBRATION FOR ANALYTE SENSORS

• US 20160183855A1
• Filed: 03/09/2016
• Published: 06/30/2016
• Est. Priority Date: 03/14/2013
• Status: Abandoned Application

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Vanslyke, Stephen J., Bhavaraju, Naresh C., Bohnett, Lucas, Garcia, Arturo, Kamath, Apurv Ullas, Pryor, Jack
• Application Number:
  US15/065,589
• Publication Number:
  US 20160183855A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: G16H 40/40 for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades

Abstract

Systems and methods for processing sensor data and calibration of the sensors are provided. In some embodiments, the method for calibrating at least one sensor data point from an analyte sensor comprises receiving a priori calibration distribution information; receiving one or more real-time inputs that may influence calibration of the analyte sensor; forming a posteriori calibration distribution information based on the one or more real-time inputs; and converting, in real-time, at least one sensor data point calibrated sensor data based on the a posteriori calibration distribution information.

Claims

1. A method for calibrating at least one sensor data point from an analyte sensor, the method comprising:

(a) receiving a priori calibration distribution information;

(b) receiving one or more real-time inputs that may influence calibration of the analyte sensor;

(c) forming a posteriori calibration distribution information based on the one or more real-time inputs; and

(d) converting, in real-time, at least one sensor data point calibrated sensor data based on the a posteriori calibration distribution information.

2. The method of claim 1, wherein the a priori calibration distribution information comprises information from previous calibrations of a particular sensor session and/or information obtained prior to sensor insertion.

3. The method of claim 1, wherein the a priori calibration distribution information comprises probability distributions for sensitivity (m), sensitivity-related information, baseline (b), or baseline-related information.

4. The method of claim 1, wherein the a priori calibration distribution information comprises a priori guidance or validation ranges.

5. The method of claim 1, wherein the one or more real-time inputs comprise data received or determined since a previous calibration process.

6. The method of claim 5, wherein the one or more real-time inputs comprises at least one of:

internally-derived real-time data, externally-derived real-time data, and combinations of internally- and externally-derived real-time data.

7. The method of claim 6, wherein internally-derived real-time data includes at least one type of information selected from the group consisting of:

stimulus signal output of sensor;

sensor data measured by the sensor indicative of an analyte concentration;

sensor data indicative of analyte rate-of-change;

temperature measurements;

sensor data from multi-electrode sensors;

sensor data generated by redundant sensors;

sensor data generated by one or more auxiliary sensors;

data representative of a pressure on sensor;

data generated by an accelerometer;

sensor diagnostic information;

impedance; and

certainty level.

8. The method of claim 6, wherein externally-derived real-time data includes at least one type of information selected from the group consisting of:

glucose concentration information obtained from a reference monitor;

information related to meal;

insulin dosing time and amounts;

insulin estimates;

exercise;

sleep;

illness;

stress;

hydration; and

hormonal conditions.

9. The method of claim 6, wherein combinations of internally- and externally-derived real-time data includes at least one type of information selected from the group consisting of:

information gathered from population based data;

glucose concentration of the host;

error at calibration or error in matched data pair;

site of sensor implantation specific relationships;

time since sensor manufacture;

exposure of sensor to temperature, humidity, external factors, on shelf;

a measure of noise in an analyte concentration signal; and

a level of certainty.

10. The method of claim 1, further comprising determining a level of certainty associated with the calibration information and/or calibrated sensor data.

11. The method of claim 1, wherein forming a posteriori calibration distribution information comprises at least one of:

1) an adjustment of the a priori calibration distribution information or

     2) a creation of a new range or distribution information based on the one or more real-time inputs.

12. The method of claim 11, wherein an adjustment of the a priori calibration distribution information comprises shifting, tightening, or loosening the a priori calibration distribution.

13. The method of claim 1, wherein the calibration distribution information is selected from the group consisting of:

sensitivity;

change in sensitivity;

rate of change of sensitivity;

baseline;

change in baseline, rate of change of baseline, baseline profile associated with the sensor;

sensitivity profile associated with the sensor;

linearity;

response time;

relationships between properties of the sensor;

relationships between particular stimulus signal output; and

patient specific relationships between sensor and sensitivity, baseline, drift, impedance, impedance/temperature relationship, site of sensor implantation.

14. The method of claim 1, further comprising providing output of calibrated sensor data.

15. The method of claim 1, wherein the method is implemented on a computer having a processor and a memory coupled to said processor, wherein at least one of steps (a) through (e) are performed using said processor.

16. A system for calibrating at least one sensor data point from a continuous analyte sensor, the system comprising sensor electronics configured to be operably connected to a continuous analyte sensor, the sensor electronics configured to:

(a) receive a priori calibration distribution information;

(b) receive one or more real-time inputs that may influence calibration of the analyte sensor;

(c) form a posteriori calibration distribution information using the one or more real-time inputs; and

(d) convert, in real-time, at least one sensor data point calibrated sensor data based on the a posteriori calibration distribution information.

17. The system of claim 16, wherein the sensor electronics comprise a processor module, the processor module comprising instructions stored in computer memory, wherein the instructions, when executed by the processor module, cause the sensor electronics to perform the forming and the determining.

18. A system for calibrating at least one sensor data point from an analyte sensor, the system comprising:

means for receiving a priori calibration distribution information;

means for receiving one or more real-time inputs that may influence calibration of the analyte sensor;

means for forming a posteriori calibration distribution information based on the one or more real-time inputs; and

means for converting, in real-time, at least one sensor data point calibrated sensor data based on the a posteriori calibration distribution information.