Methods, systems, and devices for calibration and optimization of glucose sensors and sensor output

Patent metadata

Field	Value
Publication number	US-11344235-B2
Application number	US-201816117733-A
Country	US
Kind code	B2
Filing date	Aug 30, 2018
Priority date	Sep 13, 2017
Publication date	May 31, 2022
Grant date	May 31, 2022

Abstract

A continuous glucose monitoring system may utilize externally sourced information regarding the physiological state and ambient environment of its user for externally calibrating sensor glucose measurements. Externally sourced factory calibration information may be utilized, where the information is generated by comparing metrics obtained from the data used to generate the sensor's glucose sensing algorithm to similar data obtained from each batch of sensors to be used with the algorithm in the future. The output sensor glucose value of a glucose sensor may also be estimated by analytically optimizing input sensor signals to accurately correct for changes in sensitivity, run-in time, glucose current dips, and other variable sensor wear effects. Correction actors, fusion algorithms, EIS, and advanced ASICs may be used to implement the foregoing, thereby achieving the goal of improved accuracy and reliability without the need for blood-glucose calibration, and providing a calibration-free, or near calibration-free, sensor.

First claim

What is claimed is:

1. A method of optimizing glucose sensor estimation for a glucose sensor used for measuring a level of glucose in a body of a user, said glucose sensor including physical sensor electronics, a microcontroller, a working electrode, and a counter electrode, the method comprising:
periodically measuring, by the physical sensor electronics, electrode current (Isig) signals for the working electrode;
performing, by the microcontroller, an Electrochemical Impedance Spectroscopy (EIS) procedure to generate EIS-related data at multiple frequencies for the working electrode;
calculating, by the microcontroller, an adjusted calibration factor for the glucose sensor based on the EIS-related data;
calculating, by the microcontroller, an adjusted offset value for the glucose sensor based on at least one of a stabilization time adjustment or a non-linear sensor response adjustment; and
providing a blood glucose reading by calculating, by the microcontroller, an optimized measured glucose value (SG) based on the adjusted calibration factor and the adjusted offset value,
wherein SG=(adjusted calibration factor)×(Isig+adjusted offset value),
wherein said adjusted calibration factor is calculated based on at least one of a foreign body response, an oxygen response, a dip adjustment response, or a stabilization response for the glucose sensor, and
wherein said foreign body response is calculated as foreign body response=c 1 ×e imag1000×c 2 +c 3 , where imag1000 is an imaginary value at 1000 Hz of the generated EIS-related data, and c 1 , c 2 , and c 3 are experimentally determined calibration coefficients.

2. The method of claim 1 , further including displaying the optimized measured glucose value to the user.

3. The method of claim 1 , wherein said adjusted calibration factor is calculated based on real impedance values at 128 Hz of the generated EIS-related data.

4. The method of claim 1 , wherein c 1 is −1.4, c 2 is 0.008, and c 3 is 1.3.

5. The method of claim 1 , wherein said oxygen response is calculated as oxygen response=c 1 ×Vcntr 2 +c 2 ×Vcntr+c 3 , wherein Vcntr is a counter voltage input of the counter electrode.

6. The method of claim 5 , wherein c 1 is 2.0/V, c 2 is 2.0, and c 3 is 2.0V.

7. The method of claim 1 , wherein said dip adjustment response is calculated as dip adjustment=c 1 ×e lsigTrend×c 2 +c 3 , wherein lsigTrend is a sensor current trend input.

8. The method of claim 7 , wherein c 1 is 4.68, c 2 is −0.21, and c 3 is 0.97.

9. The method of claim 7 , wherein the sensor current trend input is based on 6, 12, 18, 24, and 48-hour average sensor current values.

10. The method of claim 1 , wherein said stabilization response is calculated as stabilization response=c 1 ×Vcntr+c 2 , where Vcntr is a counter voltage input of the counter electrode.

11. The method of claim 10 , wherein c 1 is 0.48/V and c 2 is 1.24.

12. The method of claim 1 , wherein said adjusted calibration factor is calculated based on a foreign body response, an oxygen response, a dip adjustment response, and a stabilization response for the glucose sensor.

13. The method of claim 1 , wherein said stabilization time adjustment for calculation of the adjusted offset value is calculated as stabilization time adjustment=c 1 ×e age×c 2 +c 3 , wherein age is a sensor age.

14. The method of claim 13 , wherein c 1 is −5.4, c 2 is −0.50, and c 3 is −1.5 nA.

15. The method of claim 13 , wherein the sensor age is measured from one of sensor warm-up completion, sensor insertion, and sensor calibration completion.

16. The method of claim 1 , said non-linear sensor response adjustment for calculation of the adjusted offset value is calculated as non-linear sensor response adjustment=c 1 +(age×c 2 +c 3 )×lsig, wherein age is a sensor age.

17. The method of claim 16 , wherein c 1 is 13.8 nA, c 2 is −0.1/day, and c 3 is −0.7.

18. The method of claim 16 , wherein the sensor age is measured from one of sensor warm-up completion, sensor insertion, and sensor calibration completion.

Assignees

• Medtronic Minimed Inc

Inventors

• Nogueira Keith
• Ajemba Peter
• Miller Michael E
• Jacks Steven C
• Nishida Jeffrey
• Tsai Andy Y
• Varsavsky Andrea

Classifications

• G16H50/70

  for mining of medical data, e.g. analysing previous cases of other patients · CPC title

• G16H50/30

  for calculating health indices; for individual health risk assessment · CPC title

• G16H40/40

  for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades · CPC title

• G16H20/17

  delivered via infusion or injection · CPC title

• G06N20/10

  using kernel methods, e.g. support vector machines [SVM] · CPC title