SYSTEM AND/OR METHOD FOR GLUCOSE SENSOR CALIBRATION

• US 20170224919A1
• Filed: 02/08/2016
• Published: 08/10/2017
• Est. Priority Date: 12/29/2008
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Keenan, Desmond Barry, Mastrototaro, John J.
• Granted Patent: US 10,471,207 B2
• Time in Patent Office: Days
• 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: A61M 2230/005 Parameter used as control input for the apparatus
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/40 for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/63 for local operation

Abstract

The subject matter disclosed herein relates to systems, methods and/or devices for calibrating sensor data to be used in estimating a blood glucose concentration. A relationship between sensor measurements and reference readings may be used to estimate a relationship between sensor measurements and blood glucose concentration. Such sensor measurements may be weighted according to a decreasing function of uncertainty associated with sensor values.

Claims

1. A method comprising:

obtaining samples of an electrical signal generated by a sensor, said samples having sample values responsive to a blood-glucose concentration in a patient;

obtaining blood glucose reference measurement values, said blood glucose reference measurement values being indicative of said blood-glucose concentration;

temporally associating at least some of said sample values with at least some of said blood glucose reference measurement values;

for at least one of said sample values temporally associated with at least one of said blood glucose reference measurement values, weighting said at least one of said temporally associated sample values based, at least in part, on a measure of statistical dispersion of said electrical signal, said measure of statistical dispersion of said electrical signal being determined based, at least in part, on said at least one of said blood glucose reference measurement values;

determining one or more parameters of an estimator of said blood-glucose concentration based, at least in part, on said weighted sample values; and

generating a control signal to a pump to affect infusion of a substance to said patient based, at least in part, on said determined one or more parameters of said estimator of said blood-glucose concentration.

2. The method of claim 1, wherein said determining said one or more parameters comprises determining said one or more parameters based, at least in part, on a linear regression of said weighted sample values and said temporally associated blood-glucose reference measurement values.

3. The method of claim 2, wherein said determining said one or more parameters of said estimator further comprises:

calculating a linear regression sensitivity ratio based, at least in part, on said weighted sample values and temporally associated blood-glucose reference measurement values;

selecting an offset based, at least in part, on said calculated linear regression sensitivity ratio; and

calculating a modified linear regression sensitivity ratio based, at least in part, on said selected offset, said weighted sample values and said temporally associated blood-glucose reference measurement values.

4. The method of claim 1, wherein said measure of statistical dispersion comprises a variance and/or approximation of a variance of said sample values as a function of said temporally associated blood glucose reference measurement values.

5. The method of claim 1, wherein said at least some of said sample values temporally associated with said at least one of said blood glucose reference values are weighted according to an inverse of said measure of statistical dispersion of said sample values.

6. The method of claim 1, and further comprising:

estimating a linear relationship of said measure of statistical dispersion of said electrical signal versus blood glucose concentration; and

deriving said one or more parameters based, at least in part, on said linear relationship.

7. The method of claim 1, wherein weighting said at least one of said sample values temporally associated with at said least one of said blood glucose reference measurement values further comprises further weighting said sample values temporally associated with said at least one of said blood glucose reference measurement values based on how recently said sample values temporally associated with said at least one of said blood glucose reference measurement values are obtained.

8. The method of claim 1, and further comprising detecting a failure of said sensor based, at least in part, on a change in said determined one or more parameters.

9. The method of claim 1, and further comprising calibrating measurements from said sensor for measuring a blood-glucose concentration based, at least in part, on said determined one or more parameters.

10. The method of claim 1, wherein said weighting said at least one of said temporally associated sample values comprises weighting said at least one of said temporally associated sample values according to a decreasing function of blood glucose reference measurement values temporally associated with said at least one of said sample values.

11. An apparatus comprising:

a sensor to generate one or more sensor signals responsive to a blood glucose concentration in a body;

an infusion pump; and

a computing platform to;

obtain samples of said one or more sensor signals;

obtain blood glucose reference measurement values, said blood glucose reference measurement values being indicative of said blood-glucose concentration;

temporally associate at least some of said sample values with at least some of said blood glucose reference measurement values;

for at least one of said sample values temporally associated with at least one of said blood glucose reference measurement values, weight said at least one of said temporally associated sample values based, at least in part, on a measure of statistical dispersion of said electrical signal, said measure of statistical dispersion of said electrical signal being determined based, at least in part, on said at least one of said blood glucose reference measurement values;

determine one or more parameters of an estimator of said blood-glucose concentration based, at least in part, on said weighted sample values; and

generate a control signal to said infusion pump to infuse a substance to said body based, at least in part, on said determined one or more parameters of said estimator of said blood-glucose concentration.

12. The apparatus of claim 11, wherein said computing platform is further to determine said one or more parameters based, at least in part, on a linear regression of said weighted sample values and said temporally associated blood-glucose reference measurement values.

13. The apparatus of claim 12, wherein said computing platform is further to:

calculate a linear regression sensitivity ratio based, at least in part, on said weighted sample values and temporally associated blood-glucose reference measurement values;

select an offset based, at least in part, on said calculated linear regression sensitivity ratio; and

calculate a modified linear regression sensitivity ratio based, at least in part, on said selected offset, said weighted sample values and said temporally associated blood-glucose reference measurement values.

14. The apparatus of claim 11, wherein said measure of statistical dispersion comprises a variance and/or approximation of a variance of said sample values as a function of said temporally associated blood glucose reference measurement values.

15. The apparatus of claim 11, wherein said at least some of said sample values temporally associated with said at least one of said blood glucose reference values are weighted according to an inverse of said measure of statistical dispersion of said sample values.

16. The apparatus of claim 11, wherein said computing platform is further to:

estimate a linear relationship of said measure of statistical dispersion of said electrical signal versus blood glucose concentration; and

derive said one or more parameters based, at least in part, on said linear relationship.

17. The apparatus of claim 11, wherein said computing platform is further to weight said sample values temporally associated with said at least one of said blood glucose reference measurement values based on how recently said sample values temporally associated with said at least one of said blood glucose reference measurement values are obtained.

18. The apparatus of claim 11, wherein said computing platform is further to detect a failure of said sensor based, at least in part, on a change in said determined one or more parameters.

19. The apparatus of claim 11, wherein said computing platform is further to calibrate measurements from said sensor for measuring a blood-glucose concentration based, at least in part, on said determined one or more parameters.

20. The apparatus of claim 11, wherein said computing platform is further to weight said at least one of said temporally associated sample values according to a decreasing function of blood glucose reference measurement values temporally associated with said at least one of said sample values.