GLUCOSE SENSOR SIGNAL STABILITY ANALYSIS

• US 20150316559A1
• Filed: 07/10/2015
• Published: 11/05/2015
• Est. Priority Date: 06/23/2010
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Luo, Ying, Gottlieb, Rebecca K., Ramachandran, Meena, Chiu, Chia-Hung, Dangui-Patel, Nandita, Kremliovsky, Michael, Rose, Jefferson
• Granted Patent: US 10,429,395 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0017 transmitting optical signals transmission by light H04B10/00
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/6849 in combination with a needle set
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: G01N 33/66 involving blood sugars, e.g. galactose

Abstract

Disclosed are methods, apparatuses, etc. for glucose sensor signal stability analysis. In certain example embodiments, a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient may be obtained. Based at least partly on the series of samples, at least one metric may be determined to assess an underlying trend of a change in responsiveness of the at least one sensor signal to the blood glucose level of the patient over time. A reliability of the at least one sensor signal to respond to the blood glucose level of the patient may be assessed based at least partly on the at least one metric assessing the underlying trend. Other example embodiments are disclosed herein.

Claims

1. A method comprising:

obtaining a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient;

determining, based at least partly on the series of samples, at least one metric assessing an underlying trend of a change in responsiveness of the at least one sensor signal to the blood glucose level of the patient over time; and

assessing a reliability of the at least one sensor signal to respond to the blood glucose level of the patient based at least partly on the at least one metric assessing the underlying trend.

2. The method of claim 1, further comprising:

generating an alert signal responsive to a comparison of the at least one metric assessing the underlying trend with at least one predetermined threshold value.

3. The method of claim 1, wherein the assessing the reliability of the at least one sensor signal comprises:

comparing the at least one metric assessing the underlying trend with at least a first predetermined threshold and a second predetermined threshold.

4. The method of claim 1, further comprising:

acquiring the at least one sensor signal from one or more subcutaneous glucose sensors,

wherein the at least one metric assessing the underlying trend reflects an apparent reliability of the at least one sensor signal that is acquired from the one or more subcutaneous glucose sensors.

5. The method of claim 1, further comprising:

altering an insulin infusion treatment for the patient responsive at least partly to the assessed reliability of the at least one sensor signal.

6. The method of claim 1, wherein the determining the at least one metric comprises:

producing the at least one metric assessing the underlying trend using a slope of a linear regression that is derived at least partly from the series of samples of the at least one sensor signal.

7. An apparatus comprising:

a controller to obtain a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient, the controller comprising one or more processors to;

determine, based at least partly on the series of samples, at least one metric assessing an underlying trend of a change in responsiveness of the at least one sensor signal to the blood glucose level of the patient over time; and

assess a reliability of the at least one sensor signal to respond to the blood glucose level of the patient based at least partly on the at least one metric assessing the underlying trend.

8. The apparatus of claim 7, wherein the one or more processors of the controller are further to:

generate an alert signal responsive to a comparison of the at least one metric assessing the underlying trend with at least one predetermined threshold.

9. The apparatus of claim 7, wherein the one or more processors of the controller are further to:

compare the at least one metric assessing the underlying trend with at least a first predetermined threshold and a second predetermined threshold.

10. The apparatus of claim 7, wherein the one or more processors of the controller are further to:

acquire the at least one sensor signal from one or more subcutaneous glucose sensors,

wherein the at least one metric assessing the underlying trend reflects an apparent reliability of the at least one sensor signal that is acquired from the one or more subcutaneous glucose sensors.

11. The apparatus of claim 7, wherein the one or more processors of the controller are further to:

alter an insulin infusion treatment for the patient responsive at least partly to the assessed reliability of the at least one sensor signal.

12. The apparatus of claim 7, wherein the one or more processors of the controller are further to:

produce the at least one metric assessing the underlying trend using a slope of a linear regression that is derived at least partly from the series of samples of the at least one sensor signal.

13. The apparatus of claim 12, wherein the one or more processors of the controller are further to:

transform the series of samples of the at least one sensor signal to derive a monotonic curve,

wherein the controller is capable of producing the at least one metric assessing the underlying trend by calculating the slope of the linear regression, the linear regression being derived at least partly from the monotonic curve.

14. The apparatus of claim 7, wherein the one or more processors of the controller are further to:

decompose the at least one sensor signal as represented by the series of samples using at least one discrete wavelet transform; and

reconstruct a smoothed signal from one or more approximation coefficients resulting from the at least one discrete wavelet transform.

15. The apparatus of claim 7, wherein the one or more processors of the controller are further to:

iteratively update a trend estimation at multiple samples of the series of samples of the at least one sensor signal based at least partly on a trend estimation at a previous sample and a growth term.

16. A system comprising:

means for obtaining a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient;

means for determining, based at least partly on the series of samples, at least one metric assessing an underlying trend of a change in responsiveness of the at least one sensor signal to the blood glucose level of the patient over time; and

means for assessing a reliability of the at least one sensor signal to respond to the blood glucose level of the patient based at least partly on the at least one metric assessing an underlying trend.

17. The system of claim 16, further comprising means for generating an alert signal responsive to a comparison of the at least one metric assessing the underlying trend with at least one predetermined threshold.

18. The system of claim 16, wherein the means for assessing the reliability of the at least one sensor signal comprises means for comparing the at least one metric assessing the underlying trend with at least a first predetermined threshold and a second predetermined threshold.

19. The system of claim 16, further comprising:

means for acquiring the at least one sensor signal from one or more subcutaneous glucose sensors,

wherein the means for determine the at least one metric assessing the underlying trend reflects an apparent reliability of the at least one sensor signal that is acquired from the one or more subcutaneous glucose sensors.

20. The system of claim 16, wherein the means for determining the at least one metric comprises means for producing the at least one metric assessing the underlying trend using a slope of a linear regression that is derived at least partly from the series of samples of the at least one sensor signal.