GLUCOSE SENSOR SIGNAL RELIABILITY ANALYSIS

• US 20120108935A1
• Filed: 10/26/2011
• Published: 05/03/2012
• Est. Priority Date: 10/28/2010
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Liang, Bradley, Cooper, Kenneth W., Gautham, Raghavendhar, Shah, Rajiv
• Granted Patent: US 9,033,878 B2
• Time in Patent Office: Days
• US Class Current: 600/365
• CPC Class Codes: A61B 2560/0276 Determining malfunction
• CPC Class Codes: A61B 5/14503 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence
• CPC Class Codes: A61B 5/1451 for interstitial fluid
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14865 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/6849 in combination with a needle set
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61M 2205/50 with microprocessors or computers
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/14248 of the skin patch type
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00

Abstract

Disclosed are methods, apparatuses, etc. for glucose sensor signal reliability analysis.

Claims

1. A method comprising:

obtaining a plurality of glucose sensor measurements at a glucose sensor over a time interval; and

detecting a change in responsiveness of said glucose sensor to a presence of glucose in a fluid based, at least in part, on an application of one or more thresholds to one or more sensitivity metrics, at least one of said sensitivity metrics being based, at least in part, on said glucose sensor measurements.

2. The method of claim 1, wherein said change in responsiveness comprises a decrease in sensitivity of said glucose sensor to the presence of glucose in said fluid.

3. The method of claim 1, wherein at least one of said sensitivity metrics comprises a measurement of dispersion of a rate change in said blood glucose sensor measurements over at least a portion of said time interval.

4. The method of claim 3, wherein said measurement of dispersion of said rate of change comprises a variance of said rate of change.

5. The method of claim 1, wherein at least one of said sensitivity metrics comprises a computed mean value of said sensor measurements obtained over said portion of said time interval.

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

generating an alert signal in response to said detected change in said responsiveness.

7. The method of claim 1, wherein said portion of said time interval comprises a sliding time window.

8. The method of claim 1, wherein said one or more sensitivity metrics comprise at least a measurement of dispersion of a rate change in said blood glucose sensor measurements and a mean value of said sensor measurements over at least a portion of said time interval, and wherein a decrease in sensitivity of said sensor is detected if the measurement of dispersion of a rate change in said blood glucose sensor measurements does not exceed a first threshold and the mean value of said sensor measurements does not exceed a second threshold.

9. The method of claim 1, wherein said fluid comprises interstitial fluid.

10. The method of claim 1, wherein said detecting said change in responsiveness of said glucose sensor to the presence of glucose in said fluid further comprises:

defining a sequence of windows in time;

for at least one of said windows, computing a dispersion of said rate of change; and

determining at least one of said sensitivity metrics based, at least in part, on said computed dispersion.

11. The method of claim 10, wherein determining said at least one of said sensitivity metrics further comprises determining said at least one of said sensitivity metrics based, at least in part, on a ratio of said computed dispersion and a mean value of glucose sensor measurements obtained in said at least one of said windows.

12. An apparatus comprising:

a glucose sensor to obtain measurements responsive to a presence of glucose in a fluid; and

a processor to;

detect a change in responsiveness of said glucose sensor to said presence of glucose in a fluid based, at least in part, on an application of one or more thresholds to one or more sensitivity metrics,

at least one of said sensitivity metrics being computed based, at least part, on said measurements.

13. The apparatus of claim 12, wherein said change in responsiveness comprises a decrease in sensitivity of said glucose sensor to the presence of glucose in said fluid.

14. The apparatus of claim 12, wherein at least one of said sensitivity metrics comprises a measurement of dispersion of a rate change in said blood glucose sensor measurements over at least a portion of said time interval.

15. The apparatus of claim 14, wherein said measurement of dispersion of said rate of change comprises a variance of said rate of change.

16. The apparatus of claim 12, wherein said change in responsiveness of said glucose sensor to the presence of glucose in said fluid is detected by:

defining a sequence of windows in time;

for at least one of said windows, computing a dispersion of said rate of change; and

determining at least one of said sensitivity metrics based, at least in part, on said computed dispersion.

17. The apparatus of claim 16, wherein said at least one of said sensitivity metrics are detected by determining said at least one of said sensitivity metrics based, at least in part, on a ratio of said computed dispersion and a mean value of glucose sensor measurements obtained in said at least one of said windows.

18. An article comprising:

a non-transitory storage medium having machine-readable instructions stored thereon which are executable by a special purpose computing apparatus to;

obtain a plurality of glucose sensor measurements at a glucose sensor over a time interval; and

detect a change in responsiveness of said glucose sensor to a presence of glucose in a fluid based, at least in part, on an application of one or more thresholds to one or more sensitivity metrics, at least one of said sensitivity metrics being based, at least in part, on said glucose sensor measurements.

19. The article of claim 18, wherein said change in responsiveness comprises a decrease in sensitivity of said glucose sensor to the presence of glucose in said fluid.

20. The article of claim 18, wherein at least one of said sensitivity metrics comprises a measurement of dispersion of a rate change in said blood glucose sensor measurements over at least a portion of said time interval.

21. The article of claim 20, wherein said measurement of dispersion of said rate of change comprises a variance of said rate of change.

22. The article of claim 18, wherein said change in responsiveness of said glucose sensor to the presence of glucose in said fluid is detected by:

defining a sequence of windows in time;

for at least one of said windows, computing a dispersion of said rate of change; and

determining at least one of said sensitivity metrics based, at least in part, on said computed dispersion.

23. An apparatus comprising:

means for obtaining a plurality of glucose sensor measurements at a glucose sensor over a time interval; and

means for detecting a change in responsiveness of said glucose sensor to a presence of glucose in a fluid based, at least in part, on an application of one or more thresholds to one or more sensitivity metrics, at least one of said sensitivity metrics being based, at least in part, on said glucose sensor measurements.