GLUCOSE SENSOR HEALTH MONITORING AND RELATED METHODS AND SYSTEMS

• US 20150331419A1
• Filed: 05/19/2014
• Published: 11/19/2015
• Est. Priority Date: 05/19/2014
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Nogueira, Keith, Li, Xiaolong, Shah, Rajiv, Kannard, Brian T.
• Granted Patent: US 10,152,049 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61M 2205/70 with testing or calibration facilities
• CPC Class Codes: A61M 2205/702 automatically during use
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/14244 adapted to be carried by the patient, e.g. portable on the body
• 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: G05B 23/00 Testing or monitoring of control systems or parts thereof monitoring of programme-control systems G05B19/048, G05B19/406

Abstract

Infusion systems, infusion devices, and related operating methods are provided. An exemplary method of operating an infusion device capable of delivering fluid to a user involves determining one or more signal characteristics associated with a subset of the measurements corresponding to a monitoring period, determining a reliability metric for the monitoring period based on the one or more signal characteristics, and providing indication of a maintenance condition when the reliability metric violates a threshold.

Claims

1. A method of operating an infusion device operable to deliver fluid to a user based on measurements indicative of a physiological condition of the user provided by a sensing arrangement, the fluid influencing the physiological condition of the user, the method comprising:

determining one or more signal characteristics associated with a subset of the measurements, the subset of measurements corresponding to a monitoring period;

determining a reliability metric for the monitoring period based on the one or more signal characteristics; and

providing indication of a maintenance condition when the reliability metric violates a first threshold.

2. The method of claim 1, further comprising determining a number of consecutive monitoring periods that violated the first threshold when the reliability metric for the monitoring period violates the first threshold, wherein providing the indication comprises automatically providing the indication when the number of consecutive monitoring periods is greater than a second threshold.

3. The method of claim 1, wherein:

determining the one or more signal characteristics comprises determining a noise metric for each respective measurement of the subset; and

determining the reliability metric comprises determining a number of high noise measurements based on the noise metrics for the respective measurements of the subset.

4. The method of claim 3, wherein:

determining the one or more signal characteristics further comprises determining an average measurement value for the monitoring period based on the subset of the measurements; and

determining the reliability metric further comprises determining the reliability metric based at least in part on a ratio of the average measurement value to the number of high noise measurements.

5. The method of claim 4, further comprising determining a second number of consecutive monitoring periods that violated the first threshold when the reliability metric for the monitoring period violates the first threshold, wherein providing the indication comprises providing the indication when the second number of consecutive monitoring periods is greater than a second threshold.

6. The method of claim 3, wherein determining the noise metric comprises, for each respective measurement of the subset:

determining a second derivative metric associated with the respective measurement based at least in part on one or more measurements preceding the respective measurement; and

scaling the second derivative metric by a calibration factor for converting the respective measurement to a measurement value for the physiological condition.

7. The method of claim 6, wherein determining the number of high noise measurements comprises determining the number of respective measurements of the subset having an associated noise metric greater than a threshold value.

8. The method of claim 7, further comprising determining a second number of consecutive monitoring periods that violated the first threshold when the reliability metric for the monitoring period violates the first threshold, wherein providing the indication comprises providing the indication when the second number of consecutive monitoring periods is greater than a second threshold.

9. The method of claim 1, further comprising determining the measurements based on output signals provided by a sensing element of the sensing arrangement, the output signals being influenced by the physiological condition, wherein providing the indication comprises generating a user notification indicating replacement of the sensing element.

10. A computer-readable medium having computer-executable instructions stored thereon that, when executed by a control module, cause the control module to perform the method of claim 1.

11. An infusion system comprising:

a sensing element providing output signals influenced by a physiological condition in a body of a user; and

a control module coupled to the sensing element to determine filtered measurements based on the output signals, determine one or more signal characteristics associated with a subset of the filtered measurements corresponding to a monitoring period, determine a reliability metric for the monitoring period based on the one or more signal characteristics, and provide indication of a maintenance condition for the sensing element when the reliability metric violates a first threshold.

12. The infusion system of claim 11, further comprising an output user interface element coupled to the control module, wherein providing the indication comprises the control module generating a user notification indicating replacement of the sensing element when the reliability metric violates the first threshold.

13. The infusion system of claim 11, wherein:

the one or more signal characteristics comprise a respective noise metric for each respective filtered measurement of the subset and an average measurement value for the monitoring period based on the subset of the filtered measurements;

the reliability metric comprises a ratio of the average measurement value to a number of high noise measurements over the monitoring period; and

the number of high noise measurements comprises a number of filtered measurements of the subset having respective noise metrics that violate a second threshold.

14. The infusion system of claim 13, wherein the respective noise metric for each respective filtered measurement comprises a second derivative metric associated with the respective filtered measurement scaled by a calibration factor for converting the respective measurement to a measurement value for the physiological condition.

15. The infusion system of claim 13, wherein the control module determines a second number of consecutive monitoring periods that violated the first threshold when the reliability metric for the monitoring period violates the first threshold and automatically provides the indication when the second number of consecutive monitoring periods is greater than a third threshold.

16. A method of operating an infusion device operable to deliver insulin to a body of a user, the method comprising:

determining filtered measurements indicative of a glucose level in the body of the user based on output signals from a sensing element influenced by the glucose level in the body;

determining one or more signal characteristics associated with a subset of the filtered measurements that correspond to a monitoring period;

determining a reliability metric for the monitoring period based on the one or more signal characteristics; and

providing a user notification to replace the sensing element when the reliability metric violates a first threshold.

17. The method of claim 16, wherein:

determining the reliability metric comprises determining a ratio of an average measurement value for the monitoring period to a number of high noise measurements during the monitoring period; and

providing the user notification comprises providing the user notification when the reliability metric is less than the first threshold.

18. The method of claim 17, wherein determining the number of high noise measurements comprises:

determining a respective noise metric associated with each respective filtered measurement of the subset; and

determining the number of respective filtered measurements of the subset having an associated noise metric greater than a threshold value.

19. The method of claim 18, wherein determining the respective noise metric comprises:

determining a second derivative metric associated with the respective filtered measurement of the subset; and

scaling the second derivative metric by a calibration factor for converting the respective filtered measurement to a measurement value for the glucose level.

20. The method of claim 17, further comprising determining a second number of consecutive monitoring periods having an associated reliability metric less than the first threshold when the reliability metric for the monitoring period is less than the first threshold, wherein providing the user notification comprises automatically providing the user notification when the second number of consecutive monitoring periods is greater than a second threshold.