ADAPTIVE SIGNAL PROCESSING FOR INFUSION DEVICES AND RELATED METHODS AND SYSTEMS

• US 20150328402A1
• 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, Agrawal, Pratik, Kannard, Brian T., Li, Xiaolong, Liang, Bradley C., Shah, Rajiv, Zhong, Yuxiang
• Granted Patent: US 10,007,765 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61M 2205/3303 Using a biosensor
• 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 15/02 electric
• CPC Class Codes: G16H 20/17 delivered via infusion or injection

Abstract

Infusion systems, infusion devices, and related operating methods are provided. An exemplary method of operating an infusion device involves obtaining a filtered measurement indicative of a physiological condition of a user, determining a metric indicative of a characteristic of the filtered measurement based at least in part on one or more derivative metrics associated with the filtered measurement, and determining an output measurement indicative of the physiological condition of the user based at least in part on the filtered measurement, the metric, and a previous output measurement.

Claims

1. A method of operating an infusion device operable to deliver fluid to a user, the fluid influencing a physiological condition of the user, the method comprising:

obtaining a filtered measurement indicative of the physiological condition of the user;

determining a metric indicative of a characteristic of the filtered measurement based at least in part on one or more derivative metrics associated with the filtered measurement; and

determining an output measurement indicative of the physiological condition of the user based at least in part on the filtered measurement, the metric, and a previous output measurement.

2. The method of claim 1, wherein:

determining the metric comprises determining a process variance metric associated with the filtered measurement based at least in part on a first derivative metric associated with the filtered measurement and a second derivative metric associated with the filtered measurement; and

determining the output measurement comprises determining the output measurement based at least in part on the filtered measurement, the process variance metric, and the previous output measurement.

3. The method of claim 2, wherein determining the process variance metric comprises:

determining a frequency estimate associated with the filtered measurement based on the first derivative metric;

determining a noise estimate associated with the filtered measurement based on the second derivative metric; and

determining the process variance metric as a function of the frequency estimate and the noise estimate.

4. The method of claim 3, wherein:

determining the frequency estimate comprises scaling the first derivative metric by a calibration factor for converting the output measurement to a sensed value for the physiological condition, the first derivative metric comprising an average of first derivative values associated with the filtered measurement and one or more preceding filtered measurements; and

determining the noise estimate comprises scaling the second derivative metric by the calibration factor, the second derivative metric comprising an average of second derivative values associated with the filtered measurement and the one or more preceding filtered measurements.

5. The method of claim 3, further comprising:

determining a rate of change metric associated with the filtered measurement based at least in part on the first derivative metric;

scaling the rate of change metric for the filtered measurement based on the noise estimate when the noise estimate is less than a threshold value, resulting in a scaled rate of change metric; and

adding the scaled rate of change metric to the filtered measurement to obtain an adjusted filtered measurement, wherein determining the output measurement comprises determining the output measurement based at least in part on the adjusted filtered measurement, the process variance metric, and the previous output measurement.

6. The method of claim 1, further comprising:

identifying a dropout condition based at least in part the one or more derivative metrics associated with the filtered measurement; and

determining an adjusted filtered measurement in response to identifying the dropout condition, wherein determining the output measurement comprises determining the output measurement based at least in part on the adjusted filtered measurement, the metric, and the previous output measurement.

7. The method of claim 6, further comprising modifying the metric in response to identifying the dropout condition.

8. The method of claim 6, wherein identifying the dropout condition comprises identifying the dropout condition when a first derivative metric associated with the filtered measurement is greater than a first derivative dropout threshold value and a second derivative metric associated with the filtered measurement is less than a second derivative dropout threshold value.

9. The method of claim 1, further comprising adjusting the filtered measurement to compensate for delay based at least in part on the one or more derivative metrics associated with the filtered measurement, resulting in an adjusted filtered measurement, wherein determining the output measurement comprises determining the output measurement based on the adjusted filtered measurement, the metric, and the previous output measurement.

10. The method of claim 9, further comprising determining a noise estimate associated with the filtered measurement based on a second derivative metric associated with the filtered measurement, wherein adjusting the filtered measurement comprises:

scaling a rate of change metric for the filtered measurement based on the noise estimate when the noise estimate is less than a threshold value, resulting in a scaled rate of change metric; and

adding the scaled rate of change metric to the filtered measurement to obtain the adjusted filtered measurement.

11. The method of claim 1, further comprising identifying an artifact condition when a difference between the filtered measurement and a preceding filtered measurement exceeds a threshold value, wherein determining the output measurement comprises maintaining the previous output measurement in response to the artifact condition.

12. The method of claim 1, the filtered measurement being based on one or more output signals from a sensing element, the method further comprising:

determining a sensed value for the physiological condition of the user based on the output measurement and a calibration factor associated with the sensing element;

determining a delivery command based at least in part on a difference between the sensed value and a target value for the physiological condition of the user; and

operating the infusion device to deliver the fluid to the user in accordance with the delivery command.

13. 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.

14. A device comprising:

a sensing element to provide one or more signals influenced by a physiological condition of a user; and

a control module coupled to the sensing element to;

determine a filtered measurement based on the one or more signals;

determine a metric indicative of a characteristic of the filtered measurement based at least in part on one or more derivative metrics associated with the filtered measurement; and

determine an output measurement indicative of the physiological condition of the user based at least in part on the filtered measurement, the metric, and a previous output measurement.

15. The device of claim 14, further comprising a communications interface to transmit the output measurement to an infusion device, wherein operation of the infusion device to regulate the physiological condition of the user is influenced by the output measurement.

16. The device of claim 14, further comprising:

a first data storage element to maintain the one or more signals; and

a second data storage element to maintain the filtered measurement.

17. An infusion system comprising:

a sensing arrangement including a sensing element to provide one or more signals corresponding to a physiological condition in a body of a user that is sensed by the sensing element, the sensing arrangement determining an output measurement indicative of the physiological condition based at least in part on a filtered measurement based on the one or more signals, a metric indicative of a characteristic of the filtered measurement, and a previous output measurement; and

an infusion device comprising;

a motor operable to deliver fluid to the body of the user, the fluid influencing the physiological condition; and

a control system to receive the output measurement and determine a delivery command for operating the motor based at least in part on the output measurement.

18. The infusion system of claim 17, the sensing arrangement determining a calibration factor for converting the output measurement to a sensed value for the physiological condition, wherein:

the metric is influenced by the calibration factor; and

the control system determines the delivery command based at least in part on the sensed value.

19. The infusion system of claim 18, the sensing arrangement identifying a dropout condition based at least in part on one or more derivative metrics associated with the filtered measurement and determining a dropout compensated filtered measurement in response to identifying the dropout condition, the output measurement being determined based at least in part on the dropout compensated filtered measurement, wherein the infusion device further comprises a display to present a graphical representation of the sensed value determined based on the dropout compensated filtered measurement.

20. The infusion system of claim 18, the sensing arrangement identifying an artifact condition when a difference between the filtered measurement and a preceding filtered measurement exceeds a threshold value and determining the output measurement by maintaining the previous output measurement in response to the artifact condition, wherein the infusion device further comprises a display to present a graphical representation of the sensed value determined based on the previous output measurement after identifying the artifact condition.