Infusion systems and methods for patient activity adjustments

• US 10,854,322 B2
• Filed: 12/19/2017
• Issued: 12/01/2020
• Est. Priority Date: 12/21/2016
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Sadeghzadeh, Mahta, Grosman, Benyamin, Legray, David, Rankers, Ulrich H., Roy, Anirban, Vargas, Steven J.
• Primary Examiner(s): Mendez, Manuel A
• Application Number:
  US15/847,748
• Publication Number:
  US 20180169332A1
• Time in Patent Office: 1,078 Days
• 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 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 5/7465 Arrangements for interactive communication between patient and care services, e.g. by using a telephone network telemetry of measured physiological signal A61B5/0002
• CPC Class Codes: A61K 38/28 Insulins
• CPC Class Codes: A61M 2005/14208 with a programmable infusion control system, characterised by the infusion program
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/3303 Using a biosensor
• CPC Class Codes: A61M 2205/35 Communication
• CPC Class Codes: A61M 2205/3569 sublocal, e.g. between console and disposable
• CPC Class Codes: A61M 2205/3584 using modem, internet or bluetooth
• CPC Class Codes: A61M 2205/3592 using telemetric means, e.g. radio or optical transmission
• CPC Class Codes: A61M 2205/50 with microprocessors or computers
• CPC Class Codes: A61M 2205/502 User interfaces, e.g. screens or keyboards
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2205/8206 battery-operated
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 2230/63 Motion, e.g. physical activity
• CPC Class Codes: A61M 5/142 Pressure infusion, e.g. using pumps
• CPC Class Codes: A61M 5/14244 adapted to be carried by the patient, e.g. portable on the body
• CPC Class Codes: A61M 5/145 : using pressurised reservoirs, e.g. pressurised by means of pistons
• CPC Class Codes: A61M 5/16804 : Flow controllers
• CPC Class Codes: A61M 5/16831 : Monitoring, detecting, signalling or eliminating infusion flow anomalies low-level float-valves causing cut-off A61M5/40; indicating or recording presence, absence or direction of flow in general G01P13/0066
• CPC Class Codes: A61M 5/16877 : Adjusting flow; Devices for setting a flow rate
• 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: G16H 10/20 : for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 : for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/17 : delivered via infusion or injection
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/60 : relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders

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 patient involves obtaining, by a control system associated with the infusion device, user input indicating an activity by the patient, obtaining historical data for the patient corresponding to the activity, determining a probable patient response corresponding to the activity based at least in part on the historical data for the patient, determining an adjustment for delivering the fluid by the infusion device based at least in part on the probable patient response, and operating the infusion device to deliver the fluid to the patient in accordance with the adjustment.

Claims

1. A method of operating an infusion device capable of delivering fluid to a patient, the fluid influencing a physiological condition of the patient, the method comprising:

obtaining, by a control system associated with the infusion device, user input indicating a future activity by the patient;

obtaining, by the control system, historical data for the patient corresponding to the future activity;

determining, by the control system, a probable patient response corresponding to the future activity based at least in part on the historical data for the patient;

determining, by the control system, an adjustment for delivering the fluid by the infusion device based at least in part on the probable patient response to the future activity; and

operating, by the control system, the infusion device to deliver the fluid to the patient in accordance with the adjustment.

2. The method of claim 1, further comprising identifying a current operational context for the infusion device, wherein determining the probable patient response comprises determining the probable patient response based at least in part on a correlation between the historical data corresponding to the future activity and the current operational context.

3. The method of claim 2, the historical data including historical measurement data indicative of the physiological condition of the patient and historical operational context data associated with the historical measurement data, the method further comprising determining a model characterizing the probable patient response as a function of an operational context for the infusion device based on a correlation between the historical measurement data and the historical operational context data associated therewith, wherein determining the probable patient response comprises applying the model to the current operational context.

4. The method of claim 1, further comprising:

obtaining, by the control system, a second user input indicating a characteristic of a meal;

determining, by the control system, a meal bolus dosage based at least in part on the characteristic, wherein determining the adjustment comprises adjusting the meal bolus dosage based at least in part on the probable patient response.

5. The method of claim 1, wherein:

determining the adjustment comprises adjusting a target value for the physiological condition based on a relationship between the probable patient response and the target value, resulting in an adjusted target value; and

operating the infusion device to deliver the fluid to the patient in accordance with the adjustment comprises;

determining a dosage command based at least in part on a difference between a current measurement value for the physiological condition and the adjusted target value; and

operating an actuation arrangement of the infusion device to deliver an amount of the fluid corresponding to the dosage command.

6. The method of claim 1, wherein:

obtaining the historical data comprises;

identifying previous events corresponding to the future activity using event log data associated with the patient; and

obtaining historical context data associated with the previous events and historical measurement data corresponding to the previous events, wherein the historical measurement data is indicative of the physiological condition contemporaneous to the respective previous events; and

determining the probable patient response comprises;

determining a model for a physiological response of the patient based on a correlation between the historical measurement data and historical context data associated with the previous events; and

applying the model to a current operational context to obtain the probable patient response.

7. The method of claim 6, wherein the historical context data comprises timestamps associated with the previous events and the current operational context comprises a current time of day.

8. The method of claim 1, the future activity comprising exercise, wherein:

obtaining the historical data comprises;

identifying previous exercise events using event log data associated with the patient; and

obtaining historical context data associated with the previous exercise events and historical measurement data corresponding to the previous exercise events, wherein the historical measurement data is indicative of the physiological condition contemporaneous to the respective previous exercise events; and

determining the probable patient response comprises;

determining a model for a physiological response of the patient based on a correlation between the historical measurement data and historical context data associated with the previous exercise events; and

applying the model to a current operational context to obtain the probable patient response.

9. The method of claim 1, the future activity comprising sleep, wherein:

obtaining the historical data comprises obtaining historical measurement data corresponding to a plurality of preceding overnight periods, wherein the historical measurement data is indicative of the physiological condition during respective ones of the plurality of preceding overnight periods; and

determining the probable patient response comprises determining the probable patient response based on the historical measurement data corresponding to the plurality of preceding overnight periods.

10. The method of claim 1, wherein:

the user input includes indication of an anticipated characteristic of the future activity;

the historical data includes historical characteristics associated with previous instances of the future activity and historical measurement data corresponding to the previous instances of the future activity; and

determining the probable patient response comprises;

determining a model for a physiological response of the patient based on a correlation between the historical measurement data and the historical characteristics associated with the previous instances of the future activity; and

applying the model to the anticipated characteristic of the future activity to obtain the probable patient response.

11. The method of claim 10, wherein the anticipated characteristic comprises an expected duration or an expected intensity of the future activity.

12. A computer-readable medium having instructions stored thereon that are executable by the control system associated with the infusion device to perform the method of claim 1.

13. A method of operating an infusion device capable of delivering insulin to a patient, the method comprising:

obtaining, by a control system associated with the infusion device, user input indicative of a future activity by the patient in the future;

obtaining, by the control system, historical glucose measurement data for the patient corresponding to previous instances of the future activity;

determining, by the control system, a probable glycemic response to the future activity for the patient based at least in part on the historical glucose measurement data for the previous instances of the future activity;

adjusting, by the control system, a closed-loop control parameter based at least in part on the probable glycemic response; and

after adjusting the closed-loop control parameter;

obtaining a sensor glucose measurement value for the patient; and

operating an actuation arrangement of the infusion device to deliver insulin to the patient based at least in part on the sensor glucose measurement value and the closed-loop control parameter.

14. The method of claim 13, wherein:

adjusting the closed-loop control parameter comprises adjusting a target glucose value for the patient to obtain an adjusted target glucose value; and

operating the actuation arrangement comprises determining a command for the actuation arrangement based at least in part on a difference between the sensor glucose measurement value and the adjusted target glucose value.

15. The method of claim 13, wherein determining the probable glycemic response to the future activity comprises:

determining a predicted characteristic associated with the future activity based on an operational context and a correlation between historical characteristics and historical operational contexts associated with the previous instances of the future activity; and

determining the probable glycemic response based on the predicted characteristic and a correlation between the historical glucose measurement data and the historical characteristics associated with the previous instances of the future activity.

16. The method of claim 15, wherein:

the operational context comprising a current time of day or a future time of day associated with the future activity;

determining the predicted characteristic comprises determining an expected duration of the future activity or an expected intensity of the future activity based on the current time of day and a correlation between historical times of day associated with the previous instances of the future activity and the respective duration or intensity of the respective previous instances of the future activity; and

determining the probable glycemic response comprises;

determining a model of a physiological response by the patient to the future activity as a function of a duration or an intensity of the future activity and a time of day based on correlations between historical glucose measurement data associated with respective ones of the previous instances of the future activity, a respective duration or a respective intensity associated with the respective ones of the previous instances of the future activity, and a respective time of day associated with the respective ones of the previous instances of the future activity; and

determining the probable glycemic response by applying the model to the predicted characteristic and the current time of day or the future time of day.

17. The method of claim 16, further comprising determining the future time of day associated with the future activity based at least in part on the historical times of day associated with the previous instances of the future activity.

18. The method of claim 13, further comprising determining a predicted characteristic associated with the future activity based on the previous instances of the future activity, wherein adjusting the closed-loop control parameter comprises temporarily adjusting the closed-loop control parameter for a duration of time influenced by the predicted characteristic.

19. An infusion system comprising:

an actuation arrangement operable to deliver fluid to a user, the fluid influencing a physiological condition of the user;

a user interface to receive user input indicative of a future activity by the user in the future;

a data storage element to maintain historical data corresponding to previous instances of the future activity by the user; and

a control system coupled to the actuation arrangement, the data storage element and the user interface to determine a probable physiological response by the user to the future activity based at least in part on the historical data, determine a fluid delivery adjustment based on the probable physiological response, and operate the actuation arrangement to deliver the fluid to the user in accordance with the fluid delivery adjustment.

20. The infusion system of claim 19, wherein:

the future activity comprises exercise or sleep;

the fluid comprises insulin; and

the fluid delivery adjustment comprises an adjusted meal bolus or an adjusted closed-loop control parameter.