AUTOMATED DETECTION OF A PHYSICAL BEHAVIOR EVENT AND CORRESPONDING ADJUSTMENT OF A MEDICATION DISPENSING SYSTEM BASED ON HISTORICAL EVENTS

• US 20200135320A1
• Filed: 10/29/2019
• Published: 04/30/2020
• Est. Priority Date: 10/31/2018
• Status: Abandoned Application

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Vleugels, Katelijn
• Application Number:
  US16/667,650
• Publication Number:
  US 20200135320A1
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/6802 Sensor mounted on worn items
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/13 delivered from dispensers
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• 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

Abstract

An automated medication dispensing system provides for triggering a medication administration message when an inferred event is detected for which a medication administration message is to be sent. The event might be the start, the beginning, or an anticipation of a start, of an eating event, detected by an event detection module from gestures of a user from a set of sensor readings. The message can be a signal to medication dispensing apparatus, and/or a reminder message to the user, an ancillary message to a caregiver, health professional, or others. The medication administration message might comprise a signal to an input of an insulin management system or an input of a meal-aware artificial pancreas. The events might also include a drinking event, a smoking event, a personal hygiene event, and/or a medication related event.

Claims

1. An automated medication dosing and dispensing system comprising:

sensors to detect movement related to a user of the automated medication dosing and dispensing system;

a computer-readable storage medium comprising program code instructions; and

a processor, wherein the program code instructions are configurable to cause the processor to perform a method comprising the steps of;

determining, from sensor readings obtained from the sensors, a start or an anticipated start of a current food intake event of the user;

reviewing historical data collected for previously recorded food intake events of the user;

identifying a correlation between the current food intake event and a number of the previously recorded food intake events; and

adjusting medication dosage, medication dispensing parameters, or both medication dosage and medication dispensing parameters based on the identified correlation.

2. The system of claim 1, wherein at least one of the sensor readings measures a movement of a body part of the user.

3. The system of claim 1, further comprising an event detection module to determine, from the sensor readings, a physical behavior event of the user.

4. The system of claim 3, wherein the event detection module determines gestures of the user that characterize the current food intake event.

5. The system of claim 1, wherein the adjusting is based on at least one of the following characteristics of the food intake event:

time duration;

pace;

start time;

end time;

number of bites;

number of sips;

eating method;

type of utensils used;

type of containers used;

amount of chewing before swallowing;

chewing speed;

amount of food consumed;

time between bites;

time between sips;

content of food consumed.

6. The system of claim 1, wherein:

the medication managed by the system is insulin; and

the adjusting step calculates a dosage of insulin to be administered and a schedule for delivery of the calculated dosage of insulin.

7. The system of claim 1, wherein the sensors comprise an accelerometer that measures movement of an arm of the user and a gyroscope that measures rotation of the arm of the user.

8. The system of claim 1, wherein the historical data comprises parameters that are not directly linked to the food intake event.

9. The system of claim 8, wherein the parameters include at least one of:

location information;

time of day the user wakes up;

stress level;

sleeping behavior patterns;

calendar event details;

phone call information;

email meta-data.

10. A method of operating an automated medication dosing and dispensing system having sensors to detect movement related to a user, the method comprising the steps of:

determining, from sensor readings obtained from the sensors, a start or an anticipated start of a current food intake event of the user;

reviewing historical data collected for previously recorded food intake events of the user;

identifying a correlation between the current food intake event and a number of the previously recorded food intake events; and

adjusting medication dosage, medication dispensing parameters, or both medication dosage and medication dispensing parameters based on the identified correlation.

11. The method of claim 10, wherein at least one of the sensor readings measures a movement of a body part of the user.

12. The method of claim 10, further comprising the step of determining, from the sensor readings, physical behavior events of the user.

13. The method of claim 12, wherein the physical behavior events determined from the sensor readings include gestures of the user that characterize the current food intake event.

14. The method of claim 10, wherein the adjusting is based on at least one of the following characteristics of the food intake event:

time duration;

pace;

start time;

end time;

number of bites;

number of sips;

eating method;

type of utensils used;

type of containers used;

amount of chewing before swallowing;

chewing speed;

amount of food consumed;

time between bites;

time between sips;

content of food consumed.

15. The method of claim 10, wherein:

the medication managed by the system is insulin; and

the adjusting step calculates a dosage of insulin to be administered and a schedule for delivery of the calculated dosage of insulin.

16. The method of claim 10, wherein the sensors comprise an accelerometer that measures movement of an arm of the user and a gyroscope that measures rotation of the arm of the user.

17. The method of claim 10 wherein the historical data comprises parameters that are not directly linked to the food intake event.

18. The method of claim 17, wherein the parameters include at least one of:

location information;

time of day the user wakes up;

stress level;

sleeping behavior patterns;

calendar event details;

phone call information;

email meta-data.

19. The method of claim 10, wherein the adjusting is performed upon detection of an actual or imminent start of the current food intake event.

20. The method of claim 10, wherein the adjusting is based on characteristics of the current gesture-based physical behavior event.