Systems, methods and devices for providing a personalized exercise program recommendation

• US 10,112,075 B2
• Filed: 02/01/2016
• Issued: 10/30/2018
• Est. Priority Date: 02/01/2016
• Status: Active Grant

• Current Assignee: Logitech Europe S A (Logitech International SA)
• Original Assignee: Logitech Europe S A (Logitech International SA)
• Inventors: Wisbey, Ben, Armstrong, Judd, Diesterbeck, Hagen, Shepherd, David
• Primary Examiner(s): McClellan, James S
• Application Number:
  US15/012,755
• Publication Number:
  US 20170216671A1
• Time in Patent Office: 1,002 Days
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/6829 Foot or ankle
• CPC Class Codes: A63B 2024/0081 Coaching or training aspects related to a group of users
• CPC Class Codes: A63B 24/0075 Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
• CPC Class Codes: G06V 40/23 Recognition of whole body movements, e.g. for sport training
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation
• 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
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Systems, methods, and devices are provided for determining an exercise program recommendation for an anticipated exercise session. One such system includes a wearable device comprising a biosensor that monitors biometrics (e.g. heart rate); a motion sensor that monitors activity; a processor operatively coupled to the biosensor, the processor configured to process electronic signals periodically generated by the biosensor and the motion sensor; and a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to execute specific functions. In particular, the instructions are executed to cause the processor to generate biometric data from the biometrics (e.g. heart rate information in particular). Further, the instructions are executed to generate an exercise program recommendation for an anticipated exercise session, the exercise program recommendation comprising one or more of a reference activity type and a time interval, and wherein the exercise program recommendation is based on one or more of an exertion recommendation and an activity archive.

Claims

1. A system for providing an exercise program recommendation, the system comprising:

a wearable device, comprising;

a biosensor that detects biometric information;

a motion sensor that detects activity and generates activity information; and

a processor operatively coupled to the biosensor and the motion sensor, the processor configured to process electronic signals generated by the biosensor and the motion sensor and generate one or more of biometric data and activity data therefrom; and

a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to;

generate two or more exercise program recommendations for an anticipated future exercise session, the two or more exercise recommendations are ranked based on one or more of a time interval, a reference activity type, and an exertion measure, the exercise program recommendations comprising one or more reference activity types and a time interval,

wherein the exercise program recommendation is based on a recommendation regarding the amount of exertion to be performed within an activity and a stored activity archive, the activity archive comprising one or more of an exertion load, an exertion index, and a response profile associated with one or more previously performed exercise sessions, and

wherein the exertion recommendation is based on biometrics information received from the biosensor and the detected activity.

2. The system of claim 1, wherein the wearable device further comprises one or more of an earphone and a wristband.

3. The system of claim 1, wherein the biosensor comprises one or more of a finger biosensor, a wrist biosensor, and an optical heartrate sensor.

4. The system of claim 1, wherein the biometric data includes one or more of a heart rate and a heart rate variability.

5. The system of claim 1, further comprising:

a first wireless transceiver embedded in the wearable device;

a second wireless transceiver embedded in a computing device operatively coupled to the wearable device, and

wherein, the first and second wireless transceivers are configured to receive and send one or more of the biometric data and the activity data.

6. A system for providing an exercise program recommendation, the system comprising:

an electronic clock configured to monitor time;

a wearable device, comprising;

a biosensor that detects biometric information;

a motion sensor that detects activity and generates activity information; and

a processor operatively coupled to the biosensor and the motion sensor, the processor configured to process electronic signals generated by the biosensor and the motion sensor and generate one or more of biometric data and activity data therefrom; and

a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to;

generate two or more exercise program recommendations for a future exercise session, the two or more exercise recommendations are ranked based on one or more of a time interval, a reference activity type, and an exertion measure, the exercise program recommendations comprising one or more reference activity types and a time interval,

wherein the exercise program recommendations are based on a recommendation regarding the amount of exertion to be performed within an activity and a stored activity archive, and

wherein the exertion recommendation for the future exercise session is generated from an exertion model based on one or more of a response profile for a past exercise session, an exertion load for a past exercise session, and an exertion index for a past exercise session.

7. The system of claim 6, wherein the wearable device further comprises one or more of an earphone and a wristband.

8. The system of claim 6, wherein the biosensor comprises one or more of a finger biosensor, a wrist biosensor, and an optical heartrate sensor.

9. The system of claim 6, wherein the biometric data includes one or more of a heart rate and a heart rate variability.

10. The system of claim 6, wherein the biosensor monitors detects biometric information periodically at a predetermined frequency.

11. The system of claim 6, further comprising:

a first wireless transceiver embedded in the wearable device; and

a second wireless transceiver embedded in a computing device operatively coupled to the wearable device,

wherein the first and second wireless transceivers are configured to receive and send one or more of the biometric data and the activity data.

12. A computer-implemented method for determining an exercise program recommendation for an anticipated future exercise session, the method comprising:

detecting biometric information using a biosensor embedded in a wearable device;

detecting activity using a motion sensor embedded in a wearable device;

generating biometric data from the detected biometric information;

generating activity data from the detected activity;

generating an exercise intensity value based on biometric information detected by the biosensor and the activity detected by the motion sensor;

generating an exertion value based on the exercise intensity value;

generating one or more of an exertion load and an exertion index based on a plurality of exertion values;

generating a response profile based on biometric information detected by the biosensor and the activity detected by the motion sensor;

storing in an activity archive one or more of the biometric data, the activity data, the exertion load, the exertion index, and the response profile;

generating an exertion recommendation for a future exercise session; and

generating two or more exercise program recommendations based on the exertion recommendation and the data stored in the activity archive,

wherein the two or more exercise recommendations are ranked based on one or more of a time interval, a reference activity type, and an exertion measure.

13. The computer-implemented method of claim 12, wherein generating an exertion value comprises:

weighting each of a plurality of exercise intensity values based on each exercise intensity value'"'"'s proximity in time to the most recent exercise intensity value;

aggregating the weighted plurality of exercise intensity values over a measuring period; and

generating an exertion value based on the aggregation of the weighted plurality of exercise intensity values for the measuring period.

14. The computer-implemented method of claim 12, wherein generating a response profile comprises:

calculating a current HRV value from the biometric data;

calculating, based on a set of HRV values previously calculated using the biometric data, an average HRV value and an HRV variation;

calculating the HRV score based on a difference between the average HRV value and the current HRV value, the difference being scaled by the HRV variation; and

creating a response profile based on one or more a heart rate variability (HRV) score based on the biometric data, a fatigue score based on the activity data, a predicted HRV score based on the biometric data and the activity data, and a predicted fatigue score based on one or more of the biometric data and the activity data.

15. The computer-implemented method of claim 12, wherein the wearable device further comprises one or more of an earphone and a wristband.

16. The computer-implemented method of claim 12, wherein the biosensor comprises one or more of a finger biosensor, a wrist biosensor, and an optical heartrate sensor.

17. The computer-implemented method of claim 12, wherein the biometric data includes one or more of a heart rate and a heart rate variability.