IP Library › Granted Patent US 10,568,570
Granted Patent B1
US 10,568,570 · App. 16/276,105 · Granted Feb 25, 2020

Methods and systems for providing a preferred fitness state of a user

Inventor: Trungram Gyaltrul Sherpa (Cambridge, MA)
A61B5/486A61B5/0002A61B5/0077A61B5/04A61B5/0531A61B5/6802A61B5/7267A61B5/7435G06N5/04G06N20/00G16H50/20A61B2562/0204A61B2562/0219A61B2562/0271
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Quick Facts
Patent No.
US 10,568,570
App. No.
16/276,105
Filed
Feb 14, 2019
Granted
Feb 25, 2020
Kind
B1
Art Unit
3792
USPC
600/301
Abstract

Systems and methods for providing a preferred fitness state of a use are disclosed. The system includes at least a sensor that detects at least a biological parameter of a user and a fitness state sorting module that generates a current user fitness state using machine-learning and the at least a biological parameter. Methods of providing a preferred fitness state of a user include detecting at least a biological parameter of a user, determining by a fitness state sorting module a current user fitness state and determining a user specific recommendation by the fitness state sorting module.

Claims (33)

1. A system for machine-learning data analysis for determining a fitness state of a user, the system comprising:

at least a sensor designed and configured to detect at least a biological parameter of a user and transmit a data signal containing the at least a biological parameter;

a biological parameter processing module operating on a computing device, wherein the biological parameter processing module is configured to:

receive the data signal containing at least a biological parameter; and

parse the data signal to extract the at least a biological parameter;

a demographic processing module operating on the computing device, wherein the demographic processing module is configured to receive at least a user input from the user, wherein the at least a user input includes a desired fitness state of the user;

a fitness state sorting module operating on the computing device wherein:

the fitness state sorting module includes a fitness state model relating biological parameters to fitness states;

the fitness state sorting module includes a user specific recommendation model relating fitness states to user specific recommendations and

the fitness state sorting module is configured to generate a current user fitness state using the fitness state model and the at least a biological parameter and generate a user specific recommendation using the user specific recommendation model and the at least a user input wherein the at least a user input includes a goal fitness level; and

a user interface configured to provide the current user fitness state and the user specific recommendation to the user.

2. A system for machine-learning data analysis for determining a fitness state of a user, the system comprising:

at least a sensor designed and configured to detect at least a biological parameter of a user and transmit a data signal; and

a fitness state sorting module operating on the computing device wherein:

the fitness state sorting module includes a fitness state model relating biological parameters to fitness states;

the fitness state sorting module includes a user specific recommendation model relating fitness states to user specific recommendations;

the fitness state sorting module is configured to generate a current user fitness state using the fitness state model and the at least a biological parameter and

the fitness state sorting module is configured to generate a user specific recommendation using the user specific recommendation model and a goal fitness level wherein the fitness state sorting module is configured to generate the goal fitness level using the fitness state model.

3. The system of claim 2 , wherein the at least a sensor further comprises a camera.

4. The system of claim 2 , wherein the at least a sensor further comprises a thermal sensor.

5. The system of claim 2 , wherein the at least a sensor further comprises an electrophysiological sensor.

6. The system of claim 2 , wherein the at least a sensor further comprises an electrodermal sensor.

7. The system of claim 2 , wherein the at least a sensor further comprises an acoustic sensor.

8. The system of claim 2 , wherein the at least a sensor further comprises a motion sensor.

9. The system of claim 2 , wherein the at least a sensor further comprises a wearable device.

10. The system of claim 2 , wherein the user specific recommendation further comprises a recommended exercise.

11. The system of claim 2 , wherein the fitness state sorting module further comprises at least one of a strength state fitness module, an endurance state fitness module, and a well-being fitness state module.

12. The system of claim 1 , wherein the fitness state model is generated by:

receiving a training set including a plurality of input data containing biological parameters and a plurality of output data containing fitness states associated with the biological parameters of the plurality of input data; and

generating the fitness state model from the training set using a machine-learning algorithm.

13. The system of claim 1 , wherein the user specific recommendation model is generated by:

receiving a training set including a plurality of input data containing fitness states and a plurality of output data containing user specific recommendations associated with the biological parameters of the plurality of input data; and

generating the user specific recommendation model from the training set using a machine-learning algorithm.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 17, 2024
From: SHERPA, TRUNGRAM GYALTRUL
To: SUMMIT INNOVATIONS GROUP, LLC
Reel/Frame 067449/0892 →
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