Movement based fitness and fitness product management

• US 10,360,811 B2
• Filed: 01/05/2016
• Issued: 07/23/2019
• Est. Priority Date: 01/06/2015
• Status: Active Grant

• Current Assignee: asensei, Inc.
• Original Assignee: asensei, Inc.
• Inventors: Webster, Steven, Arnott, Ross, Burgar, William
• Primary Examiner(s): Bullington, Robert P
• Application Number:
  US14/987,995
• Publication Number:
  US 20160193500A1
• Time in Patent Office: 1,295 Days
• Field of Search: 434247
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G09B 19/0038 Sports

Abstract

Raw motion data generated by sensors affixed to a user performing exercises or poses in response to perceiving content annotated with a motion track and presented to the user, the motion track generated using a posture dictionary is collected. The exercises or poses are determined from the raw motion data using the posture dictionary. Motion data indicating the exercises or poses within the raw motion data is generated using the raw motion data. The user is graded in performing the exercises or poses by comparing the motion data with the motion track. The content is presented to the user based on the grading of the user.

Claims

1. A method comprising:

using a posture dictionary to generate a motion track;

presenting to a user content annotated with the motion track;

obtaining garment data associated with an identified garment worn by the user;

pairing the identified garment to sensors using the garment data, wherein pairing the identified garment to the sensors provides a predicted location of the sensors on the user'"'"'s body;

gathering raw motion data generated by the sensors when the user performs exercises or poses;

determining a first exercise or pose of the exercises or poses from the raw motion data using the posture dictionary and the predicted location of the sensors on the user'"'"'s body;

generating motion data for the first exercise or pose using the raw motion data and the predicted location of the sensors on the user'"'"'s body;

grading the user in performing the first exercise or pose by comparing the motion data with the motion track; and

presenting to the user second content derived from the grading of the user.

2. The method of claim 1, further comprising:

updating user data of the user to include an identification of the identified garment, wherein the user data is utilized to present to the user an advertisement of a product.

3. The method of claim 1, further comprising:

gathering expert raw motion data generated by a plurality of sensors affixed to an expert performing the exercises or poses;

receiving a video of the expert performing the exercises or poses;

building the posture dictionary based on the expert raw motion data and the video of the expert performing the exercises or poses.

4. The method of claim 1, wherein the second content derived from the grading of the user is linear and presenting the content to the user derived from the grading of the user further comprises presenting different portions of linear content non-linearly based on the grading of the user.

5. The method of claim 1, further comprising segmenting the user to a skill level of a particular skill, based on the grading of the user, using a skills matrix for the particular skill.

6. The method of claim 1, further comprising:

segmenting the user to a skill level of a particular skill, based on the grading of the user, using a skills matrix for the particular skill;

recommending new content to the user based on the skill level to which the user is segmented.

7. The method of claim 1, further comprising identifying an identification of the identified garment worn by the user from a signature received from the garment wirelessly.

8. The method of claim 1, wherein the motion track includes embedded content directors, wherein the embedded content directors are used in presenting to the user the second content derived from the grading of the user.

9. The method of claim 1, wherein the motion track includes embedded content directors, the embedded content directors used in presenting to the user second content derived from the grading of the user.

20. The method of claim 1, further comprising:

determining a second exercise or pose of the exercises or poses from the raw motion data using the posture dictionary and the predicted location of the sensors on the user'"'"'s body;

generating second motion data for the second exercise or pose using the raw motion data and the predicted location of the sensors on the user'"'"'s body.

10. A system comprising:

sensors affixed to a user;

a content presentation control engine that;

uses a posture dictionary to generate a motion track;

presents content annotated with the motion track to the user;

a garment detection engine that;

obtains garment data associated with an identified garment worn by the user;

pairs the identified garment to the sensors using the garment data, wherein pairing the identified garment to the sensors provides a predicted location of the sensors on the user'"'"'s body;

a sensor data gathering engine configured to;

gather raw motion data generated by the sensors when the user performs exercises or poses;

determine a first exercise or pose of the exercises or poses from the raw motion data using the posture dictionary and the predicted location of the sensors on the user'"'"'s body;

generate motion data for the first exercise or pose using the raw motion data and the predicted location of the sensors on the user'"'"'s body;

a user grading engine configured to grade the user in performing the first exercise or pose by comparing the motion data with the motion track;

wherein the content presentation control engine is configured to present to the user second content derived from the grading of the user.

11. The system of claim 10, further comprising:

a user data generation engine configured to update user data of the user to include an identification of the identified garment, wherein the user data is utilized to present to the user an advertisement of a product.

12. The system of claim 10, the sensor data gathering engine further configured to:

determine a second exercise or pose of the exercises or poses from the raw motion data using the posture dictionary and the predicted location of the sensors on the user'"'"'s body;

generate motion data for the second exercise or pose-using the raw motion data and the predicted location of the sensors on the user'"'"'s body.

13. The system of claim 10, further comprising a posture dictionary management engine configured to:

gather expert raw motion data generated by a plurality of sensors affixed to an expert performing the exercises or poses;

receive a video of the expert performing the exercises or poses;

build the posture dictionary based on the expert raw motion data and the video of the expert performing the exercises or poses.

14. The system of claim 10, wherein the second content derived from the grading of the user is linear and the content presentation control engine presents different portions of linear content non-linearly based on the grading of the user.

15. The system of claim 10, further comprising a skills progression engine configured to segment the user to a skill level of a particular skill, based on the grading of the user, using a skills matrix for the particular skill.

16. The system of claim 10, further comprising:

a skills progression engine configured to segment the user to a skill level of a particular skill, based on the grading of the user, using a skills matrix for the particular skill;

a content recommendation engine configured to recommend new content to the user based on the skill level to which the user is segmented.

17. The system of claim 10, further comprising identifying the garment worn by the user using a signature received from the garment wirelessly.

18. The system of claim 10, wherein the motion track includes embedded content directors, wherein the embedded content directors are used to present to the user the second content derived from the grading of the user.

19. The system of claim 10, wherein the motion track includes embedded content directors, wherein the embedded content directors are used to present to the user second content derived from the grading of the user.

21. A non-transitory computer readable medium comprising instructions that, when executed, cause one or more processors to perform:

using a posture dictionary to generate a motion track;

presenting to a user content annotated with the motion track;

obtaining garment data associated with an identified garment worn by the user;

pairing the identified garment to sensors using the garment data, wherein pairing the identified garment to the sensors provides a predicted location of the sensors on the user'"'"'s body;

gathering raw motion data generated by the sensors when the user performs exercises or poses;

determining a first exercise or pose of the exercises or poses from the raw motion data using the posture dictionary and the predicted location of the sensors on the user'"'"'s body;

generating motion data for the first exercise or pose using the raw motion data and the predicted location of the sensors on the user'"'"'s body;

grading the user in performing the first exercise or pose by comparing the motion data with the motion track; and

presenting to the user second content derived from the grading of the user.