The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 09, 2024

Filed:

Oct. 20, 2020
Applicant:

Plethy, Inc., San Jose, CA (US);

Inventors:

Ravi Jagannathan, Cupertino, CA (US);

Raja Sundaram, Los Gatos, CA (US);

Sahadevan Harikrishnan, Fremont, CA (US);

Assignee:

PLETHY, INC., San Jose, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/11 (2006.01); A61B 5/00 (2006.01); A63B 24/00 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G16H 30/20 (2018.01); G16H 40/67 (2018.01);
U.S. Cl.
CPC ...
A61B 5/1128 (2013.01); A61B 5/1121 (2013.01); A61B 5/486 (2013.01); A61B 5/721 (2013.01); A61B 5/7267 (2013.01); A63B 24/0062 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G16H 30/20 (2018.01); G16H 40/67 (2018.01); A61B 5/0077 (2013.01); A61B 2562/0219 (2013.01); A61B 2576/00 (2013.01);
Abstract

A method for assessing movement of a body portion includes, via one or more machine learning models, analyzing a sensor signal indicative of movement of the body portion to determine a movement of the body portion; determining a sensor confidence level based, at least in part, on a characteristic of the sensor signal; receiving a series of images indicative of movement of the body portion; measuring an angle of movement of the body portion; determining a vision confidence level based, at least in part, on a quality of an identification the body portion; selecting the sensor signal, the measured angle of movement, or a combination thereof as an input into a machine learning model based on the sensor confidence level and the vision confidence level, respectively; analyzing the input to determine a movement pattern of the body portion; and outputting the movement pattern to a user.


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