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:
Sep. 23, 2025

Filed:

Jun. 14, 2022
Applicant:

Samsung Electronics Co., Ltd., Gyeonggi-Do, KR;

Inventors:

Ebrahim Nematihosseinabadi, San Jose, CA (US);

Shibo Zhang, Evanston, IL (US);

Tousif Ahmed, San Jose, CA (US);

Md Mahbubur Rahman, San Jose, CA (US);

Anh Minh Dinh, San Francisco, CA (US);

Nathan Robert Folkman, San Francisco, CA (US);

Sean Bornheimer, San Francisco, CA (US);

Jun Gao, Menlo Park, CA (US);

Jilong Kuang, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); A61B 5/08 (2006.01); G10L 21/0208 (2013.01); G10L 21/028 (2013.01); G10L 25/66 (2013.01); G10L 25/78 (2013.01); G10L 25/84 (2013.01); G16H 40/63 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
A61B 5/7282 (2013.01); A61B 5/0823 (2013.01); A61B 5/4803 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); G10L 21/0208 (2013.01); G10L 21/028 (2013.01); G10L 25/66 (2013.01); G10L 25/84 (2013.01); G16H 40/63 (2018.01); G16H 50/20 (2018.01); G10L 2025/783 (2013.01);
Abstract

Detecting and identifying a predetermined health event can include detecting a potential occurrence of the predetermined health event for a user by processing in real-time motion signals corresponding to motion of the user. A likelihood that the potential occurrence is an actual occurrence of the predetermined health event can be determined based on template matching of the motion signals. In response to determining that the likelihood exceeds a predetermined threshold, audio signals coinciding in time with the motion of the user can be processed using one or more layers of a multilayered audio event classifier.


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