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. 25, 2023

Filed:

Oct. 19, 2018
Applicant:

Meta Platforms Technologies, Llc, Menlo Park, CA (US);

Inventors:

Patrick Kaifosh, New York, NY (US);

Tudor Giurgica-Tiron, New York, NY (US);

Timothy Machado, Palo Alto, CA (US);

Thomas Reardon, New York, NY (US);

Erik Schomburg, Brooklyn, NY (US);

Assignee:

Meta Platforms Technologies, LLC, Menlo Park, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/389 (2021.01); G05B 13/04 (2006.01); G06K 9/00 (2022.01); G06F 3/01 (2006.01); G05B 13/02 (2006.01); A61B 7/00 (2006.01); A61B 5/11 (2006.01); A61B 5/00 (2006.01); G06K 9/62 (2022.01);
U.S. Cl.
CPC ...
G05B 13/048 (2013.01); A61B 5/1107 (2013.01); A61B 5/389 (2021.01); A61B 5/681 (2013.01); A61B 5/7267 (2013.01); A61B 7/006 (2013.01); G05B 13/0265 (2013.01); G06F 3/015 (2013.01); G06K 9/0057 (2013.01); G06K 9/00536 (2013.01); G06K 9/00557 (2013.01); G06K 9/624 (2013.01); G06K 9/6263 (2013.01);
Abstract

A system comprising a plurality of neuromuscular sensors, each of which is configured to record a time-series of neuromuscular signals from a surface of a user's body; and at least one computer hardware processor programmed to perform: applying a source separation technique to the time series of neuromuscular signals recorded by the plurality of neuromuscular sensors to obtain a plurality of neuromuscular source signals and corresponding mixing information; providing features, obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, as input to a trained statistical classifier and obtaining corresponding output; and identifying, based on the output of the trained statistical classifier, and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.


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