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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.

Patent No.:

US 11998364 B1

PDFFull Text
Date of Patent:
Jun. 04, 2024

Filed:

Jun. 04, 2021

Image-based system and method for predicting physiological parameters

Applicant:

Sharecare Ai, Inc., Palo Alto, CA (US);

Inventors:

Walter De Brouwer, Los Altos Hills, CA (US);

Apurv Mishra, Styria Graz, AT;

Samia De Brouwer, Los Altos Hills, CA (US);

Assignee:

Sharecare AI, Inc., Palo Alto, CA (US);

Attorneys:

HAYNES BEFFEL & WOLFELD LLP

Ernest J. Beffel, Jr.

Korbin S Van Dyke

Primary Examiner:

Samir A Ahmed

Int. Cl.
CPC ...
G06V 40/16 (2022.01); A61B 5/00 (2006.01); A61B 5/103 (2006.01); A61B 5/107 (2006.01); G06F 18/2413 (2023.01); G06N 3/045 (2023.01); G06N 3/082 (2023.01); G06N 5/046 (2023.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); A61B 5/024 (2006.01); A61B 5/16 (2006.01); G06N 7/01 (2023.01); G06N 20/10 (2019.01);
U.S. Cl.
CPC ...
A61B 5/7275 (2013.01); A61B 5/0077 (2013.01); A61B 5/1032 (2013.01); A61B 5/1072 (2013.01); A61B 5/441 (2013.01); A61B 5/4872 (2013.01); A61B 5/7267 (2013.01); G06F 18/24133 (2023.01); G06N 3/045 (2023.01); G06N 3/082 (2013.01); G06N 5/046 (2013.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/169 (2022.01); G06V 40/172 (2022.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); A61B 5/024 (2013.01); A61B 5/02405 (2013.01); A61B 5/163 (2017.08); A61B 5/442 (2013.01); G06N 7/01 (2023.01); G06N 20/10 (2019.01); G06V 40/178 (2022.01);
Abstract

System and method for determining physiological parameters of a person are disclosed. A physiological parameter may be obtained by analyzing a facial image of a person, and determining, from the facial image, a physiological parameter of the person by processing the facial image with a data processor. A neural network model such as regression deep learning convolutional neural network is used to predict the physiological parameter. An image processor screens out images which can't be recognized as facial images and adjust facial images to frontal facial images for predicting of physiological parameters.

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