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:
Mar. 18, 2025

Filed:

May. 23, 2022
Applicant:

Aic Innovations Group, Inc., New York, NY (US);

Inventors:

Deshana Desai, Jersey City, NJ (US);

Xiaoguang Lu, West Windsor, NJ (US);

Lei Guan, Jersey City, NJ (US);

Shaolei Feng, West Wndsor, NJ (US);

Richard Christie, Pennington, NJ (US);

Assignee:

AIC Innovations Group, Inc., New York, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06F 40/279 (2020.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06T 7/246 (2017.01); G06V 10/82 (2022.01); G06V 40/16 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06F 40/279 (2020.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06T 7/246 (2017.01); G06V 10/82 (2022.01); G06V 40/171 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30201 (2013.01);
Abstract

A video is segmented into a plurality of sequences corresponding to different facial states performed by a patient in the video. For each sequence, displacement of a plurality of groups of landmarks of a face of the patient is tracked, to obtain, for each group of the plurality of groups, one or more displacement measures characterizing positions of the landmarks of the group. The one or more displacement measures corresponding to each group are provided into a corresponding neural network, to obtain a landmark feature. The neural networks corresponding to each group are different from one another. A sequence score for the sequence is determined based on a plurality of landmark features corresponding to the groups. A plurality of sequence scores are provided into a machine learning component, to obtain a patient score. A disease state of the patient is determined based on the patient score.


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