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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 12213767 B1

PDFFull Text
Date of Patent:
Feb. 04, 2025

Filed:

Mar. 17, 2022

Video-based method and system for accurately estimating human body heart rate and facial blood volume distribution

Applicant:

Zhejiang University, Zhejiang, CN;

Inventors:

Hujun Bao, Hangzhou, CN;

Xiaogang Xu, Hangzhou, CN;

Xiaolong Wang, Hangzhou, CN;

Assignee:

ZHEJIANG UNIVERSITY, Hangzhou, CN;

Attorney:

W&G Law Group

Primary Examiner:

Leon Flores

Int. Cl.
CPC ...
A61B 5/024 (2006.01); A61B 5/00 (2006.01); A61B 5/0295 (2006.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G06V 10/25 (2022.01); G06V 10/62 (2022.01); G06V 10/774 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 40/16 (2022.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
A61B 5/02416 (2013.01); A61B 5/0295 (2013.01); A61B 5/7232 (2013.01); A61B 5/725 (2013.01); A61B 5/7264 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G06V 10/25 (2022.01); G06V 10/62 (2022.01); G06V 10/774 (2022.01); G06V 10/806 (2022.01); G06V 10/82 (2022.01); G06V 40/161 (2022.01); G06V 40/171 (2022.01); G16H 50/20 (2018.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30201 (2013.01); G06V 2201/03 (2022.01);
Abstract

Provided is a video-based method and system for accurately estimating heart rate and facial blood volume distribution, and the method mainly comprises the following steps: firstly, carrying out face detection of video frame containing human face, and extracting face image sequence and face key position points sequence in time dimension; secondly, compressing these sequence of face image and face key position points to obtain the facial signals in time dimension; thirdly, estimating facial blood volume distribution by facial signals mentioned in third step; finally, estimating heart rate values by using model based on deep learning technology and the spectrum analysis method respectively, then fusing the estimation results by Kalman filter to promote the accuracy of heart rate estimation.

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