Non-Contact Method of Heart Rate Using a Webcam

被引：5

作者：

Zhao, Jin ^{[1
,2
]}

Huang, Jifeng ^{[1
]}

Jia, Guoqing ^{[3
]}

Ji, Xiaohong ^{[3
]}

Shan, Lianhai ^{[4
]}

机构：

[1] Shanghai Normal Univ, Coll Informat Mech & Elect Engn, Shanghai, Peoples R China

[2] Shanghai Res Ctr Wireless Commun, Shanghai 201210, Peoples R China

[3] Qinghai Univ Nationalities, Coll Phys & Elect Informat Engn, Xining, Qinghai, Peoples R China

[4] Shanghai Internet Things Co Ltd, Shanghai 201899, Peoples R China

来源：

IEEE 2018 INTERNATIONAL CONGRESS ON CYBERMATICS / 2018 IEEE CONFERENCES ON INTERNET OF THINGS, GREEN COMPUTING AND COMMUNICATIONS, CYBER, PHYSICAL AND SOCIAL COMPUTING, SMART DATA, BLOCKCHAIN, COMPUTER AND INFORMATION TECHNOLOGY | 2018年

基金：

中国国家自然科学基金;

关键词：

the blood volume pulse; tree component analysis; complete total empirical mode decomposition; heart rate; RISK;

D O I：

10.1109/Cybermatics_2018.2018.00315

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Aiming at the defects of traditional heart rate measurement, a blood volume pulse (BVP) signal and estimate heart rate estimate is proposed based on tree component analysis (TCA) and complete total empirical mode decomposition (CEEMD). The region of interest is selected from facial video, which is taken by non-contact camera, and then is separated by TCA to obtain noisy BVP. BVP signal is decomposed into different scale signal which is computed by spectrum analysis to get heart rate. The experiment indicates that the method is consistent with the pulse oximeter, and the 95 % confidence interval of this measurement system is[-1.5,1.5]. Benefiting from property of simplicity and non-contact, this method can be applied to live detection. Moreover, the method can avoid the selection of relevant parameters and reduce the workload of the operators.

引用

页码：1902 / 1906

页数：5

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