{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T05:26:57Z","timestamp":1740461217427,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"abstract":"<jats:p>Heart rate measurement is an important means of monitoring the physiological status of the human body. A non-contact heart rate measurement method is proposed by analyzing the change of pixels. Multi-filter and sub-region method are adopted to solve the problem of the complex heart rate signal extraction result. As the independence of the RGB color model, the green component signals can be taken from the mixed signals by using Fast ICA. The main peak noise is removed by the wavelet filtering and the band-pass filter, and the heart rate is obtained in the analysis of the energy spectrum by using the Fourier transform. The facial organs influence on the extraction of the heart rate signal is effectively reduced by dividing the face region, and the part of the face to best reflect the heart rate is further determined. The experimental results show that this method can be convenient and accurate to achieve the heart rate measurement, and the proposed division method of the most appropriate facial part to extract the heart rate enhances the application of the heart rate measurement.<\/jats:p>","DOI":"10.3233\/978-1-61499-927-0-818","type":"book-chapter","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T11:58:24Z","timestamp":1740398304000},"source":"Crossref","is-referenced-by-count":0,"title":["Non-Contact Heart Rate Measurement Based on Facial Video"],"prefix":"10.3233","author":[{"family":"Zhou Nan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Huang Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Huang Jifeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Pan Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ni Yepeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Shan Lianhai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining IV"],"original-title":[],"deposited":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T11:59:35Z","timestamp":1740398375000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-926-3&spage=818&doi=10.3233\/978-1-61499-927-0-818"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-927-0-818","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2018]]}}}