Non-contact heart rate detection via periodic signal detection methods

Gizem Tabak, Andrew C. Singer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Real time non-contact heart rate detection is performed by using different methods for periodic signal detection in noise. Heart rate is estimated from a scalar signal formed from the average color values of the observed skin from videos recorded previously at first, and then captured in real time with a built-in laptop webcam. Cramer-Rao lower bounds are calculated as a function of SNR for an assumed parametric model, and heart rate is detected via autocorrelation, maximum likelihood and Fourier-based methods. The performance is evaluated by comparing the error rates for different detection techniques in each case.

Original languageEnglish (US)
Title of host publicationConference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages790-794
Number of pages5
ISBN (Electronic)9781467385763
DOIs
StatePublished - Feb 26 2016
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 8 2015Nov 11 2015

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2016-February
ISSN (Print)1058-6393

Other

Other49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/8/1511/11/15

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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