Non-contact heart rate detection via periodic signal detection methods

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.