Effective methods to extract PPG signals from face using stochastic state space modeling approach

The Photoplethymography(PPG) which means heart-rate pulsation is generally measured on a finger or an ear using contact sensors. The recent several studies using web-cam to measure PPG have been introduced under the desktop or mobile computing environment including service robot . However the motion artifact issue is also emerging in non-contact camera sensing similar to contact-type one because it is sensitive to artifacts generated by subject´s head and body motion. In this paper, The effective methods to extract PPG signals from face is introduced by stochastic state space modeling(SSM) approach and its system parameters are estimated by subspace system identification.