Extraction Of Vital Physiological Signals Based On Image Sequence

Vital physiological signals such as heart rate, breathing waveform are closely related to our state of health and can be used to diagnose some common diseases. Traditionally, these signals are obtained only by some professional medical equipment. Recently, many new non-contact methods based on image sequence have been proposed to extract vital physiological signals. Using those methods we can obtain our vital physiological signals such as heart rate and breathing waveform by the camera of mobile phones or personal computers and it is very convenient for us to monitor our state of health. We hope that we can find some methods used to extract the vital physiological signals.Our paper first introduces the principle of the Eulerian Motion Magnification algorithm, describes the implementation process of the algorithm, and discusses the four key questions about the Eulerian Motion Magnification. Then, our paper analyzes the features of the pulse and breathing in the image sequence and introduces how to amplify the color change of the skin associated with pulse and the motion of the upper body associated with breathing. Finally, our paper presents a series of methods which are based on Eulerian Motion Magnification used to extract physiological signals from image sequence and discusses the implementation process and extraction results of those methods. By those methods our paper implements the extraction of heart rate, breathing waveform, pulse waveform and skin capillary distribution. What’s more, our paper also implements the heart rate and breathing waveform extraction system run on personal computers and the pulse waveform detection system run on Android smart phone.The results of the extraction show that these methods presented in this paper are accurate and robust. At the same time those method can be run stably in personal computer and Android smart phone.