Heart rate, the speed of the heartbeat, has been regarded as one of the most important measurements to evaluate one’s health. It can be used to measure one’s anxiety, stress and illness; abnormalities of heart rate usually indicate potential disease one may have. Recent
studies have shown that it is possible to directly measure the heart rate from a sequence of images that contain a person’s face. Requiring only a webcam, this method largely simplifies the process of traditional methods, which require the use of a pulse oximeter attached to the fingertip
to measure the PPG signal, or electrodes placed on the skin to measure the ECG signal. However, this most recent method, though attracting a lot of interest, still suffers from sudden movement of the head, or turning away from the camera. In this paper, we propose a novel robust method of
generating reliable PPG signals and measuring the heart rate from only face videos in real time, which is invariant to the movement of the head. We have also conducted studies on how different factors, light conditions, the angle of the head and the distance of the head away from the camera,
could affect the predictions of the heart rate. After conducting a thorough analysis, we can conclude that our method succeeds in producing accurate, robust and promising results.