A computationally efficient heart rate measurement system using video cameras

Video cameras are increasingly being used to measure human heart rates non-invasively, without contact. Such systems find applications in tele-medicine, remote monitoring of quarantined patients and premature neonates and are also useful for health conscious consumers. Several algorithms have been reported in the literature for measuring the heart rate from videos of human subjects. These algorithms use offline, computationally involved techniques such as Independent Component Analysis (ICA) or Principal Component Analysis (PCA) which render the algorithms unfeasible for implementation on real-time embedded systems. We conducted experiments to find an optimal colorspace for measuring the heart rate. We subsequently used a novel means of optical filtering of this colorspace to develop an accurate real-time algorithm, without the need for ICA or PCA, using ordinary standard definition (SD) web cameras. In this paper we present our algorithm and also compare it with existing state of the art algorithms.