A weiner filter based robust algorithm for estimation of heart rate from wrist based photoplethysmogram

The paradigm of wellness consists of both physical and mental wellness. One important parameter of physical wellness in the monitoring of cardiac health during activity, which requires measurement of ambulatory heart rate (HR). With the advent of smart wearable devices, measurement of heart-rate using Photoplethysmogram (PPG) has become a commodity. However, arriving at a reliable heart-rate measurement in real-time during daily activities is an open research problem. In this paper, we propose a method based on Weiner Filter, to estimate the correct HR values in the presence of motion, while being computationally efficient to be run on-device. Results are presented on a public data-set which prove the efficacy and efficiency of the proposed method.