Variational Mode Decomposition-Based Heart Rate Estimation Using Wrist-Type Photoplethysmography During Physical Exercise

Heart rate (HR) monitoring based on Photoplethys-mography (PPG) has drawn increasing attention in modern wearable devices due to its simple hardware implementation and low cost. In this work, we propose a variational mode decomposition(VMD)-based HR estimation method using wrist-type PPG signals during physical exercise. To remove motion artifacts (MA), VMD was first used and then a post-processing method after VMD was proposed to guarantee the robustness of MA removal. The performance of our proposed method was evaluated on two PPG datasets used in 2015 IEEE Signal Processing Cup. The method achieved the average absolute error of 1.45 beat per minute (BPM) on the 12 training sets and 3.19 BPM on the 10 testing sets, confirmed by the experimental results.