A variational mode decomposition-based approach for Heart rate monitoring using wrist-type Photoplethysmographic Signals during intensive Physical Exercise ☆

Heart rate monitoring using photoplethysmographic (PPG) signals recorded from wrist during intensive physical exercise is challenging because the PPG signals are contaminated by strong motion artifact. In this paper, we present a new approach for PPG based heart rate monitoring. We first perform the variational mode decomposition to decompose the PPG signal into multiple modes then eliminate the modes whose frequencies coincides with those from accelerator signals. Finally, the spectral analysis step is applied to estimate the spectrum of the signal and selects the spectral peaks corresponding to heart rate. Experimental results on a public available dataset recorded from 12 subjects during fast running validate the performance of the proposed algorithm.