Heart rate estimation from photoplethysmogram during intensive physical exercise using non-parametric Bayesian factor analysis

Estimating heart rate from a photoplethysmogram (PPG) signal in the presence of severe motion artifacts is a challenging problem. Previous approaches have primarily relied on accelerometer data to remove motion artifacts. In this paper, we propose a non-parametric Bayesian factor analysis based approach to estimate heart rate from a PPG signal, in the presence of severe motion artifacts. The novelty of our approach lies in the fact that it relies only on a single channel PPG signal to estimate heart rate, and does not require accelerometer data. The accuracy and robustness of the proposed approach has been demonstrated on a range of datasets corresponding to different intensive physical exercise scenarios.