PPG-based heart rate estimation using Wiener filter, phase vocoder and Viterbi decoding

Abstract

Accurate heart rate (HR) estimation from the photoplethysmographic (PPG) signal during intensive physical exercises is tackled in this paper. Wiener filters are designed to attenuate the influence of motion artifacts. The phase vocoder is used to improve the initial Discrete Fourier transform (DFT) based frequency estimation. Additionally, Viterbi decoding is used as a novel post-processing step to find the path through time-frequency state-space plane. The system performance is assessed on a publically available dataset of 23 PPG recordings. The resulting algorithm is designed for scenarios that do not require online HR monitoring (swimming, offline fitness statistics). The resultant system with an error rate of 1.31 beats per minute outperforms all other systems reported to-date in literature and in contrast to existing alternatives requires no parameter to tune at the post-processing stage and operates at a much lower computational cost. The Matlab implementation is provided online.