Heart Rate Tracking using Wrist-Type Photoplethysmographic (PPG) Signals during Physical Exercise with Simultaneous Accelerometry

TL;DR

This paper introduces a novel algorithm for accurate wrist-based heart rate monitoring during intense exercise, effectively removing motion artifacts using acceleration data and spectral analysis, achieving high accuracy in challenging conditions.

Contribution

The paper presents a new two-step algorithm combining motion artifact cancellation and spectral analysis for improved heart rate estimation from wrist PPG signals during exercise.

Findings

Average absolute error of 1.25 BPM in heart rate estimation.

High accuracy maintained even under strong motion artifacts.

Effective use of acceleration data for artifact removal.

Abstract

This paper considers the problem of casual heart rate tracking during intensive physical exercise using simultaneous 2 channel photoplethysmographic (PPG) and 3 dimensional (3D) acceleration signals recorded from wrist. This is a challenging problem because the PPG signals recorded from wrist during exercise are contaminated by strong Motion Artifacts (MAs). In this work, a novel algorithm is proposed which consists of two main steps of MA Cancellation and Spectral Analysis. The MA cancellation step cleanses the MA-contaminated PPG signals utilizing the acceleration data and the spectral analysis step estimates a higher resolution spectrum of the signal and selects the spectral peaks corresponding to HR. Experimental results on datasets recorded from 12 subjects during fast running at the peak speed of 15 km/hour showed that the proposed algorithm achieves an average absolute error of 1.25 beat per minute (BPM). These experimental results also confirm that the proposed algorithm keeps high estimation accuracies even in strong MA conditions.