Review on Heart‑Rate Estimation from Photoplethysmography and Accelerometer Signals During Physical Exercise

Abstract

Non-invasive monitoring of physiological signals during physical
exercise is essential to customize the exercise module. Photoplethysmography
(PPG) signal has often been used to non-invasively monitor
heart-rate, respiratory rate, and blood-pressure among other physiological
signals. Typically, PPG signal is acquired using pulse oximeter from
finger-tip or wrist. Advantage of wrist-based PPG sensors is that it is
more convenient to wear. Other sensors such as accelerometer can also
be integrated with it due to large area on the wrist. This article provides
a review of the algorithms developed for heart rate estimation during
physical exercise from the PPG signals and accelerometer signals. The
datasets used to develop these techniques are described. Algorithms
for denoising of PPG signals using accelerometer signals are either in
time domain or frequency domain