Extraction of Heart Rate from Photoplethysmography Signals on Multiple Sites for Wearable Heart Monitoring Systems

This study contributes to improving heart rate (HR) monitoring by comparing the Peripheral Beat Amplitude (PBA) and Smoothed Z-score Peak Detection (Z-Score) algorithms for HR extraction across different body sites. The Z-Score algorithm, leveraging on edge computing, demonstrated higher accuracy than PBA, with a Mean Absolute Error (MAE) around 4 BPM. The study also explores the suitability of the Perfusion Ratio technique for Blood Oxygen (SpO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>) levels and the Welch method for respiratory rate (RR). Testing was conducted simultaneously at four distinct body sites (finger, wrist, arm, and ankle) during sitting and walking activities on six healthy individuals. Results indicate that the wrist is the optimal measurement site for various physiological parameters. Post-processing techniques were deliberately chosen to enhance the system's overall performance. The focus on HR necessitated evaluating two algorithms, given its critical importance. For SpO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and RR, single algorithms were selected to streamline processing while ensuring reliable measurements. The developed system exhibits acceptable power consumption of 51.98 m W and achieves an average coverage of 80% in controlled tests, indicating a significant portion of monitoring time provides accurate physiological data. This study emphasizes the deliberate selection of algorithms and measurement sites, demonstrating the superiority of the Z-Score algorithm and the practicality of integrating HR, SpO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, RR, and PPG monitoring in a single system.