A Systematic Approach Focused on Machine Learning Models for Exploring the Landscape of Physiological Measurement and Estimation Using Photoplethysmography (PPG)

This study provided a comprehensive analysis of the extraction of various physiological parameters using PPG waveforms and focused on the role of machine learning (ML) models used for the estimation of blood pressure and hypertension classification based on PPGWaveforms to make future research and innovation recommendations.