A robust heart rate measurement framework based on videos

• Main Authors: Dong, Bowei, Liu, Yuliang, Wang, Xinwei
• Format: Conference Proceeding
• Language: English
• Published: SPIE 30.04.2024
• ISBN: 1510679723; 9781510679726
• ISSN: 0277-786X
• DOI: 10.1117/12.3018792

Human physiological parameters such as heart rate (HR) and heart rate variability (HRV) hold significant importance in health analysis and disease diagnosis. Traditional measurement methods heavily depend on contact sensors, which are inconvenient and uncomfortable for subjects. In contrast, video-based remote photoplethysmography (rPPG) has emerged as a promising technology for non-contact physiological measurement. However, its utility is compromised by susceptibility to motion artifacts and lighting. In response to the challenges posed by motion artifacts and lighting, we propose a robust rPPG framework. This paper assesses the noise robustness of diverse methods employed in rPPG-based physiological measurement, including face detection and tracking, region of interest (ROI) selection, rPPG signal extraction and heart rate calculation. The experimental results demonstrate the efficacy of the proposed framework in enhancing pre-processing outcomes and facilitating accurate heart rate measurements, even during dynamic motion tasks.