Lighting effects on optimal facial regions for remote heart rate measurement

Remote photoplethysmography (rPPG) can evaluate real-time changes in blood flow volume by capturing facial videos and analyzing the color changes. Although the rPPG technique enables contactless heart rate (HR) monitoring, it remains highly susceptible to ambient lighting variations. Previous studies have demonstrated the critical influence of facial skin detection on the extracted rPPG signals. In this research, we defined 15 facial regions of interest (ROIs) based on anatomical criteria and evaluated their HR measurement performance on two public datasets (BUAA-MIHR and MMPD) using four representative rPPG algorithms (CHROM, LGI, OMIT, and POS). The experimental results confirmed that the glabella, nasal dorsum, and malar regions consistently serve as robust physiological signal sources under complex illumination environments. Furthermore, we revealed the significant advantage of multi-ROI combinations compared to both single-ROI and holistic-face strategies. Our work provides data-supported insights for establishing novel HR measurement pipelines with enhanced accuracy and robustness.