Hybrid approach to heart rate estimation: comparing Green, CHROM and POS methods in rPPG analysis

Remote Photoplethysmography (rPPG) offers a promising non-invasive solution for vital sign monitoring, including blood pressure (BP) estimation, by extracting cardiovascular information from facial videos. This study presents a hybrid approach to BP estimation by comparing three widely used methods in rPPG analysis: the green channel method, CHROM (Chrominance-based method), and POS (Plane-Orthogonal-to-Skin method). The Green method relies solely on the intensity of the green light reflected from the skin, while it works better than Red and Green, but it is highly depended to skin tone and ambient light. At the same time, CHROM and POS exploit multi-channel color signals to enhance signal extraction under varying lighting conditions. We compare these methods' performance in signal quality, noise resilience, and their effectiveness in estimating blood pressure. Our results demonstrate that the hybrid combination of CHROM and POS methods yields improved accuracy by obtaining the MAE of 8.7bpm, and robustness over traditional single-channel approaches. This provides a step forward in practical, non-invasive BP estimation for healthcare applications. This comparative analysis highlights the strengths and limitations of each method, offering insights into their applicability in real-world scenarios.