Illumination variation-resistant video-based heart rate measurement using recursive least squares and complete ensemble empirical mode decomposition with adaptive noise

Heart rate is closely related to physiological and psychological states, and video-based techniques such as Imaging Photoplethysmography (IPPG) have been developed for heart rate detection. Although there have been some methods based on IPPG that are used to address the impact of illumination changes on heart rate detection, these methods perform poorly in environments with intense or complex illumination. This study proposes a framework that uses normalized least mean square adaptive filtering and singular spectrum analysis to combat the effects of illumination changes on heart rate detection. Experimental results on a dataset comprising 13 men and women aged 20 to 28 demonstrate the feasibility of our method under illumination changes.