Color Distortion Removal for Heart Rate Monitoring in Fitness Scenario

Abstract

Heart rate estimation from fitness plays an important role in the evaluation of fitness exercises. Conventional approaches use the photoplethysmography (PPG) sensor to consider the change of light absorption on the wrist skin for heart rate estimation. However, users are required to buy smartwatches for using this function. Various approaches based on video analysis are recently implemented for surveillance purpose. However, it is unstable for motion scenario such as fitness exercises due to the color distortion induced by movement. POS and CHROM are introduced to address this issue. Since the fixed projection planes from POS and CHROM are given in several sources of light, it is not widely applied for surveillance applications. Therefore, a novel projection plane that is adaptively changed with the lighting environment is proposed to estimate the heart rate from fitness videos in ambient light. Moreover, image and digital signal processing techniques are also applied to extract the clean pulse signal from a novel projection plane. From the experiments conducted, the proposed approach outperformed the existing approaches to be the best model for heart rate estimation from fitness videos with the accuracy up to 91.08%.