Heart Rate Detection Using Motion Compensation with Multiple ROIs

Jie Huang, Xuanheng Rao, Weichuan Zhang, Jingze Song, Xiao Sun

Abstract: Remote photoplethysmography (rPPG) has the ability to make use of image frame sequences including human faces collected by cameras for measuring heart rate (HR) without any contact. This method generates a time series signal based on the RGB spatial average of the selected region of interest (ROI) to estimate physiological signals such as HR. It is worth to note that the motion artifact produced by the subject’s face shaking is equivalent to adding considerable noise to the signal which will greatly affect the accuracy of the measurement. In this paper, a novel anti-interference multi-ROI analysis (AMA) approach is proposed which effectively utilizes the local information with multiple ROIs, the Euler angle information of the subject’s head, and the interpolation resampling technique of the video for suppressing the influence of face shaking on the accuracy of non-contact heart rate measurement. The proposed method is evaluated on the UBFC-RPPG and PURE datasets, and the experimental results demonstrate that the proposed methods are superior to many state-of-the-art methods.