Video-based human heart rate measurement using joint blind source separation. (January 2017) - Qi, Huan; Guo, Zhenyu; Chen, Xun; Shen, Zhiqi; Jane Wang, Z.
Abstract : Highlights: A video-based non-contact heart rate measurement method is proposed. The method jointly analyzes temporal colour channel signals of facial sub-regions. A max-margin multi-label classifier is used to predict optimal dataset correlation. A large public database is used to verify the performance of the proposed method. Abstract: Remote (non-contact) measurements of human cardiopulmonary physiological parameters based on photoplethysmography (PPG) can lead to efficient and comfortable medical assessment, which is important in human healthcare. It was shown that human facial blood volume variation during cardiac cycle can be indirectly captured by common Red–Green–Blue (RGB) cameras. In this paper, we show that it is promising to incorporate data from different facial sub-regions to improve remote measurement performance. We propose a novel method for non-contact video-based human heart rate (HR) measurement by exploring correlations among facial sub-regions via joint blind source separation (J-BSS). To our knowledge, this is the first time that J-BSS approaches, instead of prevailing BSS techniques such as independent component analysis (ICA), is successfully applied in non-contact physiological parameter measurement. We test the proposed method on a large public database, which provides the subjects' left-thumb plethysmograph signals as ground truth. Experimental results show that the proposed J-BSS method outperforms previous ICA-based methodologies.