AbstractsMedical & Health Science

Video-based cardiac physiological measurements using joint blind source separation approaches

by Huan Qi

Institution: University of British Columbia
Year: 2015
Posted: 02/05/2017
Record ID: 2106556
Full text PDF: http://hdl.handle.net/2429/54005


Non-contact measurements of human cardiopulmonary physiological parameters based on photoplethysmography (PPG) can lead to efficient and comfortable medical assessment. It was shown that human facial blood volume variation during cardiac cycle can be indirectly captured by regular Red-Green-Blue (RGB) cameras. However, few attempts have been made to incorporate data from different facial sub-regions to improve remote measurement performance. In this thesis, we propose a novel framework for non-contact video-based human heart rate (HR) measurement by exploring correlations among facial sub-regions via joint blind source separation (J-BSS). In an experiment involving video data collected from 16 subjects, we compare the non-contact HR measurement results obtained from a commercial digital camera to results from a Health Canada and Food and Drug Administration (FDA) licensed contact blood volume pulse (BVP) sensor. We further test our framework on a large public database, which provides subjects' left-thumb plethysmograph signal as ground truth. Experimental results show that the proposed framework outperforms the state-of-the-art independent component analysis (ICA)-based methodologies. Driver physiological monitoring in vehicle is of great importance to provide a comfortable driving environment and prevent road accidents. Contact sensors can be placed on the driver's body to measure various physiological parameters. However such sensors may cause discomfort or distraction. The development of non-contact techniques can provide a promising solution. In this thesis, we employ our proposed non-contact video-based HR measurement framework to monitor the drivers heart rate and do heart rate variability analysis using a simple consumer-level webcam. Experiments of real-world road driving demonstrate that the proposed non-contact framework is promising even with the presence of unstable illumination variation and head movement.