| Citation: | CHEN Hui, ZHENG Xiujuan, NI Zongjun, et al. Vital signs detection via facial video analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(9): 1770-1777. doi: 10.13700/j.bh.1001-5965.2020.0065(in Chinese)
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To detect the physiological signals related to vital signs via facial video is easily affected by ambient lights and head motions. In order to reduce the disturbance and increase the accuracy of estimations of vital signs, this paper proposes a facial video analysis method that combines Ensemble Empirical Mode Decomposition (EEMD) algorithm and signals quality detection to accurately detect vital signs such as the heart rate and respiratory rate of human beings. The performance of the proposed method is validated by comparing it with the existing signal processing techniques in a public dataset. The experimental results show that the proposed method can obtain more accurate estimates of heart rate and respiratory rate than the existing methods. The correlation coefficients between the estimates and the golden standards are higher than 0.9 and 0.8, respectively. The vital signs detection method has the potential to benefit real-time living face recognition and intelligent surveillance video analysis.
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