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Heart rate estimation from color video sequences with high SNR

Yimei Zheng, Zecheng Lin, Wenzheng Ding, Min Yi, Caizhong Guan, Dingan Han, Junping Zhong, Haishu Tan, Xuehua Wang, Honglian Xiong, Mingyi Wang, and Yaguang Zeng

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Abstract

We propose an absorption intensity heartbeat modulation-averaged shifted histogram (AIHM-ASH) method for estimating human heart rate (HR) using color videos of lip image sequences. When heartbeat occurs, AIHM is generated. Based on the AIHM, HR signals can be demodulated by computing the instantaneous HR modulation depth that presents the relative red blood cell (RBC) concentration from the green channel image of the RGB color video. In addition, the ASH algorithm further suppresses the background tissue and vein signals, and increases the signal-to-noise ratio (SNR). The experimental results for flow phantoms, chicken embryos, and human lips validated the proposed method’s optimal estimation conditions and effectiveness, where the accuracy and root mean square error (RMSE) were 99.23% and 0.8 bpm, respectively. The proposed HR estimation method has significant potential to advance health monitoring and disease prevention via conventional color video cameras installed in public places.

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Supplementary Material (4)

NameDescription
Supplement 1       Supplemental document including 3 Supplements.
Visualization 1       Raw video of flow phantom capillaries.
Visualization 2       Raw video of the chicken embryo.
Visualization 3       IMD_HR video of the chicken embryo.

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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