Psychological stress detection based on heart rate variability

Yu-zhong Liu; Hua-liang Li; Jianmin Wang; Haochuan Zhang; Xiaojun Zheng

doi:10.1117/12.2668856

20 April 2023 Psychological stress detection based on heart rate variability

Yu-zhong Liu, Hua-liang Li, Jianmin Wang, Haochuan Zhang, Xiaojun Zheng

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126021R (2023) https://doi.org/10.1117/12.2668856
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

Aiming at the problems of complex operation and low accuracy in psychological stress detection, we proposed a new method based on heart rate variability. We set the length gradient exploration for the length of the window and the window repeat part. Get the best window settings, and we extracted the time domain, frequency domain and nonlinear features of heart rate variability for model construction. We used the TOPT Automation Machine learning algorithm to obtain an optimal algorithm - extremely randomized tree algorithm, and the AUC on the test set was 0.934, which can be highly credible to detect psychological stress.

Citation Download Citation

Yu-zhong Liu, Hua-liang Li, Jianmin Wang, Haochuan Zhang, and Xiaojun Zheng "Psychological stress detection based on heart rate variability", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126021R (20 April 2023); https://doi.org/10.1117/12.2668856

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