Abstract
The evaluation methods of driving fatigue have been the hot topics in the study of traffic. This paper studied the main existing driving fatigue evaluation methods based on RR intervals and verified the effectiveness of these methods by experiments. There were 15 drivers selected in the simulation driving experiment, and the pulse signal of them was collected and recorded during the test period. Average heart rate, time and frequency domain features of HRV, nonlinear features of HRV, and statistic of MSPC were chosen as the indexes to verify. The experimental results show that “T2” of HRV time domain indexes, including MSPC, SDNN, RMSSD and total power, HRV frequency domain indexes like LF/HF, and the longer axis of Poincare scatter plot can distinguish the fatigue state and the waking state of drivers with a favorable effect.
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Acknowledgments
This research is partially supported by the National Natural Science Foundation of China (Grant No. 61503007, 61603005), Technology Project General Project of Beijing Municipal Education Commission. No. SQKM201810009007, and Beijing Youth Talent Support Program. The authors gratefully thank anonymous referees for their useful comments and editors for their work.
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Guo, W., Xu, C., Tan, J., Li, Y. (2019). Review and Implementation of Driving Fatigue Evaluation Methods Based on RR Interval. In: Wang, W., Bengler, K., Jiang, X. (eds) Green Intelligent Transportation Systems. GITSS 2017. Lecture Notes in Electrical Engineering, vol 503. Springer, Singapore. https://doi.org/10.1007/978-981-13-0302-9_81
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DOI: https://doi.org/10.1007/978-981-13-0302-9_81
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