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Analysis on the Correlation Degree between the Driver’s Reaction Ability and Physiological Parameters

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  • Shiwu Li
  • Mengzhu Guo
  • Linhong Wang
  • Meng Chai
  • Facheng Chen
  • Yunong Wei

Abstract

In this paper, the correlation degree between driver’s reaction time and the physiological signal is analyzed. For this purpose, a large number of road experiments are performed using the biopac and the reaction time test systems to collect data. First, the electroencephalograph (EEG) signal is processed by using the fast Fourier and the inverse Fourier transforms. Then, the power spectrum densities (PSD) of α , β , δ , and EEG wave are calculated by Welch procedure. The average power of the power spectrum of α , β , and θ is calculated by the biopac software and two ratio formulas, and α / β , are selected to be the impact factors. After that the heart rate and the standard deviation of RR interval are calculated from the electrocardiograph (ECG) signal. Lastly, the correlation degree between the eight impact factors and the reaction time are analyzed based on the grey correlation analysis. The results demonstrate that α / β has the greatest correlation to the reaction time except EEG-PSD. Furthermore, two mathematical models for the reaction time-driving time and the α / β -driving time are developed based on the Gaussian function. These mathematical models are then finally used to establish the functional relation of α / β -the reaction time.

Suggested Citation

  • Shiwu Li & Mengzhu Guo & Linhong Wang & Meng Chai & Facheng Chen & Yunong Wei, 2017. "Analysis on the Correlation Degree between the Driver’s Reaction Ability and Physiological Parameters," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-8, February.
  • Handle: RePEc:hin:jnlmpe:5215874
    DOI: 10.1155/2017/5215874
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    Cited by:

    1. Shiyue Fang & Xujing Zhang & Xinzhan Li & Yue Chen & Baiyi He & Yuan Bao & Dongmin Ma, 2023. "Numerical-Well-Testing Interpretation of Injection/Falloff Testing for Coalbed Methane Well in Hedong Coalfield," Energies, MDPI, vol. 16(13), pages 1-16, June.
    2. Yongzheng Yang & Zhigang Du & Fangtong Jiao & Fuquan Pan, 2021. "Analysis of EEG Characteristics of Drivers and Driving Safety in Undersea Tunnel," IJERPH, MDPI, vol. 18(18), pages 1-18, September.

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