To study the cumulative fatigue of drivers of different ages, we compare the differences in their sleep-deprived driving, and obtain the optimal driving time. EEG data were collected through the eego™mylab full mobile EEG recording and analysis system, and the fatigue status of the experimenter was investigated with the subjective inquiry method. The ASA software is used to preprocess the original data, and the integration method is used to obtain the α, β, θ and δ. According to average power Spectral density of wave, we need to calculate R(α/β), R(θ/β) and R(α+θ)/β, and to analyze the processed data through SPSS with R(α+θ)/β. As an indicator of fatigue driving, we need to find the drivers of different age groups separately. As for R(α+θ)/β, we need to fit it with the duration of driving and analyze the relationship between drivers of different age groups and the cumulative speed of fatigue driving. The results show that the fatigue accumulation speed of young and middle-aged drivers is slower in 2 hours, while the fatigue accumulation speed of elderly drivers is faster. The optimal driving time for young, middle and elderly drivers is 105-120, 105-120, and 75-90 minutes, respectively.


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    Title :

    Assessment of Fatigue Level of Drivers of Different Ages Based on EEG Signals


    Contributors:
    Peiyou, Xue (author) / Pengfei, Feng (author) / Mingyu, Lu (author) / Mengmeng, Duan (author)


    Publication date :

    2023-09-22


    Size :

    1344284 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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