MAO Ke-jun, LIU Xiao-ming, ZHAO Xiao-hua, RONG Jian. The Choice of Driver Fatigue Prediction Key Parameters Based on EEG Recordings[J]. Journal of Beijing University of Technology, 2010, 36(7): 966-970.
    Citation: MAO Ke-jun, LIU Xiao-ming, ZHAO Xiao-hua, RONG Jian. The Choice of Driver Fatigue Prediction Key Parameters Based on EEG Recordings[J]. Journal of Beijing University of Technology, 2010, 36(7): 966-970.

    The Choice of Driver Fatigue Prediction Key Parameters Based on EEG Recordings

    • In order to get an early driving fatigue warning early,the EEG data for a driver was recorded by an EEG apparatus in a driving simulation environment.The power spectrum estimation was used to establish the power distribution with frequency bands.Delta and alpha activities were referred to be possible to predict driver fatigue early.So the prediction system was created by the BP neural network,the prediction performance was tested separately in three situations such as the delta activity input,the alpha activity input and the combination of both input.The result shows the prediction impact is the best when the input vector is the combination of both and has the basis on the development of driving fatigue warning system.
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