traffic accidents bring serious harm to individuals and society. Fatigue driving has many potential safety hazards, which is the main factor causing road traffic accidents. Therefore, it is urgent to monitor the fatigue system. Firstly, the EEG signals are preprocessed by Butterworth band-pass filter, and then the features are extracted by wavelet transform. The classification results of fatigue EEG signals based on support vector machine are used as the initial fatigue value. Then RANSAC method is used to select fatigue signal. Finally, according to the average value of signals screened by RANSAC method as the standard value, the driver's fatigue state is determined by calculating the Euclidean distance between the standard value and the fatigue EEG signal. The experimental results show that the accuracy of the proposed method is better than that of the traditional method, which can reach 90%. It is easy to use and has wide application value.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Classification of driving fatigue based on EEG signals


    Beteiligte:
    Qin, Xuebin (Autor:in) / Yang, Peijiao (Autor:in) / Shen, Yutong (Autor:in) / Li, Mingqiao (Autor:in) / Hu, Jiachen (Autor:in) / Yun, Janhong (Autor:in)


    Erscheinungsdatum :

    2020-11-01


    Format / Umfang :

    971853 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Driving Fatigue Identification Method Based on Physiological Signals

    Mao, Zhe / Yan, Xin-ping / Wu, Chao-zhong | ASCE | 2008


    Heterogeneous Signal Fusion Method in Driving Fatigue Detection Signals

    Qingjun Wang / Zhendong Mu | DOAJ | 2021

    Freier Zugriff

    A Study of the Identification Method of Driving Fatigue Based on Physiological Signals

    Xu, Shili / Zhao, Xiao-hua / Zhang, Xing-jian et al. | ASCE | 2011


    Driving State Recognizing Based on Driving Behavior Signals

    Hu, D. / Yang, P. / Mu, Z. et al. | British Library Conference Proceedings | 2010


    Driving State Recognizing Based on Driving Behavior Signals

    Hu, Dunli / Yang, Pan / Mu, Zhichun et al. | ASCE | 2010