• DocumentCode
    3496000
  • Title

    EEG-based brain dynamics of driving distraction

  • Author

    Lin, Chin-Teng ; Chen, Shi-An ; Ko, Li-Wei ; Wan, Yu-Kai

  • Author_Institution
    Dept. of Electr. & Control Eng., Nat. Chiao-Tung Univ., Hsinchu, Taiwan
  • fYear
    2011
  • fDate
    July 31 2011-Aug. 5 2011
  • Firstpage
    1497
  • Lastpage
    1500
  • Abstract
    Distraction during driving has been recognized as a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) -based brain dynamics in response to driving distraction. To study human cognition under specific driving tasks in a simulated driving experiment, this study utilized two simulated events including unexpected car deviations and mathematics questions. The raw data were first separated into independent brain sources by Independent Component Analysis. Then, the EEG power spectra were used to evaluate the time-frequency brain dynamics. Results showed that increases of theta band and beta band power were observed in the frontal cortex. Further analysis demonstrated that reaction time and multiple cortical EEG power had high correlation. Thus, this study suggested that the features extracted by EEG signal processing, which were the theta power increases in frontal area, could be used as the distracted indexes for early detection of driver inattention in real driving.
  • Keywords
    electroencephalography; feature extraction; independent component analysis; medical signal processing; neurophysiology; EEG power spectra; EEG signal processing; EEG-based brain dynamics; beta band power; driving distraction; driving task; electroencephalography; feature extraction; human cognition; independent component analysis; simulated driving experiment; theta band power; time-frequency brain dynamics; Accidents; Educational institutions; Electroencephalography; Scalp; Time factors; Vehicle dynamics; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2011 International Joint Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4244-9635-8
  • Type

    conf

  • DOI
    10.1109/IJCNN.2011.6033401
  • Filename
    6033401