• DocumentCode
    173395
  • Title

    A driver-vehicle interface based on ERD/ERS potentials and alpha rhythm

  • Author

    Luzheng Bi ; Tenghuan He ; Xinan Fan

  • Author_Institution
    Sch. of Mech. Eng., Beijing Inst. of Technol., Beijing, China
  • fYear
    2014
  • fDate
    5-8 Oct. 2014
  • Firstpage
    1058
  • Lastpage
    1062
  • Abstract
    In this paper, we propose a novel driver-vehicle interface by using the event-related desynchronizations (ERD) and event-related synchronization (ERS) potentials induced by motor imagery in conjunction with alpha rhythm to interact with a vehicle. The alpha rhythm, which is recognized by using a linear discriminant analysis (LDA) classifier, is employed to control the starting and stopping of the vehicle. The ERD/ERS brain-computer interface (BCI) is applied to control the turning left and right of the vehicle. A simulated vehicle based on the proposed driver-vehicle interface is developed and tested online by applying a driving task, including vehicle starting and stopping, lane keeping and curve negotiation, and avoiding obstacle. The experimental results suggest that the proposed interface is feasible.
  • Keywords
    brain-computer interfaces; medical signal processing; signal classification; traffic engineering computing; BCI; ERD-ERS potentials; LDA classifier; alpha rhythm; brain-computer interface; curve negotiation task; driver-vehicle interface; driving task; event-related desynchronization; event-related synchronization; lane keeping task; linear discriminant analysis; motor imagery; obstacle avoidance task; vehicle starting task; vehicle stopping task; Brain models; Brain-computer interfaces; Electroencephalography; Rhythm; Turning; Vehicles; Brain-controlled vehicle; alpha rhythm; driver-vehicle interaction; motor imagery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • Type

    conf

  • DOI
    10.1109/SMC.2014.6974053
  • Filename
    6974053