• DocumentCode
    128393
  • Title

    Motor imagery controlled wheelchair system

  • Author

    Lijun Jiang ; Tham, Eugene ; Yeo, Mervyn ; Zaixing Wang ; Bo Jiang

  • Author_Institution
    Sch. of Eng., Republic Polytech., Singapore, Singapore
  • fYear
    2014
  • fDate
    9-11 June 2014
  • Firstpage
    532
  • Lastpage
    535
  • Abstract
    The motor imagery (MI) component of electroencephalogram (EEG) recordings has a substantial role in scientific applications. It is one of the commonest methodologies adopted by brain-computer interface (BCI) researchers. However, many MI based device is expensive and bulky due to the dependence on complex EEG sensing system. To overcome the drawbacks, a low-cost prototype is developed, leveraging on motor imagery component of EEG signal and Electromyography (EMG) signal. Based on signals from 14 channels, the system with friendly GUI, efficient algorithm, and easy-to-use dry sensors can detect and determine at least 4 movement directions of intention of a user: left, right, forward, backward. The proposed system is cost-effective and easy to use. The system has been successfully incorporated into a wheelchair control platform. The application of the system can extend to not only people who are suffering from spinal cord injuries, but also elderly or people suffering from limb muscle disorder.
  • Keywords
    brain-computer interfaces; control engineering computing; electrocardiography; electromyography; graphical user interfaces; handicapped aids; medical signal processing; BCI; EEG recordings; EEG signal; EMG signal; GUI; MI based device; brain-computer interface; elderly; electroencephalogram; electromyography; graphical user interface; limb muscle disorder; motor imagery controlled wheelchair system; spinal cord injury; user intention; wheelchair control platform; Electroencephalography; Electromyography; Filtering; Ports (Computers); Sensors; Spinal cord injury; Wheelchairs; Brain computer interface(BCI); Electromyography (EMG); Wheelchair; electroencephalogram (EEG); motor imagery (MI);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-4316-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2014.6931221
  • Filename
    6931221