• DocumentCode
    971020
  • Title

    ECoG factors underlying multimodal control of a brain-computer interface

  • Author

    Wilson, J. Adam ; Felton, Elizabeth A. ; Garell, P. Charles ; Schalk, Gerwin ; Williams, Justin C.

  • Author_Institution
    Dept. of Biomed. Eng., Wisconsin Univ., Madison, WI, USA
  • Volume
    14
  • Issue
    2
  • fYear
    2006
  • fDate
    6/1/2006 12:00:00 AM
  • Firstpage
    246
  • Lastpage
    250
  • Abstract
    Most current brain-computer interface (BCI) systems for humans use electroencephalographic activity recorded from the scalp, and may be limited in many ways. Electrocorticography (ECoG) is believed to be a minimally-invasive alternative to electroencephalogram (EEG) for BCI systems, yielding superior signal characteristics that could allow rapid user training and faster communication rates. In addition, our preliminary results suggest that brain regions other than the sensorimotor cortex, such as auditory cortex, may be trained to control a BCI system using similar methods as those used to train motor regions of the brain. This could prove to be vital for users who have neurological disease, head trauma, or other conditions precluding the use of sensorimotor cortex for BCI control.
  • Keywords
    bioelectric phenomena; brain; handicapped aids; medical computing; medical control systems; BCI control; ECoG; auditory cortex; brain-computer interface; electroencephalography; fast communication rates; head trauma; multimodal Control; neurological disease; rapid user training; sensorimotor cortex; Communication system control; Diseases; Electrodes; Electroencephalography; Epilepsy; Humans; Magnetic resonance imaging; Pain; Patient monitoring; Scalp; Brain–computer interface (BCI); electrocorticography (ECoG); sensorimotor cortex; Adult; Brain Mapping; Cerebral Cortex; Communication Aids for Disabled; Computer Peripherals; Evoked Potentials; Female; Humans; Imagination; Male; Man-Machine Systems; Neuromuscular Diseases; Systems Integration; User-Computer Interface; Volition;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2006.875570
  • Filename
    1642780