Voluntary brain regulation and communication with electrocorticogram signals

Thilo Hinterberger, Guido Widman, Thomas Navin Lal, Jeremy Hill, Michael Tangermann, Wolfgang Rosenstiel, Bernhard Schölkopf, Christian Elger, Niels Birbaumer

Research output: Contribution to journalArticlepeer-review

Abstract

Brain-computer interfaces (BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of brain signals such as the electroencephalogram (EEG). Three of five patients with epilepsy were able to spell their names with electrocorticogram (ECoG) signals derived from motor-related areas within only one or two training sessions. Imagery of finger or tongue movements was classified with support-vector classification of autoregressive coefficients derived from the ECoG signals. After training of the classifier, binary classification responses were used to select letters from a computer-generated menu. Offline analysis showed increased theta activity in the unsuccessful patients, whereas the successful patients exhibited dominant sensorimotor rhythms that they could control. The high spatial resolution and increased signal-to-noise ratio in ECoG signals, combined with short training periods, may offer an alternative for communication in complete paralysis, locked-in syndrome, and motor restoration.

Original languageEnglish
Pages (from-to)300-306
Number of pages7
JournalEpilepsy and Behavior
Volume13
Issue number2
DOIs
Publication statusPublished - Aug 2008

Keywords

  • Brain regulation
  • Brain-computer interface
  • Electrocorticogram
  • Epilepsy
  • Sensorimotor rhythms

ASJC Scopus subject areas

  • Clinical Neurology
  • Behavioral Neuroscience
  • Neurology

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