EEG-basierte Brain-Computer Interfaces zur Echtzeit-Dekodierung mentaler Zustände

Translated title of the contribution: EEG-based brain-computer interfaces for real-time decoding of mental states

G. Curio, B. Blankertz, K. R. Müller

Research output: Contribution to journalArticlepeer-review


Brain-computer interfaces (BCI) employ algorithmic procedures of machine learning in order to extract user-specific patterns of high-dimensional EEG features. These patterns are optimised to decode intention-related brain states in real-time. Characteristic BCI applications for paralysed patients are control of active prostheses or speller software. To recognise a users motor intention a BCI system utilises individual EEG activation indices, such as the readiness potential or the modulation of regional EEG rhythms. Also beyond the borders of rehabilitation, this neurotechnology enables a growing set of novel application scenarios, e.g., BCIs can serve as optimised feedback tools for the stabilisation of mental states such as vigilance or attention.

Translated title of the contributionEEG-based brain-computer interfaces for real-time decoding of mental states
Original languageGerman
Pages (from-to)213-219
Number of pages7
JournalKlinische Neurophysiologie
Issue number3
Publication statusPublished - 2012
Externally publishedYes


  • brain-computer interface (BCI)
  • machine learning
  • neuro-feedback
  • prosthesis control
  • readiness potential

ASJC Scopus subject areas

  • Clinical Neurology
  • Physiology (medical)


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