Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms

Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus Robert Müller

Research output: Contribution to journalArticle

434 Citations (Scopus)

Abstract

Noninvasive electroencephalogram (EEG) recordings provide for easy and safe access to human neocortical processes which can be exploited for a brain-computer interface (BCI). At present, however, the use of BCIs is severely limited by low bit-transfer rates. We systematically analyze and develop two recent concepts, both capable of enhancing the information gain from multichannel scalp EEG recordings: 1) the combination of classifiers, each specifically tailored for different physiological phenomena, e.g., slow cortical potential shifts, such as the premovement Bereitschaftspotential or differences in spatio-spectral distributions of brain activity (i.e., focal event-related desynchronizations) and 2) behavioral paradigms inducing the subjects to generate one out of several brain states (multiclass approach) which all bare a distinctive spatio-temporal signature well discriminable in the standard scalp EEG. We derive information-theoretic predictions and demonstrate their relevance in experimental data. We will show that a suitably arranged interaction between these concepts can significantly boost BCI performances.

Original languageEnglish
Pages (from-to)993-1002
Number of pages10
JournalIEEE Transactions on Biomedical Engineering
Volume51
Issue number6
DOIs
Publication statusPublished - 2004 Jun

Keywords

  • Brain-computer interface (BCI)
  • Common spatial patterns
  • Electroencephalogram (EEG)
  • Event-related desynchronization
  • Feature combination
  • Movement related potential
  • Multiclass
  • Single-trial analysis

ASJC Scopus subject areas

  • Biomedical Engineering

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