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About Brain State Decoding in Brain-Computer Interfaces

bci_scheme.pngDiagram of a typical BCI system

In general, brain-computer interface (BCI) systems make use of state-of-the-art machine learning methods, to decode ongoing brain signals in real-time. Via BCIs, users shall be enabled to type text, control a computer or wheelchair - even if they are severely motor impaired. To perform such a task, a BCI is realized using several components (as shown in Figure 1):

  • Brain activity measurement: EEG, ECoG, MRI, PET, NIRS, etc
  • Signal preprocessing: band-pass filtering, outlier removal, artifact correction, normalization, etc
  • Feature extraction: gain relevant information from acquired data, e.g. the band power of a neural oscillatory source of interest
  • Classification: determinewhich brain state the recorded signals correspond to (decode the intented action of the subject)
  • Application/feedback: present the effect of a control step to the user, e.g. by typing a letter to the screen


Here some examples what can be done with a BCI system:

External resources

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