Using Coherence for Robust Online Brain-Computer Interface (BCI) Control

  • Martin Spüler
  • Wolfgang Rosenstiel
  • Martin Bogdan
Part of the Communications in Computer and Information Science book series (CCIS, volume 438)

Abstract

A Brain-Computer Interface (BCI) enables the user to control a computer by brain activity only. In this paper we investigated the use of different brain connectivity methods to control a Magnetoencephalography (MEG)-based Brain-Computer Interface (BCI). We compared the use of coherence, phase synchronisation and a widely used method for spectral power estimation and found coherence to be a more robust feature extraction method, when using the BCI over a longer time interval across sessions. To validate these results we implemented an online BCI system using coherence and could show that coherence also performed more robust in an online setting than traditional methods.

Keywords

Brain connectivity Brain-Computer Interface (BCI) Coherence Magnetoencephalogrpahy (MEG) non-stationarity 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Martin Spüler
    • 1
  • Wolfgang Rosenstiel
    • 1
  • Martin Bogdan
    • 1
    • 2
  1. 1.Wilhelm-Schickard-Institute for Computer ScienceUniversity of TübingenGermany
  2. 2.Computer EngineeringUniversity of LeipzigGermany

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