Non-invasive Brain-Computer Interfaces: Enhanced Gaming and Robotic Control

  • Reinhold Scherer
  • Elisabeth C. V. Friedrich
  • Brendan Allison
  • Markus Pröll
  • Mike Chung
  • Willy Cheung
  • Rajesh P. N. Rao
  • Christa Neuper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6691)

Abstract

The performance of non-invasive electroencephalogram-based (EEG) brain-computer interfacing (BCI) has improved significantly in recent years. However, remaining challenges include the non-stationarity and the low signal-to-noise ratio (SNR) of the EEG, which limit the bandwidth and hence the available applications. In this paper, we review ongoing research in our labs and introduce novel concepts and applications. First, we present an enhancement of the 3-class self-paced Graz-BCI that allows interaction with the massive multiplayer online role playing game World of Warcraft. Second, we report on the long-term stability and robustness of detection of oscillatory components modulated by distinct mental tasks. Third, we describe a scalable, adaptive learning framework, which allows users to teach the BCI new skills on-the-fly. Using this hierarchical BCI, we successfully train and control a humanoid robot in a virtual home environment.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Reinhold Scherer
    • 1
    • 2
  • Elisabeth C. V. Friedrich
    • 3
  • Brendan Allison
    • 1
  • Markus Pröll
    • 1
  • Mike Chung
    • 2
  • Willy Cheung
    • 2
  • Rajesh P. N. Rao
    • 2
  • Christa Neuper
    • 1
    • 2
  1. 1.Institute for Knowledge DiscoveryGraz University of TechnologyGrazAustria
  2. 2.Computer Science and EngineeringUniversity of WashingtonSeattleUSA
  3. 3.Department of PsychologyUniversity of GrazGrazAustria

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