Playing pinball with non-invasive BCI

Michael W. Tangermann, Matthias Krauledat, Konrad Grzeska, Max Sagebaum, Carmen Vidaurre, Benjamin Blankertz, Klaus Robert Müller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

77 Citations (Scopus)

Abstract

Compared to invasive Brain-Computer Interfaces (BCI), non-invasive BCI systems based on Electroencephalogram (EEG) signals have not been applied successfully for precisely timed control tasks. In the present study, however, we demonstrate and report on the interaction of subjects with a real device: a pinball machine. Results of this study clearly show that fast and well-timed control well beyond chance level is possible, even though the environment is extremely rich and requires precisely timed and complex predictive behavior. Using machine learning methods for mental state decoding, BCI-based pinball control is possible within the first session without the necessity to employ lengthy subject training. The current study shows clearly that very compelling control with excellent timing and dynamics is possible for a non-invasive BCI.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference
Pages1641-1648
Number of pages8
Publication statusPublished - 2009
Event22nd Annual Conference on Neural Information Processing Systems, NIPS 2008 - Vancouver, BC, Canada
Duration: 2008 Dec 82008 Dec 11

Publication series

NameAdvances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference

Other

Other22nd Annual Conference on Neural Information Processing Systems, NIPS 2008
CountryCanada
CityVancouver, BC
Period08/12/808/12/11

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Tangermann, M. W., Krauledat, M., Grzeska, K., Sagebaum, M., Vidaurre, C., Blankertz, B., & Müller, K. R. (2009). Playing pinball with non-invasive BCI. In Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference (pp. 1641-1648). (Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference).