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Using Rest Class and Control Paradigms for Brain Computer Interfacing

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Brain-Computer Interfaces

Part of the book series: Human-Computer Interaction Series ((HCIS))

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Abstract

The use of Electroencephalography (EEG) for Brain Computer Interface (BCI) provides a cost-efficient, safe, portable and easy to use BCI for both healthy users and the disabled. This chapter will first briefly review some of the current challenges in BCI research and then discuss two of them in more detail, namely modeling the “no command” (rest) state and the use of control paradigms in BCI. For effective prosthetic control of a BCI system or when employing BCI as an additional control-channel for gaming or other generic man machine interfacing, a user should not be required to be continuously in an active state, as is current practice. In our approach, the signals are first transduced by computing Gaussian probability distributions of signal features for each mental state, then a prior distribution of idle-state is inferred and subsequently adapted during use of the BCI. We furthermore investigate the effectiveness of introducing an intermediary state between state probabilities and interface command, driven by a dynamic control law, and outline the strategies used by two subjects to achieve idle state BCI control.

This chapter is a slightly revised version of: S. Fazli, M. Danóczy, F. Popescu, B. Blankertz, K.-R. Müller: Using Rest Class and Control Paradigms for Brain Computer Interfacing. IWANN (1) 2009: 651–665.

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Acknowledgements

The studies were partly supported by BFNT, BMBF FKZ 01IBE01A/B, by DFG MU 987/3-1 and by the EU under PASCAL2. This publication only reflects the authors’ views.

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Authors and Affiliations

  1. Berlin Institute of Technology, Franklinstr. 28/29, Berlin, Germany

    Siamac Fazli, Márton Danóczy, Benjamin Blankertz & Klaus-Robert Müller

  2. Fraunhofer FIRST, Kekuléstr. 7, Berlin, Germany

    Florin Popescu & Benjamin Blankertz

Authors
  1. Siamac Fazli
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  2. Márton Danóczy
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  3. Florin Popescu
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  4. Benjamin Blankertz
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  5. Klaus-Robert Müller
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Corresponding author

Correspondence to Siamac Fazli .

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Editors and Affiliations

  1. Researcher, Microsoft Research, One Microsoft Way,Redmond 11514 NE 1, Washington, 98052, Washington, USA

    Desney S. Tan

  2. Fac. Electrical Engineering,, Mathematics &Computer Science, University of Twente, Enschede, Netherlands

    Anton Nijholt

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Fazli, S., Danóczy, M., Popescu, F., Blankertz, B., Müller, KR. (2010). Using Rest Class and Control Paradigms for Brain Computer Interfacing. In: Tan, D., Nijholt, A. (eds) Brain-Computer Interfaces. Human-Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-84996-272-8_4

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  • DOI: https://doi.org/10.1007/978-1-84996-272-8_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-271-1

  • Online ISBN: 978-1-84996-272-8

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