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Control of a Wheelchair by Motor Imagery in Real Time

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Intelligent Data Engineering and Automated Learning – IDEAL 2008 (IDEAL 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5326))

Abstract

This paper gives an outline of a non-invasive brain machine interface (BMI) implemented for controlling a motorized wheelchair online. Subjects were trained by using an effective feedback training method, and they could then control the wheelchair freely, similar to controlling it with a joystick.

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References

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Author information

Authors and Affiliations

  1. BSI-TOYOTA Collaboration Center, RIKEN, Japan

    Kyuwan Choi & Andrzej Cichocki

Authors
  1. Kyuwan Choi
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  2. Andrzej Cichocki
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Editor information

Editors and Affiliations

  1. University of West Scotland, PA1 2BE, Paisley, Scotland

    Colin Fyfe

  2. KAIST, Daejeon, Korea

    Dongsup Kim

  3. Brain Science Research Center and Department of Bio & Brain Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, 305-701, Daejeon, Korea

    Soo-Young Lee

  4. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2008 Springer-Verlag Berlin Heidelberg

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Choi, K., Cichocki, A. (2008). Control of a Wheelchair by Motor Imagery in Real Time. In: Fyfe, C., Kim, D., Lee, SY., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2008. IDEAL 2008. Lecture Notes in Computer Science, vol 5326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88906-9_42

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  • DOI: https://doi.org/10.1007/978-3-540-88906-9_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88905-2

  • Online ISBN: 978-3-540-88906-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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