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International Conference on Intelligent Data Engineering and Automated Learning

IDEAL 2019: Intelligent Data Engineering and Automated Learning – IDEAL 2019 pp 141–149Cite as

A Method Based on Filter Bank Common Spatial Pattern for Multiclass Motor Imagery BCI

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11872))

Abstract

The Common Spatial Pattern (CSP) algorithm is capable of solving the binary classification problem for the motor image task brain-computer interface (BCI). This paper proposes a novel method based on the Filter Bank Common Spatial Pattern (FBCSP) termed the Multiscale and Overlapping FBCSP (MO-FBCSP). We extend the CSP algorithm for multiclass by using the one-versus-one (OvO) strategy. Multiple periods are selected and combined with the overlapping spectrum of the filter bank which contains useful information. This method is evaluated on the benchmark BCI Competition IV dataset 2a with 9 subjects. An average accuracy of 80% was achieved with the random forest (RF) classifier, and the corresponding kappa value was 0.734. Quantitative results have shown that the proposed scheme outperforms the classical FBCSP algorithm by over 12%.

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Acknowledgement

This work was partially supported by a Natural Science Foundation of China (NSFC) grant (61572076) and Beijing Advanced Innovation Center for Imaging Technology.

Author information

Authors and Affiliations

  1. College of Information Engineering, Capital Normal University, Beijing, China

    Ziqing Xia & Likun Xia

  2. Laboratory of Neural Computing and Intelligent Perception (NCIP), New York, USA

    Ziqing Xia & Likun Xia

  3. International Science and Technology Cooperation Base of Electronic System Reliability and Mathematical Interdisciplinary, Beijing, China

    Likun Xia

  4. Beijing Advanced Innovation Center for Imaging Technology, Beijing, China

    Likun Xia

  5. School of Medicine, Stanford University, Stanford, USA

    Ming Ma

Authors
  1. Ziqing Xia
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  2. Likun Xia
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  3. Ming Ma
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Corresponding author

Correspondence to Likun Xia .

Editor information

Editors and Affiliations

  1. University of Manchester, Manchester, UK

    Hujun Yin

  2. Technical University of Madrid, Madrid, Spain

    David Camacho

  3. University of Birmingham, Birmingham, UK

    Peter Tino

  4. University of Huelva, Huelva, Spain

    Antonio J. Tallón-Ballesteros

  5. University of Exeter, Exeter, UK

    Ronaldo Menezes

  6. University of Manchester, Manchester, UK

    Richard Allmendinger

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Xia, Z., Xia, L., Ma, M. (2019). A Method Based on Filter Bank Common Spatial Pattern for Multiclass Motor Imagery BCI. In: Yin, H., Camacho, D., Tino, P., Tallón-Ballesteros, A., Menezes, R., Allmendinger, R. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2019. IDEAL 2019. Lecture Notes in Computer Science(), vol 11872. Springer, Cham. https://doi.org/10.1007/978-3-030-33617-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-33617-2_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33616-5

  • Online ISBN: 978-3-030-33617-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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