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Subject-Specific-Frequency-Band for Motor Imagery EEG Signal Recognition Based on Common Spatial Spectral Pattern

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PRICAI 2019: Trends in Artificial Intelligence (PRICAI 2019)

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Abstract

Over the last decade, processing of biomedical signals using machine learning algorithms has gained widespread attention. Amongst these, one of the most important signals is electroencephalography (EEG) signal that is used to monitor the brain activities. Brain-computer-interface (BCI) has also become a hot topic of research where EEG signals are usually acquired using non-invasive sensors. In this work, we propose a scheme based on common spatial spectral pattern (CSSP) and optimization of temporal filters for improved motor imagery (MI) EEG signal recognition. CSSP is proposed as it improves the spatial resolution while the temporal filter is optimized for each subject as the frequency band which contains most significant information varies amongst different subjects. The proposed scheme is evaluated using two publicly available datasets: BCI competition III dataset IVa and BCI competition IV dataset 1. The proposed scheme obtained promising results and outperformed other state-of-the-art methods. The findings of this work will be beneficial for developing improved BCI systems.

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Author information

Authors and Affiliations

  1. School of Electrical and Electronics Engineering, Fiji National University, Suva, Fiji

    Shiu Kumar

  2. The University of the South Pacific, Laucala Campus, Suva, Fiji

    Shiu Kumar & Alok Sharma

  3. IIIS, Griffith University, Brisbane, QLD, 4111, Australia

    Alok Sharma

  4. RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan

    Alok Sharma & Tatsuhiko Tsunoda

  5. Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan

    Alok Sharma & Tatsuhiko Tsunoda

  6. CREST, JST, Tokyo, 113-8510, Japan

    Alok Sharma & Tatsuhiko Tsunoda

Authors
  1. Shiu Kumar
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  2. Alok Sharma
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  3. Tatsuhiko Tsunoda
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Corresponding authors

Correspondence to Shiu Kumar or Alok Sharma .

Editor information

Editors and Affiliations

  1. Department of Computing, Macquarie University, Sydney, NSW, Australia

    Abhaya C. Nayak

  2. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Alok Sharma

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Kumar, S., Sharma, A., Tsunoda, T. (2019). Subject-Specific-Frequency-Band for Motor Imagery EEG Signal Recognition Based on Common Spatial Spectral Pattern. In: Nayak, A., Sharma, A. (eds) PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. Lecture Notes in Computer Science(), vol 11671. Springer, Cham. https://doi.org/10.1007/978-3-030-29911-8_55

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  • DOI: https://doi.org/10.1007/978-3-030-29911-8_55

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