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EEG-Based Mental Task Classification with Convolutional Neural Networks – Parallel vs 2D Data Representation

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Information Technology in Biomedicine (ITIB 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 762))

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Abstract

In this paper a convolutional neural network, CNN, is trained to perform mental task recognition on the basis of the EEG signal. We address the problem of EEG data representation and processing, comparing two different approaches to the construction of the convolutional layers of the CNN. We demonstrate that splitting the input EEG data into individual channels and frequency bands is beneficial in terms of the generalization error, although the training process is faster and more stable if complete, unsplit two-dimensional spectrograms of the EEG signal are processed.

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Acknowledgement

We would like to thank Dr. Arkadiusz Tomczyk (Institute of Information Technology, Łódź University of Technology) for kindly providing the computational resources to run the experimental evaluation of our CNN models.

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Authors and Affiliations

  1. Institute of Information Technology, Łódź University of Technology, ul. Wólczańska 215, 93-005, Łódź, Poland

    Bartłomiej Stasiak, Sławomir Opałka, Dominik Szajerman & Adam Wojciechowski

Authors
  1. Bartłomiej Stasiak
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  2. Sławomir Opałka
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  3. Dominik Szajerman
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  4. Adam Wojciechowski
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Corresponding author

Correspondence to Bartłomiej Stasiak .

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Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Ewa Pietka

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Wojciech Wieclawek

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Stasiak, B., Opałka, S., Szajerman, D., Wojciechowski, A. (2019). EEG-Based Mental Task Classification with Convolutional Neural Networks – Parallel vs 2D Data Representation. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_48

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