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Processing and Analysis of EEG Signal for SSVEP Detection

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Recent Developments and Achievements in Biocybernetics and Biomedical Engineering (PCBBE 2017)

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Abstract

The aim of the article is to provide a systematic presentation of basic tools that are most commonly used to analyze electroencephalography signals (EEG) in brain–computer interfaces for detection of steady-state visually evoked potentials (SSVEP). We use a database of EEG signals containing SSVEP and demonstrate the desirability of the use of selected methods, showing their benefits. Methods such as independent components analysis (ICA), frequency analysis (DFT), and time-frequency analysis (STFT) are presented. For SSVEP, the features of EEG signal should be stable with time. Short-Time Fourier Transform (STFT) allows to confirm this stability. Independent Component Analysis is used to extract pure SSVEP components. The advantages of each method are described and the obtained results are discussed. Further, source location by the use of low-resolution electromagnetic tomography algorithm is demonstrated.

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Author information

Authors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Marcin Kołodziej, Andrzej Majkowski, Łukasz Oskwarek, Remigiusz J. Rak & Paweł Tarnowski

Authors
  1. Marcin Kołodziej
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  2. Andrzej Majkowski
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  3. Łukasz Oskwarek
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  4. Remigiusz J. Rak
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  5. Paweł Tarnowski
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Corresponding author

Correspondence to Andrzej Majkowski .

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Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Piotr Augustyniak

  2. Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland

    Roman Maniewski

  3. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

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Kołodziej, M., Majkowski, A., Oskwarek, Ł., Rak, R.J., Tarnowski, P. (2018). Processing and Analysis of EEG Signal for SSVEP Detection. In: Augustyniak, P., Maniewski, R., Tadeusiewicz, R. (eds) Recent Developments and Achievements in Biocybernetics and Biomedical Engineering. PCBBE 2017. Advances in Intelligent Systems and Computing, vol 647. Springer, Cham. https://doi.org/10.1007/978-3-319-66905-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-66905-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66904-5

  • Online ISBN: 978-3-319-66905-2

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