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Dynamics of Frequency Characteristics of Visually Evoked Potentials of Electroencephalography During the Work with Brain-Computer Interfaces

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Speech and Computer (SPECOM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13721))

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Abstract

The paper verifies the hypothesis of time-dependent dynamics of steady-state visual evoked potentials during a short series of stimulations (15 s) simulating work with brain-computer interfaces. Using deep machine learning of a neural network with direct propagation and known methods of machine classification, the frequency characteristics of the visual evoked potentials of electroencephalography during the work with brain-computer interfaces are analyzed. It is shown that the temporal dynamics of steady-state visual evoked potentials even for such a short period of time can sufficiently change the parameters. It can potentially serve as an obstacle for work with this type of brain-computer interfaces for a number of users. The described approach allows us to confirm the hypothesis that over time the brain shows signs of fatigue, consisting in changes in the frequency-time characteristics of the registered signal. Thus, the human brain shows signs of fatigue during sessions of steady-state visual evoked potentials.

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Acknowledgement

This work was supported by RFBR grant 19–29-01156 mk.

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Authors and Affiliations

  1. V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia

    Yaroslav Turovsky, Daniyar Wolf, Roman Meshcheryakov & Anastasia Iskhakova

Authors
  1. Yaroslav Turovsky
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  2. Daniyar Wolf
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  3. Roman Meshcheryakov
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  4. Anastasia Iskhakova
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Corresponding author

Correspondence to Anastasia Iskhakova .

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Editors and Affiliations

  1. Indian Institute of Technology Dharwad, Dharwad, India

    S. R. Mahadeva Prasanna

  2. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Alexey Karpov

  3. Koneru Lakshmaiah Education Foundation, Vaddeswaram, India

    K. Samudravijaya

  4. KIIT Group of Colleges, Gurugram, India

    Shyam S. Agrawal

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Turovsky, Y., Wolf, D., Meshcheryakov, R., Iskhakova, A. (2022). Dynamics of Frequency Characteristics of Visually Evoked Potentials of Electroencephalography During the Work with Brain-Computer Interfaces. In: Prasanna, S.R.M., Karpov, A., Samudravijaya, K., Agrawal, S.S. (eds) Speech and Computer. SPECOM 2022. Lecture Notes in Computer Science(), vol 13721. Springer, Cham. https://doi.org/10.1007/978-3-031-20980-2_57

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  • DOI: https://doi.org/10.1007/978-3-031-20980-2_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20979-6

  • Online ISBN: 978-3-031-20980-2

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