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Use of Wavelets for Recognizing Types of Motion by Means of Data on the Electrical Activity of the Brain

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Abstract

We consider the task of oscillatory pattern recognition on the fragments of electroencephalogram records obtained during motion and their mental representation for the development of a neurointerface software. Using a multiscale analysis, the number of channels is estimated that will provide reliable separation of motions of various types from background activity.

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Funding

This investigation was supported in part by the Russian Science Foundation, project no. 17-72-30003.

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Authors and Affiliations

  1. Yuri Gagarin State Technical University of Saratov, 410054, Saratov, Russia

    D. S. Grishina & A. N. Pavlov

  2. Saratov State University, 410012, Saratov, Russia

    A. N. Pavlov & O. N. Pavlova

  3. Innopolis University, 420500, Innopolis, Tatarstan, Russia

    A. E. Runnova

Authors
  1. D. S. Grishina
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  2. A. N. Pavlov
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  3. O. N. Pavlova
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  4. A. E. Runnova
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Corresponding author

Correspondence to A. N. Pavlov.

Ethics declarations

All studies involving people were conducted in accordance with principles for human experimentation as defined in the Declaration of Helsinki and International Conference on Harmonization Good Clinical Practice guidelines and later amendments or comparable ethical standards, as well as approved by the relevant institutional review boards. Informed consent was obtained from every participant in the study.

CONFLICT OF INTEREST. The authors declare that they have no conflict of interest.

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Translated by P. Pozdeev

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Grishina, D.S., Pavlov, A.N., Pavlova, O.N. et al. Use of Wavelets for Recognizing Types of Motion by Means of Data on the Electrical Activity of the Brain. Tech. Phys. Lett. 45, 820–822 (2019). https://doi.org/10.1134/S1063785019080224

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  • DOI: https://doi.org/10.1134/S1063785019080224

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