EEG Dimension Reduction in Motor Imagery-based BCI Approach

Dmitry Lazurenko; Valery Kiroy; Dmitry Shaposhnikov

doi:doi:10.11648/j.aap.20220701.11

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EEG Dimension Reduction in Motor Imagery-based BCI Approach

Dmitry Lazurenko, Valery Kiroy, Dmitry Shaposhnikov

Published in Advances in Applied Physiology (Volume 7, Issue 1)

Received: 7 December 2021 Accepted: 4 January 2022 Published: 12 January 2022

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Abstract

Although a significant number of studies have been devoted to the investigation of the electrographic correlates and neurophysiological mechanisms of voluntary movement and motor imagery-related brain activity, there is a question on which EEG characteristics reflect its content. Considering that motor imagery is a complex cognitive process which requires coordinated activity of a number of cortical structures of the hemispheres, the EEG dimension reduction problems were studied. The values were recorded from 14 channels in eight subjects in the task of voluntary movement execution and motor imagery activity. The principal component analysis has shown that the orthogonal transformation of the EEG channels has formed of 3 components, sufficient to describe a multidimensional brain pattern. The description of invariant EEG patterns of voluntary movements and motor imagery can be performed on the basis of a compressed set of features of the covariance matrix. It has been shown that frontal and central areas as critical brain structures controlling behaviour predominantly participated in the performance of movement execution. Whereas under conditions of motor imagery-related brain activity, the loci remaining in the primary motor cortex were additionally formed in the parieto-occipital associative regions of the brain, with a partial dominance of the right hemisphere. The eigenvectors of target spatio-temporal EEG patterns associated with the movements execution and motor imagery can be used as markers for classification in the BCIs.

Published in	Advances in Applied Physiology (Volume 7, Issue 1)
DOI	10.11648/j.aap.20220701.11
Page(s)	1-7
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

EEG, Movement Execution, Motor Imagery, Dimension Reduction, Component, PCA, LDA

References

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APA Style

Dmitry Lazurenko, Valery Kiroy, Dmitry Shaposhnikov. (2022). EEG Dimension Reduction in Motor Imagery-based BCI Approach. Advances in Applied Physiology, 7(1), 1-7. https://doi.org/10.11648/j.aap.20220701.11

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ACS Style

Dmitry Lazurenko; Valery Kiroy; Dmitry Shaposhnikov. EEG Dimension Reduction in Motor Imagery-based BCI Approach. Adv. Appl. Physiol. 2022, 7(1), 1-7. doi: 10.11648/j.aap.20220701.11

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AMA Style

Dmitry Lazurenko, Valery Kiroy, Dmitry Shaposhnikov. EEG Dimension Reduction in Motor Imagery-based BCI Approach. Adv Appl Physiol. 2022;7(1):1-7. doi: 10.11648/j.aap.20220701.11

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@article{10.11648/j.aap.20220701.11,
  author = {Dmitry Lazurenko and Valery Kiroy and Dmitry Shaposhnikov},
  title = {EEG Dimension Reduction in Motor Imagery-based BCI Approach},
  journal = {Advances in Applied Physiology},
  volume = {7},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.aap.20220701.11},
  url = {https://doi.org/10.11648/j.aap.20220701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aap.20220701.11},
  abstract = {Although a significant number of studies have been devoted to the investigation of the electrographic correlates and neurophysiological mechanisms of voluntary movement and motor imagery-related brain activity, there is a question on which EEG characteristics reflect its content. Considering that motor imagery is a complex cognitive process which requires coordinated activity of a number of cortical structures of the hemispheres, the EEG dimension reduction problems were studied. The values were recorded from 14 channels in eight subjects in the task of voluntary movement execution and motor imagery activity. The principal component analysis has shown that the orthogonal transformation of the EEG channels has formed of 3 components, sufficient to describe a multidimensional brain pattern. The description of invariant EEG patterns of voluntary movements and motor imagery can be performed on the basis of a compressed set of features of the covariance matrix. It has been shown that frontal and central areas as critical brain structures controlling behaviour predominantly participated in the performance of movement execution. Whereas under conditions of motor imagery-related brain activity, the loci remaining in the primary motor cortex were additionally formed in the parieto-occipital associative regions of the brain, with a partial dominance of the right hemisphere. The eigenvectors of target spatio-temporal EEG patterns associated with the movements execution and motor imagery can be used as markers for classification in the BCIs.},
 year = {2022}
}

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TY  - JOUR
T1  - EEG Dimension Reduction in Motor Imagery-based BCI Approach
AU  - Dmitry Lazurenko
AU  - Valery Kiroy
AU  - Dmitry Shaposhnikov
Y1  - 2022/01/12
PY  - 2022
N1  - https://doi.org/10.11648/j.aap.20220701.11
DO  - 10.11648/j.aap.20220701.11
T2  - Advances in Applied Physiology
JF  - Advances in Applied Physiology
JO  - Advances in Applied Physiology
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2471-9714
UR  - https://doi.org/10.11648/j.aap.20220701.11
AB  - Although a significant number of studies have been devoted to the investigation of the electrographic correlates and neurophysiological mechanisms of voluntary movement and motor imagery-related brain activity, there is a question on which EEG characteristics reflect its content. Considering that motor imagery is a complex cognitive process which requires coordinated activity of a number of cortical structures of the hemispheres, the EEG dimension reduction problems were studied. The values were recorded from 14 channels in eight subjects in the task of voluntary movement execution and motor imagery activity. The principal component analysis has shown that the orthogonal transformation of the EEG channels has formed of 3 components, sufficient to describe a multidimensional brain pattern. The description of invariant EEG patterns of voluntary movements and motor imagery can be performed on the basis of a compressed set of features of the covariance matrix. It has been shown that frontal and central areas as critical brain structures controlling behaviour predominantly participated in the performance of movement execution. Whereas under conditions of motor imagery-related brain activity, the loci remaining in the primary motor cortex were additionally formed in the parieto-occipital associative regions of the brain, with a partial dominance of the right hemisphere. The eigenvectors of target spatio-temporal EEG patterns associated with the movements execution and motor imagery can be used as markers for classification in the BCIs.
VL  - 7
IS  - 1
ER  -

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Author Information

Dmitry Lazurenko

Research Center for Neurotechnology, Southern Federal University (SFedU), Rostov-on-Don, Russia
Valery Kiroy

Research Center for Neurotechnology, Southern Federal University (SFedU), Rostov-on-Don, Russia
Dmitry Shaposhnikov

Research Center for Neurotechnology, Southern Federal University (SFedU), Rostov-on-Don, Russia

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APA Style

Dmitry Lazurenko, Valery Kiroy, Dmitry Shaposhnikov. (2022). EEG Dimension Reduction in Motor Imagery-based BCI Approach. Advances in Applied Physiology, 7(1), 1-7. https://doi.org/10.11648/j.aap.20220701.11

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ACS Style

Dmitry Lazurenko; Valery Kiroy; Dmitry Shaposhnikov. EEG Dimension Reduction in Motor Imagery-based BCI Approach. Adv. Appl. Physiol. 2022, 7(1), 1-7. doi: 10.11648/j.aap.20220701.11

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AMA Style

Dmitry Lazurenko, Valery Kiroy, Dmitry Shaposhnikov. EEG Dimension Reduction in Motor Imagery-based BCI Approach. Adv Appl Physiol. 2022;7(1):1-7. doi: 10.11648/j.aap.20220701.11

Copy | Download

@article{10.11648/j.aap.20220701.11,
  author = {Dmitry Lazurenko and Valery Kiroy and Dmitry Shaposhnikov},
  title = {EEG Dimension Reduction in Motor Imagery-based BCI Approach},
  journal = {Advances in Applied Physiology},
  volume = {7},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.aap.20220701.11},
  url = {https://doi.org/10.11648/j.aap.20220701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aap.20220701.11},
  abstract = {Although a significant number of studies have been devoted to the investigation of the electrographic correlates and neurophysiological mechanisms of voluntary movement and motor imagery-related brain activity, there is a question on which EEG characteristics reflect its content. Considering that motor imagery is a complex cognitive process which requires coordinated activity of a number of cortical structures of the hemispheres, the EEG dimension reduction problems were studied. The values were recorded from 14 channels in eight subjects in the task of voluntary movement execution and motor imagery activity. The principal component analysis has shown that the orthogonal transformation of the EEG channels has formed of 3 components, sufficient to describe a multidimensional brain pattern. The description of invariant EEG patterns of voluntary movements and motor imagery can be performed on the basis of a compressed set of features of the covariance matrix. It has been shown that frontal and central areas as critical brain structures controlling behaviour predominantly participated in the performance of movement execution. Whereas under conditions of motor imagery-related brain activity, the loci remaining in the primary motor cortex were additionally formed in the parieto-occipital associative regions of the brain, with a partial dominance of the right hemisphere. The eigenvectors of target spatio-temporal EEG patterns associated with the movements execution and motor imagery can be used as markers for classification in the BCIs.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - EEG Dimension Reduction in Motor Imagery-based BCI Approach
AU  - Dmitry Lazurenko
AU  - Valery Kiroy
AU  - Dmitry Shaposhnikov
Y1  - 2022/01/12
PY  - 2022
N1  - https://doi.org/10.11648/j.aap.20220701.11
DO  - 10.11648/j.aap.20220701.11
T2  - Advances in Applied Physiology
JF  - Advances in Applied Physiology
JO  - Advances in Applied Physiology
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2471-9714
UR  - https://doi.org/10.11648/j.aap.20220701.11
AB  - Although a significant number of studies have been devoted to the investigation of the electrographic correlates and neurophysiological mechanisms of voluntary movement and motor imagery-related brain activity, there is a question on which EEG characteristics reflect its content. Considering that motor imagery is a complex cognitive process which requires coordinated activity of a number of cortical structures of the hemispheres, the EEG dimension reduction problems were studied. The values were recorded from 14 channels in eight subjects in the task of voluntary movement execution and motor imagery activity. The principal component analysis has shown that the orthogonal transformation of the EEG channels has formed of 3 components, sufficient to describe a multidimensional brain pattern. The description of invariant EEG patterns of voluntary movements and motor imagery can be performed on the basis of a compressed set of features of the covariance matrix. It has been shown that frontal and central areas as critical brain structures controlling behaviour predominantly participated in the performance of movement execution. Whereas under conditions of motor imagery-related brain activity, the loci remaining in the primary motor cortex were additionally formed in the parieto-occipital associative regions of the brain, with a partial dominance of the right hemisphere. The eigenvectors of target spatio-temporal EEG patterns associated with the movements execution and motor imagery can be used as markers for classification in the BCIs.
VL  - 7
IS  - 1
ER  -

Copy | Download