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Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems

This paper presents an illusory visual motion stimulus-based brain-computer interface (BCI). We aim to use the proposed system to enhance the motor imagery (MI) modality. Since motor imagery requires a long time for training, a stimulation method with external stimuli through the sensory system is a...

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Autores principales: Punsawad, Yunyong, Siribunyaphat, Nannaphat, Wongsawat, Yodchanan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988285/
https://www.ncbi.nlm.nih.gov/pubmed/33786390
http://dx.doi.org/10.1016/j.heliyon.2021.e06457
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author Punsawad, Yunyong
Siribunyaphat, Nannaphat
Wongsawat, Yodchanan
author_facet Punsawad, Yunyong
Siribunyaphat, Nannaphat
Wongsawat, Yodchanan
author_sort Punsawad, Yunyong
collection PubMed
description This paper presents an illusory visual motion stimulus-based brain-computer interface (BCI). We aim to use the proposed system to enhance the motor imagery (MI) modality. Since motor imagery requires a long time for training, a stimulation method with external stimuli through the sensory system is an alternative method for increasing efficiency. The research is divided into two parts. First, we observed the visual motion illusion pattern based on brain topographic maps for the novel BCI modality. Second, we implemented the illusory visual motion stimulus-based BCI system. Arrow and moving-arrow patterns were used to modulate alpha rhythms at the visual and motor cortex. The arrow pattern had an average classification accuracy of approximately 78.5%. Additionally, illusory visual motion stimulus-based BCI systems are proposed using the proposed feature extraction and decision-making algorithm. This proposed BCI system can control the cursor moving in the left or right direction with the designed algorithm to create five commands for assistive communication. Ten volunteers participated in the experiment, and a brain-computer interface system with motor imagery and an illusory visual motion stimulus were used to compare efficiencies. The results showed that the proposed method achieved approximately 4% higher accuracy than motor imagery. The accuracy of the proposed illusory visual motion stimulus and algorithm was approximately 80.3%. Therefore, an illusory visual motion stimulus hybrid BCI system can be incorporated into the MI-based BCI system for beginner motor imagery. Based on the results, the proposed assistive communication system can be used to enhance communication in people with severe disabilities.
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spelling pubmed-79882852021-03-29 Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems Punsawad, Yunyong Siribunyaphat, Nannaphat Wongsawat, Yodchanan Heliyon Research Article This paper presents an illusory visual motion stimulus-based brain-computer interface (BCI). We aim to use the proposed system to enhance the motor imagery (MI) modality. Since motor imagery requires a long time for training, a stimulation method with external stimuli through the sensory system is an alternative method for increasing efficiency. The research is divided into two parts. First, we observed the visual motion illusion pattern based on brain topographic maps for the novel BCI modality. Second, we implemented the illusory visual motion stimulus-based BCI system. Arrow and moving-arrow patterns were used to modulate alpha rhythms at the visual and motor cortex. The arrow pattern had an average classification accuracy of approximately 78.5%. Additionally, illusory visual motion stimulus-based BCI systems are proposed using the proposed feature extraction and decision-making algorithm. This proposed BCI system can control the cursor moving in the left or right direction with the designed algorithm to create five commands for assistive communication. Ten volunteers participated in the experiment, and a brain-computer interface system with motor imagery and an illusory visual motion stimulus were used to compare efficiencies. The results showed that the proposed method achieved approximately 4% higher accuracy than motor imagery. The accuracy of the proposed illusory visual motion stimulus and algorithm was approximately 80.3%. Therefore, an illusory visual motion stimulus hybrid BCI system can be incorporated into the MI-based BCI system for beginner motor imagery. Based on the results, the proposed assistive communication system can be used to enhance communication in people with severe disabilities. Elsevier 2021-03-16 /pmc/articles/PMC7988285/ /pubmed/33786390 http://dx.doi.org/10.1016/j.heliyon.2021.e06457 Text en © 2021 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Punsawad, Yunyong
Siribunyaphat, Nannaphat
Wongsawat, Yodchanan
Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems
title Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems
title_full Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems
title_fullStr Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems
title_full_unstemmed Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems
title_short Exploration of illusory visual motion stimuli: An EEG-based brain-computer interface for practical assistive communication systems
title_sort exploration of illusory visual motion stimuli: an eeg-based brain-computer interface for practical assistive communication systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988285/
https://www.ncbi.nlm.nih.gov/pubmed/33786390
http://dx.doi.org/10.1016/j.heliyon.2021.e06457
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