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Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces
Motor imagery offers an excellent opportunity as a stimulus‐free paradigm for brain–machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, a wireless scalp electronic system wi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498913/ https://www.ncbi.nlm.nih.gov/pubmed/34272934 http://dx.doi.org/10.1002/advs.202101129 |
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author | Mahmood, Musa Kwon, Shinjae Kim, Hojoong Kim, Yun‐Soung Siriaraya, Panote Choi, Jeongmoon Otkhmezuri, Boris Kang, Kyowon Yu, Ki Jun Jang, Young C. Ang, Chee Siang Yeo, Woon‐Hong |
author_facet | Mahmood, Musa Kwon, Shinjae Kim, Hojoong Kim, Yun‐Soung Siriaraya, Panote Choi, Jeongmoon Otkhmezuri, Boris Kang, Kyowon Yu, Ki Jun Jang, Young C. Ang, Chee Siang Yeo, Woon‐Hong |
author_sort | Mahmood, Musa |
collection | PubMed |
description | Motor imagery offers an excellent opportunity as a stimulus‐free paradigm for brain–machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, a wireless scalp electronic system with virtual reality for real‐time, continuous classification of motor imagery brain signals is introduced. This low‐profile, portable system integrates imperceptible microneedle electrodes and soft wireless circuits. Virtual reality addresses subject variance in detectable EEG response to motor imagery by providing clear, consistent visuals and instant biofeedback. The wearable soft system offers advantageous contact surface area and reduced electrode impedance density, resulting in significantly enhanced EEG signals and classification accuracy. The combination with convolutional neural network‐machine learning provides a real‐time, continuous motor imagery‐based brain–machine interface. With four human subjects, the scalp electronic system offers a high classification accuracy (93.22 ± 1.33% for four classes), allowing wireless, real‐time control of a virtual reality game. |
format | Online Article Text |
id | pubmed-8498913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84989132021-10-12 Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces Mahmood, Musa Kwon, Shinjae Kim, Hojoong Kim, Yun‐Soung Siriaraya, Panote Choi, Jeongmoon Otkhmezuri, Boris Kang, Kyowon Yu, Ki Jun Jang, Young C. Ang, Chee Siang Yeo, Woon‐Hong Adv Sci (Weinh) Research Article Motor imagery offers an excellent opportunity as a stimulus‐free paradigm for brain–machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, a wireless scalp electronic system with virtual reality for real‐time, continuous classification of motor imagery brain signals is introduced. This low‐profile, portable system integrates imperceptible microneedle electrodes and soft wireless circuits. Virtual reality addresses subject variance in detectable EEG response to motor imagery by providing clear, consistent visuals and instant biofeedback. The wearable soft system offers advantageous contact surface area and reduced electrode impedance density, resulting in significantly enhanced EEG signals and classification accuracy. The combination with convolutional neural network‐machine learning provides a real‐time, continuous motor imagery‐based brain–machine interface. With four human subjects, the scalp electronic system offers a high classification accuracy (93.22 ± 1.33% for four classes), allowing wireless, real‐time control of a virtual reality game. John Wiley and Sons Inc. 2021-07-17 /pmc/articles/PMC8498913/ /pubmed/34272934 http://dx.doi.org/10.1002/advs.202101129 Text en © 2021 The Authors. Advanced Science published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Mahmood, Musa Kwon, Shinjae Kim, Hojoong Kim, Yun‐Soung Siriaraya, Panote Choi, Jeongmoon Otkhmezuri, Boris Kang, Kyowon Yu, Ki Jun Jang, Young C. Ang, Chee Siang Yeo, Woon‐Hong Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces |
title | Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces |
title_full | Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces |
title_fullStr | Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces |
title_full_unstemmed | Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces |
title_short | Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces |
title_sort | wireless soft scalp electronics and virtual reality system for motor imagery‐based brain–machine interfaces |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498913/ https://www.ncbi.nlm.nih.gov/pubmed/34272934 http://dx.doi.org/10.1002/advs.202101129 |
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