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State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface

The brain–computer interface (BCI) has emerged in recent years and has attracted great attention. As an indispensable part of the BCI signal acquisition system, brain electrodes have a great influence on the quality of the signal, which determines the final effect. Due to the special usage scenario...

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Detalles Bibliográficos
Autores principales: Yuan, Haowen, Li, Yao, Yang, Junjun, Li, Hongjie, Yang, Qinya, Guo, Cuiping, Zhu, Shenmin, Shu, Xiaokang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8705666/
https://www.ncbi.nlm.nih.gov/pubmed/34945371
http://dx.doi.org/10.3390/mi12121521
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author Yuan, Haowen
Li, Yao
Yang, Junjun
Li, Hongjie
Yang, Qinya
Guo, Cuiping
Zhu, Shenmin
Shu, Xiaokang
author_facet Yuan, Haowen
Li, Yao
Yang, Junjun
Li, Hongjie
Yang, Qinya
Guo, Cuiping
Zhu, Shenmin
Shu, Xiaokang
author_sort Yuan, Haowen
collection PubMed
description The brain–computer interface (BCI) has emerged in recent years and has attracted great attention. As an indispensable part of the BCI signal acquisition system, brain electrodes have a great influence on the quality of the signal, which determines the final effect. Due to the special usage scenario of brain electrodes, some specific properties are required for them. In this study, we review the development of three major types of EEG electrodes from the perspective of material selection and structural design, including dry electrodes, wet electrodes, and semi-dry electrodes. Additionally, we provide a reference for the current chaotic performance evaluation of EEG electrodes in some aspects such as electrochemical performance, stability, and so on. Moreover, the challenges and future expectations for EEG electrodes are analyzed.
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spelling pubmed-87056662021-12-25 State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface Yuan, Haowen Li, Yao Yang, Junjun Li, Hongjie Yang, Qinya Guo, Cuiping Zhu, Shenmin Shu, Xiaokang Micromachines (Basel) Review The brain–computer interface (BCI) has emerged in recent years and has attracted great attention. As an indispensable part of the BCI signal acquisition system, brain electrodes have a great influence on the quality of the signal, which determines the final effect. Due to the special usage scenario of brain electrodes, some specific properties are required for them. In this study, we review the development of three major types of EEG electrodes from the perspective of material selection and structural design, including dry electrodes, wet electrodes, and semi-dry electrodes. Additionally, we provide a reference for the current chaotic performance evaluation of EEG electrodes in some aspects such as electrochemical performance, stability, and so on. Moreover, the challenges and future expectations for EEG electrodes are analyzed. MDPI 2021-12-08 /pmc/articles/PMC8705666/ /pubmed/34945371 http://dx.doi.org/10.3390/mi12121521 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Yuan, Haowen
Li, Yao
Yang, Junjun
Li, Hongjie
Yang, Qinya
Guo, Cuiping
Zhu, Shenmin
Shu, Xiaokang
State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface
title State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface
title_full State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface
title_fullStr State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface
title_full_unstemmed State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface
title_short State of the Art of Non-Invasive Electrode Materials for Brain–Computer Interface
title_sort state of the art of non-invasive electrode materials for brain–computer interface
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8705666/
https://www.ncbi.nlm.nih.gov/pubmed/34945371
http://dx.doi.org/10.3390/mi12121521
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