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Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface
Brain–computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) machines and computers are usually required to acqu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848923/ https://www.ncbi.nlm.nih.gov/pubmed/31658616 http://dx.doi.org/10.3390/mi10100681 |
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author | Lin, Bor-Shyh Lin, Bor-Shing Yen, Tzu-Hsiang Hsu, Chien-Chin Wang, Yao-Chin |
author_facet | Lin, Bor-Shyh Lin, Bor-Shing Yen, Tzu-Hsiang Hsu, Chien-Chin Wang, Yao-Chin |
author_sort | Lin, Bor-Shyh |
collection | PubMed |
description | Brain–computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) machines and computers are usually required to acquire EEG signal and translate them into control commands, respectively. The sizes of the above machines are usually large, and this increases the limitation for daily applications. Moreover, conventional EEG electrodes also require conductive gels to improve the EEG signal quality. This causes discomfort and inconvenience of use, while the conductive gels may also encounter the problem of drying out during prolonged measurements. In order to improve the above issues, a wearable headset with steady-state visually evoked potential (SSVEP)-based BCI is proposed in this study. Active dry electrodes were designed and implemented to acquire a good EEG signal quality without conductive gels from the hairy site. The SSVEP BCI algorithm was also implemented into the designed field-programmable gate array (FPGA)-based BCI module to translate SSVEP signals into control commands in real time. Moreover, a commercial tablet was used as the visual stimulus device to provide graphic control icons. The whole system was designed as a wearable device to improve convenience of use in daily life, and it could acquire and translate EEG signal directly in the front-end headset. Finally, the performance of the proposed system was validated, and the results showed that it had excellent performance (information transfer rate = 36.08 bits/min). |
format | Online Article Text |
id | pubmed-6848923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68489232019-11-18 Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface Lin, Bor-Shyh Lin, Bor-Shing Yen, Tzu-Hsiang Hsu, Chien-Chin Wang, Yao-Chin Micromachines (Basel) Article Brain–computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) machines and computers are usually required to acquire EEG signal and translate them into control commands, respectively. The sizes of the above machines are usually large, and this increases the limitation for daily applications. Moreover, conventional EEG electrodes also require conductive gels to improve the EEG signal quality. This causes discomfort and inconvenience of use, while the conductive gels may also encounter the problem of drying out during prolonged measurements. In order to improve the above issues, a wearable headset with steady-state visually evoked potential (SSVEP)-based BCI is proposed in this study. Active dry electrodes were designed and implemented to acquire a good EEG signal quality without conductive gels from the hairy site. The SSVEP BCI algorithm was also implemented into the designed field-programmable gate array (FPGA)-based BCI module to translate SSVEP signals into control commands in real time. Moreover, a commercial tablet was used as the visual stimulus device to provide graphic control icons. The whole system was designed as a wearable device to improve convenience of use in daily life, and it could acquire and translate EEG signal directly in the front-end headset. Finally, the performance of the proposed system was validated, and the results showed that it had excellent performance (information transfer rate = 36.08 bits/min). MDPI 2019-10-10 /pmc/articles/PMC6848923/ /pubmed/31658616 http://dx.doi.org/10.3390/mi10100681 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lin, Bor-Shyh Lin, Bor-Shing Yen, Tzu-Hsiang Hsu, Chien-Chin Wang, Yao-Chin Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
title | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
title_full | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
title_fullStr | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
title_full_unstemmed | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
title_short | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
title_sort | design of wearable headset with steady state visually evoked potential-based brain computer interface |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848923/ https://www.ncbi.nlm.nih.gov/pubmed/31658616 http://dx.doi.org/10.3390/mi10100681 |
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