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Development of a Smart Helmet for Strategical BCI Applications

Conducting electrophysiological measurements from human brain function provides a medium for sending commands and messages to the external world, as known as a brain–computer interface (BCI). In this study, we proposed a smart helmet which integrated the novel hygroscopic sponge electrodes and a com...

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Autores principales: Ko, Li-Wei, Chang, Yang, Wu, Pei-Lun, Tzou, Heng-An, Chen, Sheng-Fu, Tang, Shih-Chien, Yeh, Chia-Lung, Chen, Yun-Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515117/
https://www.ncbi.nlm.nih.gov/pubmed/31010105
http://dx.doi.org/10.3390/s19081867
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author Ko, Li-Wei
Chang, Yang
Wu, Pei-Lun
Tzou, Heng-An
Chen, Sheng-Fu
Tang, Shih-Chien
Yeh, Chia-Lung
Chen, Yun-Ju
author_facet Ko, Li-Wei
Chang, Yang
Wu, Pei-Lun
Tzou, Heng-An
Chen, Sheng-Fu
Tang, Shih-Chien
Yeh, Chia-Lung
Chen, Yun-Ju
author_sort Ko, Li-Wei
collection PubMed
description Conducting electrophysiological measurements from human brain function provides a medium for sending commands and messages to the external world, as known as a brain–computer interface (BCI). In this study, we proposed a smart helmet which integrated the novel hygroscopic sponge electrodes and a combat helmet for BCI applications; with the smart helmet, soldiers can carry out extra tasks according to their intentions, i.e., through BCI techniques. There are several existing BCI methods which are distinct from each other; however, mutual issues exist regarding comfort and user acceptability when utilizing such BCI techniques in practical applications; one of the main challenges is the trade-off between using wet and dry electroencephalographic (EEG) electrodes. Recently, several dry EEG electrodes without the necessity of conductive gel have been developed for EEG data collection. Although the gel was claimed to be unnecessary, high contact impedance and low signal-to-noise ratio of dry EEG electrodes have turned out to be the main limitations. In this study, a smart helmet with novel hygroscopic sponge electrodes is developed and investigated for long-term usage of EEG data collection. The existing electrodes and EEG equipment regarding BCI applications were adopted to examine the proposed electrode. In the impedance test of a variety of electrodes, the sponge electrode showed performance averaging 118 kΩ, which was comparable with the best one among existing dry electrodes, which averaged 123 kΩ. The signals acquired from the sponge electrodes and the classic wet electrodes were analyzed with correlation analysis to study the effectiveness. The results indicated that the signals were similar to each other with an average correlation of 90.03% and 82.56% in two-second and ten-second temporal resolutions, respectively, and 97.18% in frequency responses. Furthermore, by applying the proposed differentiable power algorithm to the system, the average accuracy of 21 subjects can reach 91.11% in the steady-state visually evoked potential (SSVEP)-based BCI application regarding a simulated military mission. To sum up, the smart helmet is capable of assisting the soldiers to execute instructions with SSVEP-based BCI when their hands are not available and is a reliable piece of equipment for strategical applications.
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spelling pubmed-65151172019-05-30 Development of a Smart Helmet for Strategical BCI Applications Ko, Li-Wei Chang, Yang Wu, Pei-Lun Tzou, Heng-An Chen, Sheng-Fu Tang, Shih-Chien Yeh, Chia-Lung Chen, Yun-Ju Sensors (Basel) Article Conducting electrophysiological measurements from human brain function provides a medium for sending commands and messages to the external world, as known as a brain–computer interface (BCI). In this study, we proposed a smart helmet which integrated the novel hygroscopic sponge electrodes and a combat helmet for BCI applications; with the smart helmet, soldiers can carry out extra tasks according to their intentions, i.e., through BCI techniques. There are several existing BCI methods which are distinct from each other; however, mutual issues exist regarding comfort and user acceptability when utilizing such BCI techniques in practical applications; one of the main challenges is the trade-off between using wet and dry electroencephalographic (EEG) electrodes. Recently, several dry EEG electrodes without the necessity of conductive gel have been developed for EEG data collection. Although the gel was claimed to be unnecessary, high contact impedance and low signal-to-noise ratio of dry EEG electrodes have turned out to be the main limitations. In this study, a smart helmet with novel hygroscopic sponge electrodes is developed and investigated for long-term usage of EEG data collection. The existing electrodes and EEG equipment regarding BCI applications were adopted to examine the proposed electrode. In the impedance test of a variety of electrodes, the sponge electrode showed performance averaging 118 kΩ, which was comparable with the best one among existing dry electrodes, which averaged 123 kΩ. The signals acquired from the sponge electrodes and the classic wet electrodes were analyzed with correlation analysis to study the effectiveness. The results indicated that the signals were similar to each other with an average correlation of 90.03% and 82.56% in two-second and ten-second temporal resolutions, respectively, and 97.18% in frequency responses. Furthermore, by applying the proposed differentiable power algorithm to the system, the average accuracy of 21 subjects can reach 91.11% in the steady-state visually evoked potential (SSVEP)-based BCI application regarding a simulated military mission. To sum up, the smart helmet is capable of assisting the soldiers to execute instructions with SSVEP-based BCI when their hands are not available and is a reliable piece of equipment for strategical applications. MDPI 2019-04-19 /pmc/articles/PMC6515117/ /pubmed/31010105 http://dx.doi.org/10.3390/s19081867 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
Ko, Li-Wei
Chang, Yang
Wu, Pei-Lun
Tzou, Heng-An
Chen, Sheng-Fu
Tang, Shih-Chien
Yeh, Chia-Lung
Chen, Yun-Ju
Development of a Smart Helmet for Strategical BCI Applications
title Development of a Smart Helmet for Strategical BCI Applications
title_full Development of a Smart Helmet for Strategical BCI Applications
title_fullStr Development of a Smart Helmet for Strategical BCI Applications
title_full_unstemmed Development of a Smart Helmet for Strategical BCI Applications
title_short Development of a Smart Helmet for Strategical BCI Applications
title_sort development of a smart helmet for strategical bci applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515117/
https://www.ncbi.nlm.nih.gov/pubmed/31010105
http://dx.doi.org/10.3390/s19081867
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