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Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Technologies like passive brain-computer interfaces (BCI) can enhance human-machine interaction. Anyhow, there are still shortcomings in terms of easiness of use, reliability, and generalizability that prevent passive-BCI from entering real-life situations. The current work aimed to technologically...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9331459/ https://www.ncbi.nlm.nih.gov/pubmed/35911603 http://dx.doi.org/10.3389/fnhum.2022.901387 |
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author | Sciaraffa, Nicolina Di Flumeri, Gianluca Germano, Daniele Giorgi, Andrea Di Florio, Antonio Borghini, Gianluca Vozzi, Alessia Ronca, Vincenzo Babiloni, Fabio Aricò, Pietro |
author_facet | Sciaraffa, Nicolina Di Flumeri, Gianluca Germano, Daniele Giorgi, Andrea Di Florio, Antonio Borghini, Gianluca Vozzi, Alessia Ronca, Vincenzo Babiloni, Fabio Aricò, Pietro |
author_sort | Sciaraffa, Nicolina |
collection | PubMed |
description | Technologies like passive brain-computer interfaces (BCI) can enhance human-machine interaction. Anyhow, there are still shortcomings in terms of easiness of use, reliability, and generalizability that prevent passive-BCI from entering real-life situations. The current work aimed to technologically and methodologically design a new gel-free passive-BCI system for out-of-the-lab employment. The choice of the water-based electrodes and the design of a new lightweight headset met the need for easy-to-wear, comfortable, and highly acceptable technology. The proposed system showed high reliability in both laboratory and realistic settings, performing not significantly different from the gold standard based on gel electrodes. In both cases, the proposed system allowed effective discrimination (AUC > 0.9) between low and high levels of workload, vigilance, and stress even for high temporal resolution (<10 s). Finally, the generalizability of the proposed system has been tested through a cross-task calibration. The system calibrated with the data recorded during the laboratory tasks was able to discriminate the targeted human factors during the realistic task reaching AUC values higher than 0.8 at 40 s of temporal resolution in case of vigilance and workload, and 20 s of temporal resolution for the stress monitoring. These results pave the way for ecologic use of the system, where calibration data of the realistic task are difficult to obtain. |
format | Online Article Text |
id | pubmed-9331459 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93314592022-07-29 Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces Sciaraffa, Nicolina Di Flumeri, Gianluca Germano, Daniele Giorgi, Andrea Di Florio, Antonio Borghini, Gianluca Vozzi, Alessia Ronca, Vincenzo Babiloni, Fabio Aricò, Pietro Front Hum Neurosci Human Neuroscience Technologies like passive brain-computer interfaces (BCI) can enhance human-machine interaction. Anyhow, there are still shortcomings in terms of easiness of use, reliability, and generalizability that prevent passive-BCI from entering real-life situations. The current work aimed to technologically and methodologically design a new gel-free passive-BCI system for out-of-the-lab employment. The choice of the water-based electrodes and the design of a new lightweight headset met the need for easy-to-wear, comfortable, and highly acceptable technology. The proposed system showed high reliability in both laboratory and realistic settings, performing not significantly different from the gold standard based on gel electrodes. In both cases, the proposed system allowed effective discrimination (AUC > 0.9) between low and high levels of workload, vigilance, and stress even for high temporal resolution (<10 s). Finally, the generalizability of the proposed system has been tested through a cross-task calibration. The system calibrated with the data recorded during the laboratory tasks was able to discriminate the targeted human factors during the realistic task reaching AUC values higher than 0.8 at 40 s of temporal resolution in case of vigilance and workload, and 20 s of temporal resolution for the stress monitoring. These results pave the way for ecologic use of the system, where calibration data of the realistic task are difficult to obtain. Frontiers Media S.A. 2022-07-14 /pmc/articles/PMC9331459/ /pubmed/35911603 http://dx.doi.org/10.3389/fnhum.2022.901387 Text en Copyright © 2022 Sciaraffa, Di Flumeri, Germano, Giorgi, Di Florio, Borghini, Vozzi, Ronca, Babiloni and Aricò. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Human Neuroscience Sciaraffa, Nicolina Di Flumeri, Gianluca Germano, Daniele Giorgi, Andrea Di Florio, Antonio Borghini, Gianluca Vozzi, Alessia Ronca, Vincenzo Babiloni, Fabio Aricò, Pietro Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces |
title | Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces |
title_full | Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces |
title_fullStr | Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces |
title_full_unstemmed | Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces |
title_short | Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces |
title_sort | evaluation of a new lightweight eeg technology for translational applications of passive brain-computer interfaces |
topic | Human Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9331459/ https://www.ncbi.nlm.nih.gov/pubmed/35911603 http://dx.doi.org/10.3389/fnhum.2022.901387 |
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