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Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset
Recent advances in mobile electroencephalogram (EEG) systems, featuring non-prep dry electrodes and wireless telemetry, have enabled and promoted the applications of mobile brain-computer interfaces (BCIs) in our daily life. Since the brain may behave differently while people are actively situated i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978365/ https://www.ncbi.nlm.nih.gov/pubmed/24744718 http://dx.doi.org/10.3389/fnhum.2014.00182 |
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author | Lin, Yuan-Pin Wang, Yijun Wei, Chun-Shu Jung, Tzyy-Ping |
author_facet | Lin, Yuan-Pin Wang, Yijun Wei, Chun-Shu Jung, Tzyy-Ping |
author_sort | Lin, Yuan-Pin |
collection | PubMed |
description | Recent advances in mobile electroencephalogram (EEG) systems, featuring non-prep dry electrodes and wireless telemetry, have enabled and promoted the applications of mobile brain-computer interfaces (BCIs) in our daily life. Since the brain may behave differently while people are actively situated in ecologically-valid environments versus highly-controlled laboratory environments, it remains unclear how well the current laboratory-oriented BCI demonstrations can be translated into operational BCIs for users with naturalistic movements. Understanding inherent links between natural human behaviors and brain activities is the key to ensuring the applicability and stability of mobile BCIs. This study aims to assess the quality of steady-state visual-evoked potentials (SSVEPs), which is one of promising channels for functioning BCI systems, recorded using a mobile EEG system under challenging recording conditions, e.g., walking. To systematically explore the effects of walking locomotion on the SSVEPs, this study instructed subjects to stand or walk on a treadmill running at speeds of 1, 2, and 3 mile (s) per hour (MPH) while concurrently perceiving visual flickers (11 and 12 Hz). Empirical results of this study showed that the SSVEP amplitude tended to deteriorate when subjects switched from standing to walking. Such SSVEP suppression could be attributed to the walking locomotion, leading to distinctly deteriorated SSVEP detectability from standing (84.87 ± 13.55%) to walking (1 MPH: 83.03 ± 13.24%, 2 MPH: 79.47 ± 13.53%, and 3 MPH: 75.26 ± 17.89%). These findings not only demonstrated the applicability and limitations of SSVEPs recorded from freely behaving humans in realistic environments, but also provide useful methods and techniques for boosting the translation of the BCI technology from laboratory demonstrations to practical applications. |
format | Online Article Text |
id | pubmed-3978365 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-39783652014-04-17 Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset Lin, Yuan-Pin Wang, Yijun Wei, Chun-Shu Jung, Tzyy-Ping Front Hum Neurosci Neuroscience Recent advances in mobile electroencephalogram (EEG) systems, featuring non-prep dry electrodes and wireless telemetry, have enabled and promoted the applications of mobile brain-computer interfaces (BCIs) in our daily life. Since the brain may behave differently while people are actively situated in ecologically-valid environments versus highly-controlled laboratory environments, it remains unclear how well the current laboratory-oriented BCI demonstrations can be translated into operational BCIs for users with naturalistic movements. Understanding inherent links between natural human behaviors and brain activities is the key to ensuring the applicability and stability of mobile BCIs. This study aims to assess the quality of steady-state visual-evoked potentials (SSVEPs), which is one of promising channels for functioning BCI systems, recorded using a mobile EEG system under challenging recording conditions, e.g., walking. To systematically explore the effects of walking locomotion on the SSVEPs, this study instructed subjects to stand or walk on a treadmill running at speeds of 1, 2, and 3 mile (s) per hour (MPH) while concurrently perceiving visual flickers (11 and 12 Hz). Empirical results of this study showed that the SSVEP amplitude tended to deteriorate when subjects switched from standing to walking. Such SSVEP suppression could be attributed to the walking locomotion, leading to distinctly deteriorated SSVEP detectability from standing (84.87 ± 13.55%) to walking (1 MPH: 83.03 ± 13.24%, 2 MPH: 79.47 ± 13.53%, and 3 MPH: 75.26 ± 17.89%). These findings not only demonstrated the applicability and limitations of SSVEPs recorded from freely behaving humans in realistic environments, but also provide useful methods and techniques for boosting the translation of the BCI technology from laboratory demonstrations to practical applications. Frontiers Media S.A. 2014-03-31 /pmc/articles/PMC3978365/ /pubmed/24744718 http://dx.doi.org/10.3389/fnhum.2014.00182 Text en Copyright © 2014 Lin, Wang, Wei and Jung. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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 | Neuroscience Lin, Yuan-Pin Wang, Yijun Wei, Chun-Shu Jung, Tzyy-Ping Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset |
title | Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset |
title_full | Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset |
title_fullStr | Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset |
title_full_unstemmed | Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset |
title_short | Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset |
title_sort | assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978365/ https://www.ncbi.nlm.nih.gov/pubmed/24744718 http://dx.doi.org/10.3389/fnhum.2014.00182 |
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