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Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice

Motor imagery (MI) is an endogenous mental process and is commonly used as an electroencephalogram (EEG)-based brain–computer interface (BCI) strategy. Previous studies of P300 and MI-based (without online feedback) BCI have shown that mental states like fatigue can negatively affect participants’ E...

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Autores principales: Li, Songwei, Duan, Junyi, Sun, Yu, Sheng, Xinjun, Zhu, Xiangyang, Meng, Jianjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8678598/
https://www.ncbi.nlm.nih.gov/pubmed/34924942
http://dx.doi.org/10.3389/fnins.2021.773790
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author Li, Songwei
Duan, Junyi
Sun, Yu
Sheng, Xinjun
Zhu, Xiangyang
Meng, Jianjun
author_facet Li, Songwei
Duan, Junyi
Sun, Yu
Sheng, Xinjun
Zhu, Xiangyang
Meng, Jianjun
author_sort Li, Songwei
collection PubMed
description Motor imagery (MI) is an endogenous mental process and is commonly used as an electroencephalogram (EEG)-based brain–computer interface (BCI) strategy. Previous studies of P300 and MI-based (without online feedback) BCI have shown that mental states like fatigue can negatively affect participants’ EEG signatures. However, exogenous stimuli cause visual fatigue, which might have a different mechanism than endogenous tasks do. Furthermore, subjects could adjust themselves if online feedback is provided. In this sense, it is still unclear how fatigue affects online MI-based BCI performance. With this question, 12 healthy subjects are recruited to investigate this issue, and an MI-based online BCI experiment is performed for four sessions on different days. The first session is for training, and the other three sessions differ in rest condition and duration—no rest, 16-min eyes-open rest, and 16-min eyes-closed rest—arranged in a pseudo-random order. Multidimensional fatigue inventory (MFI) and short stress state questionnaire (SSSQ) reveal that general fatigue, mental fatigue, and distress have increased, while engagement has decreased significantly within certain sessions. However, the BCI performances, including percent valid correct (PVC) and information transfer rate (ITR), show no significant change across 400 trials. The results suggest that although the repetitive MI task has affected subjects’ mental states, their BCI performances and feature separability within a session are not affected by the task significantly. Further electrophysiological analysis reveals that the alpha-band power in the sensorimotor area has an increasing tendency, while event-related desynchronization (ERD) modulation level has a decreasing trend. During the rest time, no physiological difference has been found in the eyes-open rest condition; on the contrary, the alpha-band power increase and subsequent decrease appear in the eyes-closed rest condition. In summary, this experiment shows evidence that mental states can change dramatically in the intensive MI-BCI practice, but BCI performances could be maintained.
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spelling pubmed-86785982021-12-18 Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice Li, Songwei Duan, Junyi Sun, Yu Sheng, Xinjun Zhu, Xiangyang Meng, Jianjun Front Neurosci Neuroscience Motor imagery (MI) is an endogenous mental process and is commonly used as an electroencephalogram (EEG)-based brain–computer interface (BCI) strategy. Previous studies of P300 and MI-based (without online feedback) BCI have shown that mental states like fatigue can negatively affect participants’ EEG signatures. However, exogenous stimuli cause visual fatigue, which might have a different mechanism than endogenous tasks do. Furthermore, subjects could adjust themselves if online feedback is provided. In this sense, it is still unclear how fatigue affects online MI-based BCI performance. With this question, 12 healthy subjects are recruited to investigate this issue, and an MI-based online BCI experiment is performed for four sessions on different days. The first session is for training, and the other three sessions differ in rest condition and duration—no rest, 16-min eyes-open rest, and 16-min eyes-closed rest—arranged in a pseudo-random order. Multidimensional fatigue inventory (MFI) and short stress state questionnaire (SSSQ) reveal that general fatigue, mental fatigue, and distress have increased, while engagement has decreased significantly within certain sessions. However, the BCI performances, including percent valid correct (PVC) and information transfer rate (ITR), show no significant change across 400 trials. The results suggest that although the repetitive MI task has affected subjects’ mental states, their BCI performances and feature separability within a session are not affected by the task significantly. Further electrophysiological analysis reveals that the alpha-band power in the sensorimotor area has an increasing tendency, while event-related desynchronization (ERD) modulation level has a decreasing trend. During the rest time, no physiological difference has been found in the eyes-open rest condition; on the contrary, the alpha-band power increase and subsequent decrease appear in the eyes-closed rest condition. In summary, this experiment shows evidence that mental states can change dramatically in the intensive MI-BCI practice, but BCI performances could be maintained. Frontiers Media S.A. 2021-12-02 /pmc/articles/PMC8678598/ /pubmed/34924942 http://dx.doi.org/10.3389/fnins.2021.773790 Text en Copyright © 2021 Li, Duan, Sun, Sheng, Zhu and Meng. 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 Neuroscience
Li, Songwei
Duan, Junyi
Sun, Yu
Sheng, Xinjun
Zhu, Xiangyang
Meng, Jianjun
Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice
title Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice
title_full Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice
title_fullStr Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice
title_full_unstemmed Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice
title_short Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice
title_sort exploring fatigue effects on performance variation of intensive brain–computer interface practice
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8678598/
https://www.ncbi.nlm.nih.gov/pubmed/34924942
http://dx.doi.org/10.3389/fnins.2021.773790
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