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Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System †

The present study introduces a brain–computer interface designed and prototyped to be wearable and usable in daily life. Eight dry electroencephalographic sensors were adopted to acquire the brain activity associated with motor imagery. Multimodal feedback in extended reality was exploited to improv...

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Detalles Bibliográficos
Autores principales: Arpaia, Pasquale, Coyle, Damien, Esposito, Antonio, Natalizio, Angela, Parvis, Marco, Pesola, Marisa, Vallefuoco, Ersilia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346666/
https://www.ncbi.nlm.nih.gov/pubmed/37447686
http://dx.doi.org/10.3390/s23135836
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author Arpaia, Pasquale
Coyle, Damien
Esposito, Antonio
Natalizio, Angela
Parvis, Marco
Pesola, Marisa
Vallefuoco, Ersilia
author_facet Arpaia, Pasquale
Coyle, Damien
Esposito, Antonio
Natalizio, Angela
Parvis, Marco
Pesola, Marisa
Vallefuoco, Ersilia
author_sort Arpaia, Pasquale
collection PubMed
description The present study introduces a brain–computer interface designed and prototyped to be wearable and usable in daily life. Eight dry electroencephalographic sensors were adopted to acquire the brain activity associated with motor imagery. Multimodal feedback in extended reality was exploited to improve the online detection of neurological phenomena. Twenty-seven healthy subjects used the proposed system in five sessions to investigate the effects of feedback on motor imagery. The sample was divided into two equal-sized groups: a “neurofeedback” group, which performed motor imagery while receiving feedback, and a “control” group, which performed motor imagery with no feedback. Questionnaires were administered to participants aiming to investigate the usability of the proposed system and an individual’s ability to imagine movements. The highest mean classification accuracy across the subjects of the control group was about 62% with 3% associated type A uncertainty, and it was 69% with 3% uncertainty for the neurofeedback group. Moreover, the results in some cases were significantly higher for the neurofeedback group. The perceived usability by all participants was high. Overall, the study aimed at highlighting the advantages and the pitfalls of using a wearable brain–computer interface with dry sensors. Notably, this technology can be adopted for safe and economically viable tele-rehabilitation.
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spelling pubmed-103466662023-07-15 Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System † Arpaia, Pasquale Coyle, Damien Esposito, Antonio Natalizio, Angela Parvis, Marco Pesola, Marisa Vallefuoco, Ersilia Sensors (Basel) Article The present study introduces a brain–computer interface designed and prototyped to be wearable and usable in daily life. Eight dry electroencephalographic sensors were adopted to acquire the brain activity associated with motor imagery. Multimodal feedback in extended reality was exploited to improve the online detection of neurological phenomena. Twenty-seven healthy subjects used the proposed system in five sessions to investigate the effects of feedback on motor imagery. The sample was divided into two equal-sized groups: a “neurofeedback” group, which performed motor imagery while receiving feedback, and a “control” group, which performed motor imagery with no feedback. Questionnaires were administered to participants aiming to investigate the usability of the proposed system and an individual’s ability to imagine movements. The highest mean classification accuracy across the subjects of the control group was about 62% with 3% associated type A uncertainty, and it was 69% with 3% uncertainty for the neurofeedback group. Moreover, the results in some cases were significantly higher for the neurofeedback group. The perceived usability by all participants was high. Overall, the study aimed at highlighting the advantages and the pitfalls of using a wearable brain–computer interface with dry sensors. Notably, this technology can be adopted for safe and economically viable tele-rehabilitation. MDPI 2023-06-23 /pmc/articles/PMC10346666/ /pubmed/37447686 http://dx.doi.org/10.3390/s23135836 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Arpaia, Pasquale
Coyle, Damien
Esposito, Antonio
Natalizio, Angela
Parvis, Marco
Pesola, Marisa
Vallefuoco, Ersilia
Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System †
title Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System †
title_full Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System †
title_fullStr Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System †
title_full_unstemmed Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System †
title_short Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System †
title_sort paving the way for motor imagery-based tele-rehabilitation through a fully wearable bci system †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346666/
https://www.ncbi.nlm.nih.gov/pubmed/37447686
http://dx.doi.org/10.3390/s23135836
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