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Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia

BACKGROUND: The brain–computer interface (BCI) race at the Cybathlon championship, for people with disabilities, challenges teams (BCI researchers, developers and pilots with spinal cord injury) to control an avatar on a virtual racetrack without movement. Here we describe the training regime and re...

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Autores principales: Korik, Attila, McCreadie, Karl, McShane, Niall, Du Bois, Naomi, Khodadadzadeh, Massoud, Stow, Jacqui, McElligott, Jacinta, Carroll, Áine, Coyle, Damien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9446658/
https://www.ncbi.nlm.nih.gov/pubmed/36068570
http://dx.doi.org/10.1186/s12984-022-01073-9
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author Korik, Attila
McCreadie, Karl
McShane, Niall
Du Bois, Naomi
Khodadadzadeh, Massoud
Stow, Jacqui
McElligott, Jacinta
Carroll, Áine
Coyle, Damien
author_facet Korik, Attila
McCreadie, Karl
McShane, Niall
Du Bois, Naomi
Khodadadzadeh, Massoud
Stow, Jacqui
McElligott, Jacinta
Carroll, Áine
Coyle, Damien
author_sort Korik, Attila
collection PubMed
description BACKGROUND: The brain–computer interface (BCI) race at the Cybathlon championship, for people with disabilities, challenges teams (BCI researchers, developers and pilots with spinal cord injury) to control an avatar on a virtual racetrack without movement. Here we describe the training regime and results of the Ulster University BCI Team pilot who has tetraplegia and was trained to use an electroencephalography (EEG)-based BCI intermittently over 10 years, to compete in three Cybathlon events. METHODS: A multi-class, multiple binary classifier framework was used to decode three kinesthetically imagined movements (motor imagery of left arm, right arm, and feet), and relaxed state. Three game paradigms were used for training i.e., NeuroSensi, Triad, and Cybathlon Race: BrainDriver. An evaluation of the pilot’s performance is presented for two Cybathlon competition training periods—spanning 20 sessions over 5 weeks prior to the 2019 competition, and 25 sessions over 5 weeks in the run up to the 2020 competition. RESULTS: Having participated in BCI training in 2009 and competed in Cybathlon 2016, the experienced pilot achieved high two-class accuracy on all class pairs when training began in 2019 (decoding accuracy > 90%, resulting in efficient NeuroSensi and Triad game control). The BrainDriver performance (i.e., Cybathlon race completion time) improved significantly during the training period, leading up to the competition day, ranging from 274–156 s (255 ± 24 s to 191 ± 14 s mean ± std), over 17 days (10 sessions) in 2019, and from 230–168 s (214 ± 14 s to 181 ± 4 s), over 18 days (13 sessions) in 2020. However, on both competition occasions, towards the race date, the performance deteriorated significantly. CONCLUSIONS: The training regime and framework applied were highly effective in achieving competitive race completion times. The BCI framework did not cope with significant deviation in electroencephalography (EEG) observed in the sessions occurring shortly before and during the race day. Changes in cognitive state as a result of stress, arousal level, and fatigue, associated with the competition challenge and performance pressure, were likely contributing factors to the non-stationary effects that resulted in the BCI and pilot achieving suboptimal performance on race day. Trial registration not registered SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12984-022-01073-9.
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spelling pubmed-94466582022-09-06 Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia Korik, Attila McCreadie, Karl McShane, Niall Du Bois, Naomi Khodadadzadeh, Massoud Stow, Jacqui McElligott, Jacinta Carroll, Áine Coyle, Damien J Neuroeng Rehabil Research BACKGROUND: The brain–computer interface (BCI) race at the Cybathlon championship, for people with disabilities, challenges teams (BCI researchers, developers and pilots with spinal cord injury) to control an avatar on a virtual racetrack without movement. Here we describe the training regime and results of the Ulster University BCI Team pilot who has tetraplegia and was trained to use an electroencephalography (EEG)-based BCI intermittently over 10 years, to compete in three Cybathlon events. METHODS: A multi-class, multiple binary classifier framework was used to decode three kinesthetically imagined movements (motor imagery of left arm, right arm, and feet), and relaxed state. Three game paradigms were used for training i.e., NeuroSensi, Triad, and Cybathlon Race: BrainDriver. An evaluation of the pilot’s performance is presented for two Cybathlon competition training periods—spanning 20 sessions over 5 weeks prior to the 2019 competition, and 25 sessions over 5 weeks in the run up to the 2020 competition. RESULTS: Having participated in BCI training in 2009 and competed in Cybathlon 2016, the experienced pilot achieved high two-class accuracy on all class pairs when training began in 2019 (decoding accuracy > 90%, resulting in efficient NeuroSensi and Triad game control). The BrainDriver performance (i.e., Cybathlon race completion time) improved significantly during the training period, leading up to the competition day, ranging from 274–156 s (255 ± 24 s to 191 ± 14 s mean ± std), over 17 days (10 sessions) in 2019, and from 230–168 s (214 ± 14 s to 181 ± 4 s), over 18 days (13 sessions) in 2020. However, on both competition occasions, towards the race date, the performance deteriorated significantly. CONCLUSIONS: The training regime and framework applied were highly effective in achieving competitive race completion times. The BCI framework did not cope with significant deviation in electroencephalography (EEG) observed in the sessions occurring shortly before and during the race day. Changes in cognitive state as a result of stress, arousal level, and fatigue, associated with the competition challenge and performance pressure, were likely contributing factors to the non-stationary effects that resulted in the BCI and pilot achieving suboptimal performance on race day. Trial registration not registered SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12984-022-01073-9. BioMed Central 2022-09-06 /pmc/articles/PMC9446658/ /pubmed/36068570 http://dx.doi.org/10.1186/s12984-022-01073-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Korik, Attila
McCreadie, Karl
McShane, Niall
Du Bois, Naomi
Khodadadzadeh, Massoud
Stow, Jacqui
McElligott, Jacinta
Carroll, Áine
Coyle, Damien
Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
title Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
title_full Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
title_fullStr Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
title_full_unstemmed Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
title_short Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
title_sort competing at the cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9446658/
https://www.ncbi.nlm.nih.gov/pubmed/36068570
http://dx.doi.org/10.1186/s12984-022-01073-9
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