دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia
المؤلفون: Attila Korik, Karl McCreadie, Niall McShane, Naomi Du Bois, Massoud Khodadadzadeh, Jacqui Stow, Jacinta McElligott, Áine Carroll, Damien Coyle
المصدر: Journal of NeuroEngineering and Rehabilitation, Vol 19, Iss 1, Pp 1-22 (2022)
بيانات النشر: BMC, 2022.
سنة النشر: 2022
المجموعة: LCC:Neurosciences. Biological psychiatry. Neuropsychiatry
مصطلحات موضوعية: Brain–computer interface (BCI), Motor imagery, Electroencephalography (EEG), Competition, Tetraplegia, Long-term training, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
الوصف: Abstract 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
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1743-0003
العلاقة: https://doaj.org/toc/1743-0003Test
DOI: 10.1186/s12984-022-01073-9
الوصول الحر: https://doaj.org/article/6b559598a20442dea745c0361f19627dTest
رقم الانضمام: edsdoj.6b559598a20442dea745c0361f19627d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17430003
DOI:10.1186/s12984-022-01073-9