Abstract
Background: The brain-computer interface (BCI) race at the Cybathlon championship for athletes 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 is tetraplegic and has 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) (left (L) and right (R) arm and feet (F)) as well as relax state (X). Three games paradigms were used for training i.e., NeuroSensi, Triad, and Cybathlon: 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 274s - 156s (255±24s to 191±14s mean±std), over 17 days (10 sessions) in 2019, and from 230s - 168s (214±14s to 181±4s), 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. Stress, arousal level and fatigue, associated with the competition challenge and performance pressure resulting in cognitive state changes, were likely contributing factors to the nonstationary effects that resulted in the BCI and pilot achieving suboptimal performance on race day. Trial registration: not registered
A Link between the Increase in Electroencephalographic Coherence and Performance Improvement in Operating a Brain-Computer Interface
