Perdikis, Serafeim and Tonin, Luca and Saeedi, Sareh and Schneider, Christoph and Millán, José del R (2018) The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users. PLoS Biology, 16 (5). e2003787-e2003787. DOI https://doi.org/10.1371/journal.pbio.2003787
Perdikis, Serafeim and Tonin, Luca and Saeedi, Sareh and Schneider, Christoph and Millán, José del R (2018) The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users. PLoS Biology, 16 (5). e2003787-e2003787. DOI https://doi.org/10.1371/journal.pbio.2003787
Perdikis, Serafeim and Tonin, Luca and Saeedi, Sareh and Schneider, Christoph and Millán, José del R (2018) The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users. PLoS Biology, 16 (5). e2003787-e2003787. DOI https://doi.org/10.1371/journal.pbio.2003787
Abstract
This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized that, contrary to the popular trend of focusing mostly on the machine learning aspects of MI BCI training, a comprehensive mutual learning methodology that reinstates the three learning pillars (at the machine, subject, and application level) as equally significant could lead to a BCI–user symbiotic system able to succeed in real-world scenarios such as the Cybathlon event. Two severely impaired participants with chronic spinal cord injury (SCI), were trained following our mutual learning approach to control their avatar in a virtual BCI race game. The competition outcomes substantiate the effectiveness of this type of training. Most importantly, the present study is one among very few to provide multifaceted evidence on the efficacy of subject learning during BCI training. Learning correlates could be derived at all levels of the interface—application, BCI output, and electroencephalography (EEG) neuroimaging—with two end-users, sufficiently longitudinal evaluation, and, importantly, under real-world and even adverse conditions.
Item Type: | Article |
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Uncontrolled Keywords: | Humans; Quadriplegia; Learning; Brain-Computer Interfaces; Machine Learning |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 13 Feb 2019 14:09 |
Last Modified: | 30 Oct 2024 17:36 |
URI: | http://repository.essex.ac.uk/id/eprint/24055 |
Available files
Filename: The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users.pdf
Licence: Creative Commons: Attribution 3.0