Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot.
Cybathlon
brain computer interface
electroencephalography
motor assistance
tetraplegia
Journal
Frontiers in human neuroscience
ISSN: 1662-5161
Titre abrégé: Front Hum Neurosci
Pays: Switzerland
ID NLM: 101477954
Informations de publication
Date de publication:
2021
2021
Historique:
received:
31
12
2020
accepted:
17
05
2021
entrez:
2
7
2021
pubmed:
3
7
2021
medline:
3
7
2021
Statut:
epublish
Résumé
Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms (
Identifiants
pubmed: 34211380
doi: 10.3389/fnhum.2021.648275
pmc: PMC8239283
doi:
Types de publication
Journal Article
Langues
eng
Pagination
648275Informations de copyright
Copyright © 2021 Robinson, Chouhan, Mihelj, Kratka, Debraine, Wenderoth, Guan and Lehner.
Déclaration de conflit d'intérêts
BrainProducts has provided EEG equipment and Rehaklinik Zihlschlacht has financially supported the CYBATHLON BCI team for participating in the CYBATHLON 2020 event. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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