Long-Term BCI Training of a Tetraplegic User: Adaptive Riemannian Classifiers and User Training

While often presented as promising assistive technologies for motor-impaired users, electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) remain barely used outside laboratories due to low reliability in real-life conditions. There is thus a need to design long-term reliable BCIs that...

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Detalles Bibliográficos
Autores principales: Benaroch, Camille, Sadatnejad, Khadijeh, Roc, Aline, Appriou, Aurélien, Monseigne, Thibaut, Pramij, Smeety, Mladenovic, Jelena, Pillette, Léa, Jeunet, Camille, Lotte, Fabien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Human Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012558/
https://www.ncbi.nlm.nih.gov/pubmed/33815081
http://dx.doi.org/10.3389/fnhum.2021.635653

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012558/
https://www.ncbi.nlm.nih.gov/pubmed/33815081
http://dx.doi.org/10.3389/fnhum.2021.635653

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