A large EEG dataset for studying cross-session variability in motor imagery brain-computer interface

In building a practical and robust brain-computer interface (BCI), the classification of motor imagery (MI) from electroencephalography (EEG) across multiple days is a long-standing challenge due to the large variability of the EEG signals. We collected a large dataset of MI from 5 different days wi...

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Detalles Bibliográficos
Autores principales: Ma, Jun, Yang, Banghua, Qiu, Wenzheng, Li, Yunzhe, Gao, Shouwei, Xia, Xinxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436944/
https://www.ncbi.nlm.nih.gov/pubmed/36050394
http://dx.doi.org/10.1038/s41597-022-01647-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436944/
https://www.ncbi.nlm.nih.gov/pubmed/36050394
http://dx.doi.org/10.1038/s41597-022-01647-1

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