A large EEG database with users' profile information for motor imagery brain-computer interface research.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
05 09 2023
05 09 2023
Historique:
received:
25
01
2023
accepted:
04
08
2023
medline:
7
9
2023
pubmed:
6
9
2023
entrez:
5
9
2023
Statut:
epublish
Résumé
We present and share a large database containing electroencephalographic signals from 87 human participants, collected during a single day of brain-computer interface (BCI) experiments, organized into 3 datasets (A, B, and C) that were all recorded using the same protocol: right and left hand motor imagery (MI). Each session contains 240 trials (120 per class), which represents more than 20,800 trials, or approximately 70 hours of recording time. It includes the performance of the associated BCI users, detailed information about the demographics, personality profile as well as some cognitive traits and the experimental instructions and codes (executed in the open-source platform OpenViBE). Such database could prove useful for various studies, including but not limited to: (1) studying the relationships between BCI users' profiles and their BCI performances, (2) studying how EEG signals properties varies for different users' profiles and MI tasks, (3) using the large number of participants to design cross-user BCI machine learning algorithms or (4) incorporating users' profile information into the design of EEG signal classification algorithms.
Identifiants
pubmed: 37670009
doi: 10.1038/s41597-023-02445-z
pii: 10.1038/s41597-023-02445-z
pmc: PMC10480224
doi:
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
580Informations de copyright
© 2023. Springer Nature Limited.
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