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Poster De Conférence Année : 2023

DUPE MIBCI: Database with User’s Profile and EEG signals for Motor Imagery Brain Computer Interface research

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 in total 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.

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hal-04125666 , version 1 (12-06-2023)

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  • HAL Id : hal-04125666 , version 1

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Pauline Dreyer, Aline Roc, Sébastien Rimbert, Fabien Lotte, Léa Pillette. DUPE MIBCI: Database with User’s Profile and EEG signals for Motor Imagery Brain Computer Interface research. BCI 2023 - 10th International BCI Meeting Balancing Innovation and Translation, Jun 2023, Bruxelles, Belgium. ⟨hal-04125666⟩
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