Large EEG Database with User Profiles for Motor Imagery BCI Research

Dreyer Pauline from the Centre National de la Recherche Scientifique shares a database of electroencephalographic signals from 87 human participants, with more than 20,800 trials representing about 70 hours of recording. The data was collected during brain-computer interface experiments at Inria Bordeaux sud-ouest, France, and organized into three datasets (A, B, and C) following a protocol for right and left hand motor imagery tasks. It includes user performance, demographics, personality, cognitive profiles, and experimental codes executed in the OpenViBE platform.

Use Cases

• Study relationships between BCI users' profiles and their performance based on provided demographic, personality, and cognitive data.
• Analyze how EEG signal properties vary for different users' profiles and motor imagery tasks using the recorded signals.
• Design cross-user BCI machine learning algorithms leveraging the data from 87 participants.
• Incorporate users' profile information into the design of EEG signal classification algorithms.

Strengths

• Contains signals from 87 human participants, a relatively large sample for BCI research.
• Includes more than 20,800 trials representing about 70 hours of recording.
• Provides detailed user profile information including demographics, personality, and cognitive data alongside performance metrics.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Centre National de la Recherche Scientifique

Collection Method

Recorded during BCI experiments using a g.USBAmp device sampled at 512 Hz and processed online with OpenViBE.

Geography

Inria Bordeaux sud-ouest, France