nm000139
BNCI 2014-001 Motor Imagery dataset
EEG
The BNCI 2014-001 Motor Imagery dataset is a widely-used benchmark for brain-computer interface research, comprising EEG recordings from 9 healthy subjects performing four-class motor imagery tasks (left hand, right hand, feet, and tongue). Each subject completed two sessions with 6 runs per session, yielding 200 training and 240 test trials. The dataset features 22 EEG channels plus 3 EOG channels (25 total) sampled at 250 Hz with minimal preprocessing (bandpass filtering 0.05-200 Hz), making it a standard resource for evaluating multi-class motor imagery classification algorithms and cross-session transfer learning approaches.
- Participants
- 9
- Channels
- 22 (10-10)
- Citations
- 90
- HED
- v8.4.0
- Size
- 1.38 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026