nm000177
Multi-session longitudinal motor imagery EEG dataset (Kumar et al. 2024)
EEG
This dataset comprises longitudinal motor imagery EEG recordings from 18 BCI-naive subjects across six sessions (one offline, five online), designed to study transfer learning and skill acquisition in brain-computer interfaces (BCIs). It compares two domain adaptation frameworks—Generic Recentering and Personally Assisted Recentering—for calibration-free BCI training using left/right hand motor imagery with visual feedback. Data were collected at 512 Hz with 22 EEG channels and analyzed using Riemannian geometry-based classifiers.
- Participants
- 18
- Channels
- 22 (10-10)
- Citations
- 49
- HED
- v8.4.0
- Size
- 14.4 GB
- Version
- v1.0.4
- Updated
- Aug 20, 2026