nm000176
BigP3BCI Study K — 9x8 adaptive/checkerboard, 2 sessions (5 healthy subjects)
EEG
- Participants
- 5
- Channels
- 16 (10-10)
- HED
- v8.4.0
- Size
- 165 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Showing 10 of 760 datasets · page 69 of 76
The BNCI 2014-002 Motor Imagery dataset comprises EEG recordings from 14 healthy subjects performing two-class motor imagery tasks (right hand and feet imagination) in a cue-guided Graz-BCI paradigm. Data were acquired at 512 Hz using 15 EEG channels with online Butterworth filtering and Laplacian montage, yielding 160 trials per subject with continuous visual feedback. This minimally preprocessed dataset has been benchmarked for brain-computer interface applications using machine learning classifiers including random forests and regularized linear discriminant analysis.