on004362
EEG Motor Movement/Imagery Dataset
EEG
Imported from OpenNeuro ds004362
- Participants
- 109
- Channels
- 64 (10-10)
- Citations
- 99
- HED
- v8.1.0
- Size
- 11.1 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
Showing 10 of 754 datasets · page 68 of 76
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- nm000190
BNCI 2015-012 PASS2D P300 dataset
EEG- Participants
- 10
- Channels
- 63 (10-10)
- Citations
- 84
- HED
- v8.4.0
- Size
- 2.16 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000189
BNCI 2015-003 P300 dataset
EEG- Participants
- 10
- Channels
- 8 (10-10)
- Citations
- 81
- HED
- v8.4.0
- Size
- 20.7 MB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- nm000188
BNCI 2014-009 P300 dataset
EEG- Participants
- 10
- Channels
- 16 (10-10)
- Citations
- 79
- HED
- v8.4.0
- Size
- 70.0 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000187
BigP3BCI Study N — 9x8 dry/wet electrode comparison (8 ALS subjects)
EEG- Participants
- 8
- Channels
- 16 (10-10)
- HED
- v8.4.0
- Size
- 349 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000186
BigP3BCI Study E — 6x6 checkerboard (8 healthy subjects)
EEG- Participants
- 8
- Channels
- 16 (10-10)
- HED
- v8.4.0
- Size
- 103 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- 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
- nm000173
Motor Imagery ataset from Ofner et al 2017
EEG- Participants
- 15
- Channels
- 61 (10-05)
- Citations
- 94
- HED
- v8.4.0
- Size
- 8.54 GB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- nm000172
High-gamma dataset described in Schirrmeister et al. 2017
EEG- Participants
- 14
- Channels
- 128 (10-05)
- Citations
- 76
- HED
- v8.4.0
- Size
- 18.5 GB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- nm000171
BNCI 2014-002 Motor Imagery dataset
EEGThe 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.
- Participants
- 14
- Channels
- 15 (other)
- Citations
- 89
- HED
- v8.4.0
- Size
- 553 MB
- Version
- v1.0.2
- Updated
- Jul 10, 2026