nm000151
Motor imagery dataset for three imaginary states of the same upper extremity
EEG
- Size
- 3.20 GB
- Updated
- May 16, 2026
Discover datasets
100 results for "neuromotor interfaces" · page 9 of 10 · ranked by relevance
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- nm000321
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study Q)
EEGBigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, annotated with target and non-target event labels for machine learning applications. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.
- Size
- 1.09 GB
- Updated
- Jun 3, 2026
- ds006839
EEG recordings during sham neurofeedback in virtual reality
EEG- Participants
- 36
- nm000323
Lee et al. 2019 (ERP) — EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy
EEGThis EEG dataset comprises recordings from 54 healthy participants performing a P300-based copy-spelling task using a 36-symbol row-column speller paradigm. The dataset includes 62 EEG channels and 4 EMG channels sampled at 1000 Hz, with offline training and online test phases designed to investigate BCI illiteracy. Data are provided in BIDS format with HED event annotations and represent a benchmark resource for evaluating brain-computer interface performance across different user populations.
- Size
- 38.6 GB
- Updated
- Jun 3, 2026
- nm000340
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study J)
EEGBigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 16-channel EEG with a standard 10-20 montage and are organized in BIDS format with HED event annotations for standardized analysis and machine learning applications.
- Size
- 426 MB
- Updated
- Jun 3, 2026
- nm000212
BNCI 2015-007 Motion VEP (mVEP) Speller dataset
EEGThis dataset comprises EEG recordings from 16 healthy participants performing motion visually evoked potential (mVEP) speller tasks using three different paradigm variants: overt gaze-directed, covert attention-based, and foveal motion center stimulation. The study investigates gaze-independent brain-computer interface communication through P300-based visual speller applications with two-level hierarchical selection from 6 groups/symbols per level, including copy-spelling and free-spelling conditions.
- Size
- 1.27 GB
- Updated
- Jun 3, 2026
- ds004473
sEEG Forced Two-Choice Task
iEEG MRI- Participants
- 8
- ds003739
Perturbed beam-walking task
EEG- Participants
- 30
- ds004784
Phantom EEG Dataset with Motion, Muscle, and Eye Artifacts and Example Scripts
EEG- Participants
- 1
- nm000175
fNIRS Finger Tapping
NIRSfNIRS finger tapping with lateralized auditory cues. 5 subjects, 56 NIRS channels (8 sources, 16 detectors incl. 8 short), NIRx NIRScout, 7.8 Hz, SNIRF format. 3 conditions x 30 trials. Zenodo DOI: 10.5281/zenodo.6575155
- Size
- 47.4 MB
- Updated
- Jun 1, 2026