nm000107
FRL Wrist Control: Wrist Movement Decoding from Surface Electromyography
EMG Zarr verified
NEMAR Dataset nm000107: wrist - Wrist movement control from EMG
- Participants
- 100
- Size
- 24.9 GB
- Version
- v2.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "electrical stimulation mapping" · page 9 of 10 · ranked by relevance
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- nm000152
Upper-limb elbow-centered motor imagery dataset (10 classes)
EEG Zarr verifiedThis dataset comprises EEG recordings from 12 healthy participants performing upper-limb motor imagery tasks centered on elbow movements. Participants executed kinesthetic imagery of nine goal-directed tasks (drawer opening, soup preparation, weight lifting, door opening, plate cleaning, combing, pizza cutting, and pick-and-place operations) plus rest, cued by visual stimuli. The dataset contains 330 trials recorded at 1000 Hz using 17 EEG channels and is designed for brain-computer interface (BCI) research and motor imagery classification studies.
- Participants
- 12
- Channels
- 17 (other)
- Citations
- 13
- HED
- v8.4.0
- Size
- 4.18 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on006897
No effect of rhythmic visual stimulation on experimental pain perception
EEG…No effect of rhythmic visual stimulation on experimental pain perception. *[Journal Name…
- Participants
- 41
- Channels
- 63 (10-10)
- Citations
- 2
- Size
- 24.3 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on005343
Gaffrey Lab Infant Microstates and Attention
EEG…channel HydroCel Geodesic Sensor Net (Electrical Geodesics, Eugene, OR). Impedances were maintained…
- Participants
- 43
- Channels
- 129 (egi-geodesic)
- Citations
- 1
- Size
- 26.5 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000271
Chang et al. 2025 — A multi-paradigm EEG dataset for studying upper limb rehabilitation exercises (Lanzhou Jiaotong University)
EEGThis dataset contains scalp EEG recordings from 28 participants performing or imagining upper-limb rehabilitation exercises under a multi-paradigm protocol. It was designed to support research on motor-imagery-based brain–computer interfaces (BCI) for upper-limb rehabilitation. The data have been converted to BIDS format from the original dataset published by Chang et al. (2025).
- Participants
- 28
- Channels
- 59 (10-10)
- Citations
- 3
- HED
- v8.4.0
- Size
- 47.1 GB
- Version
- v1.0.5
- Updated
- Aug 20, 2026
- on002791
DataSet1
EEGThis dataset is a mirror of OpenNeuro ds002791, containing EEG recordings and associated metadata. The dataset includes raw EEG data in standard formats (.eeg, .vhdr, .vmrk) along with BIDS-compliant documentation and participant information in TSV format.
- Participants
- 23
- Channels
- 256 (egi-geodesic)
- Citations
- 4
- Size
- 47.1 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on002724
A dataset recorded during development of an affective brain-computer music interface: training sessions
EEGThis dataset contains electroencephalogram (EEG), galvanic skin response (GSR), and electrocardiogram (ECG) recordings from 17 healthy participants during an affective music brain-computer interface training study. Participants listened to 40-second music clips (20s per emotional state) designed to induce specific emotional states across three sessions, with self-reported valence and arousal ratings. The data supports the development and validation of music-based brain-computer interfaces for monitoring and inducing affective states. This is the training session dataset; two additional datasets cover system calibration and online real-time control phases.
- Participants
- 10
- Channels
- 32 (10-10)
- Size
- 8.52 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on005280
223 By BP
EEG…Each participant underwent stimulation in 3 blocks, with each block comprising 10…
- Participants
- 223
- Channels
- 64 (10-10)
- Size
- 137 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000233
BCI Competition 2020 Track 4 — Upper-limb grasping motor imagery
EEGBCIComp2020UpperLimb is a preprocessed EEG dataset from BCI Competition 2020 Track 4 containing motor imagery recordings of three grasping tasks (cylindrical, spherical, lumbrical) from 15 healthy subjects across three sessions. The dataset comprises 60-channel EEG data sampled at 250 Hz with 450 trials per subject (150 trials per session across 3 sessions), designed to evaluate session-to-session transfer learning in brain-computer interface applications. Data were preprocessed with 60 Hz notch filtering and cue-aligned epoching, with the 4-second motor imagery window extracted for analysis.
- Participants
- 14
- Channels
- 60 (10-10)
- Citations
- 73
- HED
- v8.4.0
- Size
- 2.76 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on005292
142 by Biosemi
EEG…Each participant underwent stimulation in 3 blocks, with each block comprising 10…
- Participants
- 142
- Channels
- 64 (10-10)
- Size
- 116 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026