ds004306
MultisensoryDataset
EEG
- Participants
- 12
Discover datasets
100 results for "multimodal physiological recording" · page 9 of 10 · ranked by relevance
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- nm000271
Chang et al. 2025 — A multi-paradigm EEG dataset for studying upper limb rehabilitation exercises (Lanzhou Jiaotong University)
EEGA multi-paradigm EEG dataset comprising scalp electroencephalography recordings from 28 participants performing and imagining upper-limb rehabilitation exercises. This dataset is designed to support research on motor imagery and rehabilitation brain-computer interfaces (BCI) for upper-limb motor function recovery and assessment.
- Citations
- 1
- Size
- 3.46 GB
- Updated
- Jun 17, 2026
- ds006890
Longitudinal Multitask Wireless ECoG Data from Two Fully Implanted Macaca fuscata
iEEG…wireless subdural ECoG, iEEG, Macaca fuscata, BIDS-compliant dataset, longitudinal recordings, task…
- Participants
- 2
- ds006945
Structural MRI and fMRI of Participants Performing Kinesthetic Motor Imagery of Walking vs. Standing While Viewing a First‑Person Exoskeleton Video Stimulus (11 Stop‑Walk‑Stop Cycles)
EEG MRI…Rest ------------------------------------------------------------------------------- This dataset includes multimodal neuroimaging recordings from five participants performing kinesthetic…
- Participants
- 5
- on001810
EEG study of the attentional blink; before, during, and after transcranial Direct Current Stimulation (tDCS)
EEG FUNC…Concurrent tDCS-EEG -------- Recording EEG during tDCS introduces some problems, most importantly…
- Size
- 110 GB
- Updated
- Jun 20, 2026
- on003739
Perturbed beam-walking task
EEG[ — Four-class ASME BCI: investigation of the feasibility and comparison of two strategies for multiclassing
EEGThis dataset comprises EEG recordings from 15 healthy subjects performing an auditory brain-computer interface task based on the ASME (Auditory Stream segregation Multiclass ERP) paradigm. The study investigates two strategies for achieving four-class classification: ASME-4stream (four independent streams with single target stimuli) and ASME-2stream (two streams with dual target stimuli each). EEG data were recorded at 1000 Hz from 64 channels and analyzed using event-related potential methods and linear discriminant analysis classification, achieving accuracies of 83% and 86% respectively.
- Citations
- 4
- Size
- 13.9 GB
- Updated
- Jun 2, 2026
- ds007609
Resting-State EEG and Trait Anxiety
EEG…https://doi.org/10.1162/IMAG.a.44 Recording --------- EEG was recorded…
- Participants
- 51
- on003708
Basis profile curve identification to understand electrical stimulation effects in human brain networks
iEEG…This dataset contains intracranial EEG recordings from one patient during single pulse…
- Size
- 620 MB
- Updated
- Jun 22, 2026