Hybrid EEG-fNIRS MI dataset for ICH from Shi et al 2025
- Participants
- 37
- Channels
- 32 (10-10)
- HED
- v8.4.0
- Size
- 2.59 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
100 results for "mobile neuroimaging" · page 5 of 10 · ranked by relevance
[-naive subjects acquired across 6 sessions (1 offline + 5 online) to investigate transfer learning and domain adaptation for calibration-free BCI training. Subjects performed left/right hand motor imagery tasks with visual feedback using 22 EEG channels sampled at 512 Hz. The dataset compares Generic Recentering (unsupervised) and Personally Assisted Recentering (supervised) domain adaptation frameworks, with features extracted as covariance matrices and classified using Riemannian geometry-based methods.
[ performing 2-class hand motor imagery tasks (left and right hand grasping) across 1-6 sessions per subject. With 32-channel EEG recordings at 256 Hz and approximately 3,330 trials, this dataset supports the development and evaluation of BCI systems for clinical stroke rehabilitation.
…with applications in AR/VR, mobile interfaces, and accessibility. Key research objectives…
This dataset consists of 8 participants completing functional localizer and movie-viewing…
This dataset comprises multimodal physiological recordings from 86 participants during resting state and a digit span working memory task. It includes 64-channel EEG, electrocardiography, photoplethysmography, pupillometry, and behavioral performance data. The dataset enables investigation of neural and peripheral physiological correlates of cognitive load, working memory capacity, and cognitive overload detection across fine temporal scales.
…The entire experiment was mobile and the participant wore a fanny pack…