AMRI 16-N-0031 sleep1
[-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.
[ recordings of 23 healthy…
[ GuttmannFlury2025-MI ==================== Eye-BCI multimodal MI/ME dataset from Guttmann-Flury…
…nm000310) GuttmannFlury2025-SSVEP ======================= Eye-BCI multimodal SSVEP dataset from Guttmann-Flury et…