BNCI 2015-012 PASS2D P300 dataset
This dataset comprises a 9-class auditory event-related potential (ERP) paradigm designed for brain-computer interface (BCI) applications, specifically a predictive text entry system called PASS2D. Ten healthy participants performed a single session including calibration and online spelling tasks using two-dimensional auditory stimuli varying in pitch and spatial direction. The dataset includes 63-channel EEG recordings preprocessed with bandpass filtering, downsampling to 100 Hz, and artifact rejection, achieving an average spelling speed of 0.8 characters per minute.
AI-generated description, may include mistakesLoading demographics…
Coming soon. Per-file data-quality summaries are precomputed by the NEMAR processing pipeline. The static aggregate is on the way — tracked at nemar-cli#511.