BNCI 2015-012 PASS2D P300 dataset
This dataset comprises preprocessed EEG recordings from a novel 9-class auditory event-related potential (ERP) paradigm designed for brain-computer interface (BCI) applications. Ten healthy participants performed a spelling task using a predictive text entry system (PASS2D) that exploited spatial auditory stimuli varying in pitch and direction. The study demonstrates competitive performance for auditory ERP-based BCIs, achieving 0.8 characters per minute and 3.4 bits/min information transfer rate, with potential applications for communication in patients with severe motor impairment.
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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.