BNCI 2014-008 P300 dataset (ALS patients)
This dataset comprises EEG recordings from 8 patients with amyotrophic lateral sclerosis (ALS) performing a P300-based brain-computer interface (BCI) speller task. Participants completed a copy-spelling paradigm using a 6×6 matrix with row-column intensification, generating 35 trials per subject across a single session. The preprocessed data, acquired at 256 Hz from 8 electrodes using active g.Ladybird sensors, demonstrates high classification accuracy (97.5%) and represents a valuable resource for developing and benchmarking BCI systems for communication assistance in severely paralyzed populations.
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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.