nm000252 NEMAR-native dataset
Imagined speech EEG dataset — long words condition (Nguyen et al. 2017)
This dataset comprises EEG recordings from 6 healthy participants performing imagined speech tasks with two conditions (cooperate and independent word imagery). The study employed a motor imagery paradigm with auditory and visual cues, yielding 1,200 trials that were preprocessed into 3,600 overlapping epochs (1,800 per class) recorded at 256 Hz from 64 channels. Data were analyzed using Riemannian manifold methods and relevance vector machines for brain-computer interface applications, achieving mean classification accuracy of 66.2±4.8%.
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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.