Nakanishi2015 – SSVEP Nakanishi 2015 dataset
This dataset comprises 12-class steady-state visual evoked potential (SSVEP) recordings acquired from 10 healthy subjects using 8 EEG channels during a brain-computer interface task. The data were collected to evaluate and compare canonical correlation analysis (CCA)-based methods for SSVEP detection. The dataset includes preprocessed EEG signals with joint frequency-phase modulated visual stimuli ranging from 9.25 to 14.75 Hz. In the reference study, CCA-based methods achieved 92.78% classification accuracy with an information transfer rate of 91.68 bits/min using a combination approach.
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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.