A Deep Neural Network for SSVEP-based Brain-Computer Interfaces. (arXiv:2011.08562v3 [cs.LG] UPDATED)

Objective: Target identification in brain-computer interface (BCI) spellers
refers to the electroencephalogram (EEG) classification for predicting the
target character that the subject intends to spell. When the visual stimulus of
each character is tagged with a distinct frequency, the EEG records
steady-state visually evoked potentials (SSVEP) whose spectrum is dominated by
the harmonics of the target frequency. In this setting, we address the target
identification and propose a novel deep neural network (DNN) architecture.
Method: The proposed DNN processes the …

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