The extraction of motion-onset VEP BCI features based on deep learning and compressed sensing

Volume: 275, Pages: 80 - 92
Published: Jan 1, 2017
Abstract
Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong background EEG activities, and an effective approach is needed to extract the corresponding mVEP features to perform task recognition for BCI control. In the current study, we combine deep learning with compressed...
Paper Details
Title
The extraction of motion-onset VEP BCI features based on deep learning and compressed sensing
Published Date
Jan 1, 2017
Volume
275
Pages
80 - 92
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