Original paper
A convolutional neural network for steady state visual evoked potential classification under ambulatory environment
Abstract
The robust analysis of neural signals is a challenging problem. Here, we contribute a convolutional neural network (CNN) for the robust classification of a steady-state visual evoked potentials (SSVEPs) paradigm. We measure electroencephalogram (EEG)-based SSVEPs for a brain-controlled exoskeleton under ambulatory conditions in which numerous artifacts may deteriorate decoding. The proposed CNN is shown to achieve reliable performance under...
Paper Details
Title
A convolutional neural network for steady state visual evoked potential classification under ambulatory environment
Published Date
Feb 22, 2017
Journal
Volume
12
Issue
2
Pages
e0172578 - e0172578
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