CLEEGN: A Convolutional Neural Network for Plug-and-Play Automatic EEG Reconstruction

arXiv:2210.05988v2 Announce Type: replace-cross
Abstract: Human electroencephalography (EEG) is a brain monitoring modality that senses cortical neuroelectrophysiological activity in high-temporal resolution. One of the greatest challenges posed in applications of EEG is the unstable signal quality susceptible to inevitable artifacts during recordings. To date, most existing techniques for EEG artifact removal and reconstruction are applicable to offline analysis solely, or require individualized training data to facilitate online reconstruction. We have proposed CLEEGN, a novel convolutional neural network for plug-and-play automatic …

abstract applications artifact arxiv brain challenges convolutional neural network cs.lg eeg eess.sp human monitoring network neural network q-bio.nc quality signal temporal type