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A novel end-to-end 1D-ResCNN model to remove artifact from EEG signals

  • Published:2020-09 Issue: Volume:404 Page:108-121
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Sun Weitong,Su Yuping,Wu Xia,Wu Xiaojun

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Fund for the Central Universities

China Postdoctoral Science Foundation

Shaanxi Natural Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference53 articles.

1. Removal artifacts from eeg signal using independent component analysis and principal component analysis;Turnip,2014

2. Atlas of EEG in critical care;Hirsch,2011

3. The utility of ambulatory electroencephalography in routine clinical practice: a critical review.;Seneviratne;Epilepsy Res.,2013

4. Artifact suppression from eeg signals using data adaptive time domain filtering;Molla;Neurocomputing,2012

5. Manifestation of ocular-muscle EMG contamination in human intracranial recordings;Kovach;Neuroimage,2011
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