Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram.

Journal: Physiological measurement
Published Date: Dec 21, 2018

Abstract

OBJECTIVE: This study classifies sleep stages from a single lead electrocardiogram (ECG) using beat detection, cardiorespiratory coupling in the time-frequency domain and a deep convolutional neural network (CNN).

Authors

  • Qiao Li
    Department of Biomedical Informatics, Emory University, Atlanta, GA, United States of America.
  • Qichen Li
  • Chengyu Liu
    Department of General Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Supreeth P Shashikumar
  • Shamim Nemati
    Department of Biomedical Informatics, Emory School of Medicine, Atlanta, GA, USA.
  • Gari D Clifford
    Department of Biomedical Informatics, Emory University, Atlanta, GA, United States.

Keywords

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