Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study.

Journal: Journal of medical Internet research
Published Date: Feb 10, 2023

Abstract

BACKGROUND: Most existing automated sleep staging methods rely on multimodal data, and scoring a specific epoch requires not only the current epoch but also a sequence of consecutive epochs that precede and follow the epoch.

Authors

  • Shahab Haghayegh
    Department of Biomedical Engineering Cockrell School of Engineering, The University of Texas at Austin, USA. Electronic address: shahab@utexas.edu.
  • Kun Hu
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China.
  • Katie Stone
    California Pacific Medical Center Research Institute, San Francisco, CA, United States.
  • Susan Redline
    Department of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University Boston, MA.
  • Eva Schernhammer
    Harvard Medical School, Boston, MA, United States.

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