Automated multi-model deep neural network for sleep stage scoring with unfiltered clinical data.

Journal: Sleep & breathing = Schlaf & Atmung
Published Date:

Abstract

PURPOSE: To develop an automated framework for sleep stage scoring from PSG via a deep neural network.

Authors

  • Xiaoqing Zhang
    a College of Information Science and Technology , Donghua University , Shanghai , China.
  • Mingkai Xu
    Department of Electronic Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
  • Yanru Li
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China.
  • Minmin Su
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China.
  • Ziyao Xu
    Department of Electronic Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
  • Chunyan Wang
    School of Food Science, Henan Institute of Science and Technology, Xinxiang, 453003 China.
  • Dan Kang
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China.
  • Hongguang Li
    a School of Information Science and Technology , Beijing University of Chemical Technology , Beijing , China.
  • Xin Mu
    Department of Plastic Surgery Peninsula Health Melbourne Victoria Australia.
  • Xiu Ding
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China.
  • Wen Xu
    Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang 441000 China.
  • Xingjun Wang
    Department of Electronic Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China. wangxingjun@tsinghua.edu.cn.
  • Demin Han
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China. deminhan_ent@hotmail.com.