A model for obstructive sleep apnea detection using a multi-layer feed-forward neural network based on electrocardiogram, pulse oxygen saturation, and body mass index.

Journal: Sleep & breathing = Schlaf & Atmung
Published Date: Dec 1, 2021

Abstract

PURPOSE: To develop and evaluate a model for obstructive sleep apnea (OSA) detection using an artificial neural network (ANN) based on the combined features of body mass index (BMI), electrocardiogram (ECG), and pulse oxygen saturation (SpO2).

Authors

  • Zufei Li
    Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China.
  • Yanru Li
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China.
  • Guoqiang Zhao
    The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Xiaoqing Zhang
    a College of Information Science and Technology , Donghua University , Shanghai , China.
  • Wen Xu
    Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang 441000 China.
  • Demin Han
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China. deminhan_ent@hotmail.com.

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