Automatic sleep scoring: A deep learning architecture for multi-modality time series.

Journal: Journal of neuroscience methods
Published Date: Nov 4, 2020

Abstract

BACKGROUND: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This paper aims to develop a versatile deep-learning architecture to automate sleep scoring using raw polysomnography recordings.

Authors

  • Rui Yan
    Neuromorphic Computing Research Center, College of Computer Science, Sichuan University, Chengdu, 610065, China. Electronic address: ryan@scu.edu.cn.
  • Fan Li
    Department of Instrument Science and Engineering, School of SEIEE, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Dong Dong Zhou
    School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024, Dalian, China; Faculty of Information Technology, University of Jyväskylä, 40014, Jyväskylä, Finland.
  • Tapani Ristaniemi
  • Fengyu Cong
    School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024, Dalian, China; Faculty of Information Technology, University of Jyväskylä, 40014, Jyväskylä, Finland; School of Artificial Intelligence, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024, Dalian, China; Key Laboratory of Integrated Circuit and Biomedical Electronic System, Liaoning Province. Dalian University of Technology, 116024, Dalian, China.

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