MSleepNet: A Semi-Supervision-Based Multiview Hybrid Neural Network for Simultaneous Sleep Arousal and Sleep Stage Detection-Reference-Cited by-同舟云学术

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MSleepNet: A Semi-Supervision-Based Multiview Hybrid Neural Network for Simultaneous Sleep Arousal and Sleep Stage Detection

Published:2024 Issue: Volume:73 Page:1-9
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Liu Hongmei¹^ORCID,Zhang Haibo²^ORCID,Li Baozhu³^ORCID,Yu Xinge⁴^ORCID,Zhang Yuan¹^ORCID,Penzel Thomas⁵^ORCID

Affiliation:

1. College of Electronic and Information Engineering, Southwest University, Chongqing, China

2. School of Computing, University of Otago, Dunedin, New Zealand

3. Internet of Things Smart City Innovation Platform, Zhuhai Fudan Innovation Institute, Zhuhai, China

4. Department of Biomedical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong

5. Interdisciplinary Sleep Medicine Center, Charité—Universitätsmedizin, Berlin, Germany

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10379111.pdf?arnumber=10379111

Reference51 articles.

1. Profiles of sleep changes during the COVID‐19 pandemic: Demographic, behavioural and psychological factors

2. A Hybrid Transformer Model for Obstructive Sleep Apnea Detection Based on Self-Attention Mechanism Using Single-Lead ECG

3. The effects of COVID-19 stay-at-home order on sleep, health, and working patterns: a survey study of US health care workers

4. Automated Sleep Stage Scoring Using Time-Frequency Spectra Convolution Neural Network

5. The nature of arousal in sleep

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