A Systematic Review of Literature on Automated Sleep Scoring-Reference-Cited by-同舟云学术

A Systematic Review of Literature on Automated Sleep Scoring

Published:2022 Issue: Volume:10 Page:79419-79443
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Alsolai Hadeel¹^ORCID,Qureshi Shahnawaz²^ORCID,Iqbal Syed Muhammad Zeeshan³^ORCID,Vanichayobon Sirirut⁴,Henesey Lawrence Edward⁵^ORCID,Lindley Craig⁶,Karrila Seppo⁷^ORCID

Affiliation:

1. Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

2. Department of Computer Science, National University of Computing and Emerging Sciences, Fasialabad, Pakistan

3. Research and Development, BrightWare LLC, Riyadh, Saudi Arabia

4. Department of Computer Science, Prince of Songkla University, Songkhla, Thailand

5. Blekinge Institute of Technology, Karlshamn, Sweden

6. CSIRO Data 61, Pullenvale, QLD, Australia

7. Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Makham Tia, Muang, Thailand

Funder

Princess Nourah bint Abdulrahman University Researchers Supporting

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09841539.pdf?arnumber=9841539

Reference162 articles.

1. The hypnospectrogram: An EEG power spectrum based means to concurrently overview the macroscopic and microscopic architecture of human sleep

2. EEG functional connectivity in term age extremely low birth weight infants

3. Topographic analysis of coherence and propagation of EEG activity during sleep and wakefulness

4. Automatic detection and classification of sleep stages by multichannel EEG signal modeling

5. Modeling the time-varying microstructure of simulated sleep EEG spindles using time-frequency analysis methods

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