Feasibility Analysis of Symbolic Representation for Single-Channel EEG-Based Sleep Stages

Sleep screening based on the construction of sleep stages is one of the major tool for the assessment of sleep quality and early detection of sleep-related disorders. Due to the inherent variability such as inter-users anatomical variability and the inter-systems differences, representation learning...

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Bibliographic Details
Published in2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) Vol. 2021; pp. 5928 - 5931
Main Authors Chen, Zheng, Gao, Pei, Huang, Ming, Ono, Naoaki, Altaf-Ul-Amin, MD, Kanaya, Shigehiko
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.11.2021
Subjects
Brain modeling
Electroencephalography
Feasibility Studies
Feature extraction
Physiology
Representation learning
Sleep
Sleep Quality
Sleep Stages
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Summary:Sleep screening based on the construction of sleep stages is one of the major tool for the assessment of sleep quality and early detection of sleep-related disorders. Due to the inherent variability such as inter-users anatomical variability and the inter-systems differences, representation learning of sleep stages in order to obtain the stable and reliable characteristics is runoff for downstream tasks in sleep science. In this paper, we investigated feasibility of the EEG-based symbolic representation for sleep stages. By combining the Latent Dirichlet Allocation topic model and comparing with different feature extraction methods, the work proved the feasibility of multi-topics representation for sleep stages and physiological signals.
ISSN:2694-0604
DOI:10.1109/EMBC46164.2021.9629652