Estimation of a priori probabilities of sleep stages: A cycle-based approach

This paper presents a model for the estimation of a priori probabilities of sleep epoch classes based on the epoch location in a sleep cycle. These probabilities are used as additional features for sleep stage classification based on the analysis of respiratory effort. The model was validated with d...

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Bibliographic Details
Published inConference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.) Vol. 2017; pp. 3745 - 3748
Main Authors Tataraidze, Alexander, Anishchenko, Lesya, Korostovtseva, Lyudmila, Bochkarev, Mikhail, Sviryaev, Yurii, Ivashov, Sergey
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.07.2017
Subjects
Computational modeling
Estimation
Feature extraction
Indexes
Mathematical model
Sleep apnea
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ISSN1557-170X
DOI10.1109/EMBC.2017.8037671

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Summary:This paper presents a model for the estimation of a priori probabilities of sleep epoch classes based on the epoch location in a sleep cycle. These probabilities are used as additional features for sleep stage classification based on the analysis of respiratory effort. The model was validated with data of 685 subjects selected from the Sleep Heart Health Study dataset. The model improves a base algorithm by 8 percent points and demonstrates Cohen's kappa of 0.56 ± 0.12. Our results will contribute to the development of screening tools for unobtrusive sleep structure estimation.
ISSN:1557-170X
DOI:10.1109/EMBC.2017.8037671