Sleep stage classification for managing nocturnal enuresis through effective configuration

Sangyeop Lee, Junhyung Moon, Taeho Lee, Saewon Kye, Kyoungwoo Lee, Yong Seung Lee, Seung Chul Shin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Various studies have examined the quality of one'sasleep and further investigated several sleep disorders. In thoseainvestigations, accurately classifying one's sleep into the standardized sleep stages is important. The conventional classification heavily depends on the manual examination of each expert on one's physiological signals during the sleep. Therefore, various automatic classification models have been proposed using the machine learning. Although they properly classify the sleep stages on average, there have been few investigations to specifically improve the classification accuracy of certain stages. Accurate determination of several stages considerably correlating with a disorder gives us a more effective hint to conquer the disorder. Accordingly, we propose a configured classification model focusing on the interesting sleep stages related to a challenging sleep disorder, the nocturnal enuresis. We consider the deterministic physiological signals of the interesting stages when training the classifiers. Further, the proposed system utilizes recurrent neural network to effectively learn the sequential feature of the physiological data. Our proposed system achieves the classification accuracy by 83.6% over the data. In particular, technique presents up to 15.5% higher accuracy to differentiate interesting stages than the support vector machine approach for the nocturnal enuresis.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2832-2837
Number of pages6
ISBN (Electronic)9781538616451
DOIs
Publication statusPublished - 2017 Nov 27
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: 2017 Oct 52017 Oct 8

Publication series

Name2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
CountryCanada
CityBanff
Period17/10/517/10/8

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

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  • Cite this

    Lee, S., Moon, J., Lee, T., Kye, S., Lee, K., Lee, Y. S., & Shin, S. C. (2017). Sleep stage classification for managing nocturnal enuresis through effective configuration. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 (pp. 2832-2837). (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2017.8123056