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Automated Sleep Staging Using Detrended Fluctuation Analysis of Sleep EEG

  • Conference paper
Soft Computing Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 195))

Abstract

An accurate sleep staging is crucial for the treatment of sleep disorders. Recently some studies demonstrated that the long range correlations of many physiological signals measured during sleep show some variations during the different sleep stages. In this study, detrended fluctuation analysis (DFA) is used to study the electroencephalogram (EEG) signal autocorrelation during different sleep stages. A classification of these stages is then made by introducing the calculated DFA power law exponents to a K-Nearest Neighbor classifier. Our study reveals that a 2-D feature space composed of the DFA power law exponents of both the filtered THETA and BETA brain waves resulted in a classification accuracy of 94.44%, 91.66% and 83.33% for the wake, non-rapid eye movement and rapid eye movement stages, respectively. We conclude that it might be possible to build an automated sleep assessment system based on DFA analysis of the sleep EEG signal.

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Author information

Authors and Affiliations

  1. Department of Systems and Biomedical Engineering, Cairo University, Giza, Egypt

    Amr F. Farag, Shereen M. El-Metwally & Ahmed Abdel Aal Morsy

  2. Department of Biomedical Engineering, Shorouk Higher institute of Engineering, EL-Shorouk, Egypt

    Amr F. Farag

Authors
  1. Amr F. Farag
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  2. Shereen M. El-Metwally
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  3. Ahmed Abdel Aal Morsy
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Corresponding author

Correspondence to Amr F. Farag .

Editor information

Editors and Affiliations

  1. , Department of Automation & Applied Infor, Aurel Vlaicu University of Arad, Blvd. Revolutiei 77, Arad, 310130, Romania

    Valentina Emilia Balas

  2. , Institute of Intelligent Engineering, Óbuda University, Bécsi út 96/b, Budapest, 1034, Hungary

    János Fodor

  3. Dept. Measurement &, Information Systems, Technical University Budapest, Magyar tudósok körutja 2, Budapest, 1521, Hungary

    Annamária R. Várkonyi-Kóczy

  4. , Department of Informatics, University of Szeged, Arpad ter 2., Szeged, 6720, Hungary

    Joszef Dombi

  5. , School of Electrical and Information, University of South Australia, 5095, Adelaide, Australia

    Lakhmi C. Jain

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© 2013 Springer-Verlag Berlin Heidelberg

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Farag, A.F., El-Metwally, S.M., Morsy, A.A.A. (2013). Automated Sleep Staging Using Detrended Fluctuation Analysis of Sleep EEG. In: Balas, V., Fodor, J., Várkonyi-Kóczy, A., Dombi, J., Jain, L. (eds) Soft Computing Applications. Advances in Intelligent Systems and Computing, vol 195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33941-7_44

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  • DOI: https://doi.org/10.1007/978-3-642-33941-7_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33940-0

  • Online ISBN: 978-3-642-33941-7

  • eBook Packages: EngineeringEngineering (R0)

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