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Estimation of Sleep Stages by an Artificial Neural Network Employing EEG, EMG and EOG

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Abstract

Analysis and classification of sleep stages is essential in sleep research. In this particular study, an alternative system which estimates sleep stages of human being through a multi-layer neural network (NN) that simultaneously employs EEG, EMG and EOG. The data were recorded through polisomnography device for 7 h for each subject. These collective variant data were first grouped by an expert physician and the software of polisomnography, and then used for training and testing the proposed Artificial Neural Network (ANN). A good scoring was attained through the trained ANN, so it may be put into use in clinics where lacks of specialist physicians.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, University of Inonu, Malatya, Turkey

    M. Emin Tagluk

  2. Department of Electrical and Electronics Engineering, University of Batman, Batman, Turkey

    Necmettin Sezgin

  3. Department of Electrical and Electronics Engineering, University of Dicle, Diyarbakir, Turkey

    Mehmet Akin

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  1. M. Emin Tagluk
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  2. Necmettin Sezgin
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  3. Mehmet Akin
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Correspondence to Necmettin Sezgin.

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Tagluk, M.E., Sezgin, N. & Akin, M. Estimation of Sleep Stages by an Artificial Neural Network Employing EEG, EMG and EOG. J Med Syst 34, 717–725 (2010). https://doi.org/10.1007/s10916-009-9286-5

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  • DOI: https://doi.org/10.1007/s10916-009-9286-5

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