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Automatic detection of sleep spindles with the use of STFT, EMD and DWT methods

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Abstract

Sleep staging is a significant process to diagnose sleep disorders. Like other stages, several parameters are required for the determination of N-REM2 stage. Sleep spindles (SSs) are among them. In this study, a methodology was presented to automatically determine starting and ending positions of SSs. To accomplish this, short-time Fourier transform–artificial neural networks (STFT–ANN), empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods were used. Two considerable methods which were determination envelope and thresholding of the decomposed signals by EMD and DWT were also presented in this study. A database from the EEG signals of nine healthy subjects—which consisted of 100 epochs including 172 SSs in total—was prepared. According to the test results, the highest sensitivity rate was obtained as 100 and 99.42 % for EMD and DWT methods. However, the sensitivity rate for the STFT–ANN method was recorded as 55.93 %. The results indicated that the EMD method could be confidently used in the automatic determination of SSs. Thanks to this study, the sleep experts will be able to reliably find out the epochs with SSs and also know the places of SSs in these epochs, automatically. Another important point of the study was that the sleep staging process—tiring, time-consuming and high fallibility for the experts—could be performed in less time and at higher accuracy rates.

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Acknowledgments

This study is supported by the Scientific and Technological Research Council of Turkey (Project No. 113E591) and the Scientific Research Projects Coordination Unit of Selcuk University.

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Authors and Affiliations

  1. Electrical and Electronics Engineering Department, Selcuk University, 42072, Konya, Turkey

    Cüneyt Yücelbaş & Seral Özşen

  2. Computer Engineering Department, Selcuk University, Konya, Turkey

    Şule Yücelbaş & Gülay Tezel

  3. Sleep Laboratory, Faculty of Medicine, Necmettin Erbakan University, Konya, Turkey

    Serkan Küççüktürk & Şebnem Yosunkaya

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  1. Cüneyt Yücelbaş
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  2. Şule Yücelbaş
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  3. Seral Özşen
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  5. Serkan Küççüktürk
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Correspondence to Cüneyt Yücelbaş.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national Non-invasive Clinical Research Medical Ethics Review Board and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Yücelbaş, C., Yücelbaş, Ş., Özşen, S. et al. Automatic detection of sleep spindles with the use of STFT, EMD and DWT methods. Neural Comput & Applic 29, 17–33 (2018). https://doi.org/10.1007/s00521-016-2445-y

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  • DOI: https://doi.org/10.1007/s00521-016-2445-y

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