Characterizing Sleep Stages by the Fractal Dimensions of Electroencephalograms

Sy-Sang Liaw and Jiann-Yeu Chen
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Sy-Sang Liaw: Department of Physics, National Chung Hsing University, Taiwan
Jiann-Yeu Chen: Research Center for Sustainable Energy and Nanotechnology, National Chung Hsing University, Taiwan

Biostatistics and Biometrics Open Access Journal, 2017, vol. 2, issue 2, 41-47

Abstract: Fourier analysis has shown that human electroencephalography (EEG) signals mainly consist of frequencies below 80 Hz. Waves with a frequency below 13Hz are dominant during sleep. Here we find that the fractal dimensions of sleep EEG results in a frequency range of 2Hz to 13Hz have potential to be used as a continuous parameter to characterize sleep status. Our results show that during sleep, the fractal dimension is high during REM stage and decreases with subsequent sleep stages according to the standard scheme [1]. The lowest value of the fractal dimension for any subject’s sleep EEG occurs at N3 (deep sleep).

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:2:y:2017:i:2:p:41-47

DOI: 10.19080/BBOAJ.2017.02.555584

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