Analysis of Electroencephalogram Signals in Different Sleep Stages using Detrended Fluctuation Analysis

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Author(s)

Ateke Goshvarpour 1,* Ataollah Abbasi 1 Atefeh Goshvarpour 1

1. Computational Neuroscience Laboratory, Department of Biomedical Engineering, Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2013.12.07

Received: 23 May 2013 / Revised: 2 Aug. 2013 / Accepted: 30 Aug. 2013 / Published: 8 Oct. 2013

Index Terms

Detrended Fluctuation Analysis, Electroencephalogram, Nonlinear Behavior, Scaling exponents, Sleep Stages

Abstract

Scaling behavior is an indicator of the lack of characteristic time scale, and the existence of long-range correlations related to physiological constancy preservation. To investigate the fluctuations of the sleep electroencephalogram (EEG) over various time scales during different sleep stages detrended fluctuation analysis (DFA) is studied. The sleep EEG signals for analysis were obtained from the Sleep-EDF Database available online at the PhysioBank. The DFA computations were performed in different sleep stages. The scaling behavior of these time series was investigated with detrended fluctuation analysis (window size: 50 to 500). The results show that the mean values of scaling exponents were lower in subjects during stage 4 and standard deviation of scaling exponents of stage 4 was larger than that of the other stages. In contrast, the mean value of scaling exponents of stage 2 was larger, while a small variation of scaling exponent is observed at this stage. Therefore, DFA has a more stable behavior in stage 2, whereas the random variability and unpredictable behavior of DFA can be observed in the stage 4. In conclusion, scaling exponent indices are efficacious in quantifying EEG signals in different sleep stages.

Cite This Paper

Ateke Goshvarpour, Ataollah Abbasi, Atefeh Goshvarpour,"Analysis of Electroencephalogram Signals in Different Sleep Stages using Detrended Fluctuation Analysis", IJIGSP, vol.5, no.12, pp.49-55, 2013. DOI: 10.5815/ijigsp.2013.12.07

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