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

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 variat ion 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.