Detecting the origin of multifractality of EEG signals with sleep apnea syndrome using multifractal detrended fluctuation analysis method

Abstract

In this paper we try to evaluate the multifractality displayed by the EEG signals obtained from subjects with sleep apnea syndrome. The Multifractal Detrended Fluctuation Analysis (MF-DFA) shows that the EEG signals have different degree of multifractality and we suspected this variety is due to various stages of sleep. In an attempt to identify the origin of multifractality we extend our study and produce surrogate data set. Applying MF-DFA method on the surrogate data set we find that this multifractality is caused by both the long-range correlation appearing due to large and small fluctuations and broad probability distribution. However the first one has more influence on the multifractality of the EEG signals during sleep.