Detrended fluctuation analysis of EEG in sleep apnea using MIT/BIH polysomnography data

Jong Min Lee; Dae Jin Kim; In Young Kim; Kwang Suk Park; Sun I Kim

doi:10.1016/s0010-4825(01)00031-2

Detrended fluctuation analysis of EEG in sleep apnea using MIT/BIH polysomnography data

Comput Biol Med. 2002 Jan;32(1):37-47. doi: 10.1016/s0010-4825(01)00031-2.

Authors

Jong Min Lee¹, Dae Jin Kim, In Young Kim, Kwang Suk Park, Sun I Kim

Affiliation

¹ Department of Biomedical Engineering, College of Medicine, Hanyang University Haengdang-dong, Seongdong-ku, 133-791, Seoul, South Korea.

PMID: 11738639
DOI: 10.1016/s0010-4825(01)00031-2

Abstract

A number of natural time series including electroencephalogram (EEG) show highly non-stationary characteristics in their behavior. We analyzed the EEG in sleep apnea that typically exhibits non-stationarity and long-range correlations by calculating its scaling exponents. Scaling exponents of the EEG dynamics are obtained by analyzing its fluctuation with detrended fluctuation analysis (DFA), which is suitable for non-stationary time series. We found the mean scaling exponents of EEG is discriminated according to Non-REM, REM (Rapid Eye Movement) and waken stage, and gradually increased from stage 1 to stage 2, 3 and 4.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Cerebral Cortex / physiopathology
Humans
Mathematical Computing
Nonlinear Dynamics
Polysomnography*
Signal Processing, Computer-Assisted*
Sleep Apnea Syndromes / diagnosis*
Sleep Apnea Syndromes / physiopathology
Sleep Stages / physiology