NDLI: Sleep-stage Characterization by Nonlinear EEG Analysis using Wavelet-based Multifractal Formalism

Content Provider	IEEE Xplore Digital Library
Author	Qianli Ma Xinbao Ning Jun Wang Jing Li
Copyright Year	2005
Description	Author affiliation: Inst. for Biomed. Electron. Eng., Nanjing Univ. (Qianli Ma; Xinbao Ning; Jun Wang; Jing Li)
Abstract	The wavelet-based multifractal formalism was applied on sleep EEG analysis and sleep-stage characterization. The subjects used in this study were randomly selected from the MIT-BIH Polysomnographic Database. The multifractal singularity spectra of sleep EEG signals were estimated, and $h_{0},$ the Holder exponent that denotes the main singular property of the signal, was extracted from the multifractal singularity spectrum and used as sleep-stage characteristic parameter. The shift of multifractal singularity spectra of different sleep stage was observed. The mean $h_{0}$ exponents increased from awake to sleep stage 1, 2, 3 and 4, but decreased during rapid eye movement (REM) sleep. Our study suggests that the $h_{0}$ exponent could be used as an important sleep stage characteristic parameter
Starting Page	4526
Ending Page	4529
File Size	216645
Page Count	4
File Format	PDF
ISBN	0780387414
DOI	10.1109/IEMBS.2005.1615475
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Wavelet analysis Fractals Biomedical measurements Wavelet transforms Acoustic measurements Sleep Databases Chaos Power generation economics
Content Type	Text
Resource Type	Article

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