Healthc Inform Res.  2010 Mar;16(1):46-51. 10.4258/hir.2010.16.1.46.

Non-linear Analysis of Single Electroencephalography (EEG) for Sleep-Related Healthcare Applications

• Lee CK
• Jo HG
• Yoo SK

• KMID: 2166565
• DOI: http://doi.org/10.4258/hir.2010.16.1.46

Abstract

OBJECTIVES
Soft-computing techniques are commonly used to detect medical phenomena and to help with clinical diagnoses and treatment. The purpose of this paper is to analyze the single electroencephalography (EEG) signal with the chaotic methods in order to identify the sleep stages. METHODS: Data acquisition (polysomnography) was performed on four healthy young adults (all males with a mean age of 27.5 years). The evaluated algorithm was designed with a correlation dimension and Lyapunov's exponent using a single EEG signal that detects differences in chaotic characteristics. RESULTS: The change of the correlation dimension and the largest Lyapunov exponent over the whole night sleep EEG was performed. The results show that the correlation dimension and largest Lyapunov exponent decreased from light sleep to deep sleep and they increased during the rapid eye movement stage. CONCLUSIONS: These results suggest that chaotic analysis may be a useful adjunct to linear (spectral) analysis for identifying sleep stages. The single EEG based nonlinear analysis is suitable for u-healthcare applications for monitoring sleep.

Keyword

Regression Analysis; Electroencephalography; Sleep Stage; Lyapunov Exponent; u-Healthcare

MeSH Terms

Delivery of Health Care
Electroencephalography
Humans
Light
Male
Regression Analysis
Sleep Stages
Sleep, REM
Young Adult

Figure

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  Figure 1 The result of correlation dimension (D2) with respect to the different sleep stages. Light sleep 1: stage 1, Light sleep 2: stage 2, Deep sleep 1: stage 3, Deep sleep 2: stage 4, REM: rapid eye movement.

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  Figure 2 The result of Lyapunov exponent (L1) with respect to the different sleep stages. Light sleep 1: stage 1, Light sleep 2: stage 2, Deep sleep 1: stage 3, Deep sleep 2: stage 4, REM: rapid eye movement.

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  Figure 3 Mean and standard deviation of D2 for wakefulness stage, sleep stage 1-4, and rapid eye movement (REM) stage for each recording sets. WA: wake, L1: light sleep1, L2: light sleep2, D1: deep sleep1, D2: deep sleep2, REM: rapid eye movement

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  Figure 4 Mean and standard deviation of L1 for wakefulness stage, sleep stage 1-4, and rapid eye movement (REM) stage for each recording sets. WA: Wake, L1: light sleep1, L2: light sleep2, D1: deep sleep1, D2: deep sleep2, REM: rapid eye movement

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