Approximate Entropy in the Electroencephalogram during Wake and Sleep

Author:

Burioka Naoto1,Miyata Masanori1,Cornélissen Germaine2,Halberg Franz2,Takeshima Takao3,Kaplan Daniel T.4,Suyama Hisashi1,Endo Masanori1,Maegaki Yoshihiro4,Nomura Takashi3,Tomita Yutaka5,Nakashima Kenji3,Shimizu Eiji1

Affiliation:

1. Division of Medical Oncology and Molecular Respirology, Faculty of Medicine, Tottori University, Yonago, Japan Halberg Chronobiology Center, University of Minnesota, Minneapolis, Minnesota, USA

2. Division of Neurology, Institute of Neurological Sciences, Faculty of Medicine, Tottori University, Yonago, Japan

3. Department of Mathematics and Computer Science, Macalester College, St. Paul, Minnesota

4. Division of Child Neurology, Institute of Neurological Sciences, Faculty of Medicine, Tottori University, Yonago, Japan

5. Division of Health Care, Faculty of Medicine, Tottori University, Yonago, Japan

Abstract

Entropy measurement can discriminate among complex systems, including deterministic, stochastic and composite systems. We evaluated the changes of approximate entropy (ApEn) in signals of the electroencephalogram (EEG) during sleep. EEG signals were recorded from eight healthy volunteers during nightly sleep. We estimated the values of ApEn in EEG signals in each sleep stage. The ApEn values for EEG signals (mean ± SD) were 0.896 ± 0.264 during eyes-closed waking state, 0.738 ± 0.089 during Stage I, 0.615 ± 0.107 during Stage II, 0.487 ± 0.101 during Stage III, 0.397 ± 0.078 during Stage IV and 0.789 ± 0.182 during REM sleep. The ApEn values were found to differ with statistical significance among the six different stages of consciousness (ANOVA, p<0.001). ApEn of EEG was statistically significantly lower during Stage IV and higher during wake and REM sleep. We conclude that ApEn measurement can be useful to estimate sleep stages and the complexity in brain activity.

Publisher

SAGE Publications

Subject

Clinical Neurology,Neurology,General Medicine

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