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Cyclic Alternating Patterns in Normal Sleep and Insomnia: Structure and Content Differences

失眠症 脑电图 背景(考古学) 听力学 心理学 近似熵 睡眠(系统调用) 神经科学 医学 精神科 认知心理学 计算机科学 模式识别(心理学) 生物 古生物学 操作系统
作者
Ioanna Chouvarda,Martín O. Méndez,Valentina Rosso,Anna Maria Bianchi,Liborio Parrino,Andrea Grassi,Mario Giovanni Terzano,S. Cerutti,Nicos Maglaveras
出处
期刊:IEEE Transactions on Neural Systems and Rehabilitation Engineering [Institute of Electrical and Electronics Engineers]
卷期号:20 (5): 642-652 被引量:38
标识
DOI:10.1109/tnsre.2012.2208984
摘要

This work aims to investigate new markers for the quantitative characterization of insomnia, in the context of sleep microstructure, as expressed by cyclic alternating pattern (CAP) sleep. The study group includes 11 subjects with normal sleep and 10 subjects with diagnosed primary insomnia. Differences between normal sleepers and insomniacs are investigated, in terms of dynamics and content of CAP events. The overall rate of CAP and of different phases is considered. The dynamic in the structure and alternation of CAP events is further studied in different scales by use of wavelet analysis, and calculation of energy/entropy features. The content of CAP events is studied in terms of electroencephalography (EEG) complexity analysis for the different types of events. Statistically significant differences are highlighted, both in structure and content. Besides confirming the increase in CAP rate, main findings regarding the microstructure difference in insomnia include: 1) as regards the deep sleep building phases, more irregular activation-deactivation patterns, with bigger deactivation time, i.e., distance between consecutive activation events, and appearing with higher EEG complexity in deactivation, and 2) a bigger duration of desynchronisation phases, with increased EEG complexity and more irregular patterns. This analysis extends previous findings on the relation between CAPrate increase and sleep instability mechanisms, proposing specific features of CAP that seem to play a role in insomnia (as consistently presented via classification analysis). This opens new perspectives for the understanding of the role of CAP in the quantitative characterization of sleep and its disorders.

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