Wavelet Entropy Analysis of Electroencephalogram Signals During Wake and Different Sleep Stages in Patients with Insomnia Disorder

IF 3 2区医学 Q2 CLINICAL NEUROLOGY Nature and Science of Sleep Pub Date : 2024-04-06 DOI:10.2147/nss.s452017

Qian Yang, Lingfeng Liu, Jing Wang, Ying Zhang, Nan Jiang, Meiyun Zhang

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Abstract

Objective: To investigate the changes in the wavelet entropy during wake and different sleep stages in patients with insomnia disorder.
Methods: Sixteen patients with insomnia disorder and sixteen normal controls were enrolled. They underwent scale assessment and two consecutive nights of polysomnography (PSG). Wavelet entropy analysis of electroencephalogram (EEG) signals recorded from all participants in the two groups was performed. The changes in the integral wavelet entropy (En) and individual-scale wavelet entropy (En(a)) during wake and different sleep stages in the two groups were observed, and the differences between the two groups were compared.
Results: The insomnia disorder group exhibited lower En during the wake stage, and higher En during the N3 stage compared with the normal control group (all P < 0.001). In terms of En(a), patients with insomnia disorder exhibited lower En(a) in the β and α frequency bands during the wake stage compared with normal controls (β band, P < 0.01; α band, P < 0.001), whereas they showed higher En(a) in the β and α frequency bands during the N3 stage than normal controls (β band, P < 0.001; α band, P < 0.001).
Conclusion: Wavelet entropy can reflect the changes in the complexity of EEG signals during wake and different sleep stages in patients with insomnia disorder, which provides a new method and insights about understanding of pathophysiological mechanisms of insomnia disorder. Wavelet entropy provides an objective indicator for assessing sleep quality.

Keywords: insomnia disorder, sleep stages, wavelet entropy, polysomnography

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失眠症患者清醒和不同睡眠阶段脑电信号的小波熵分析

目的：研究失眠症患者在清醒和不同睡眠阶段的小波熵变化：研究失眠症患者在清醒和不同睡眠阶段的小波熵变化：方法：选取 16 名失眠症患者和 16 名正常对照者。他们接受了量表评估和连续两晚的多导睡眠图（PSG）检查。对两组所有参与者记录的脑电图（EEG）信号进行小波熵分析。结果显示，失眠症组在清醒时和不同睡眠阶段的小波熵积分（En）和个体尺度小波熵（En(a)）的变化，并比较了两组之间的差异：结果：与正常对照组相比，失眠症组在觉醒阶段的En较低，而在N3阶段的En较高（均为P < 0.001）。在En(a)方面，与正常对照组相比，失眠症患者在觉醒阶段的β和α频段的En(a)较低（β频段，P < 0.01；α频段，P < 0.001），而在N3阶段的β和α频段的En(a)较高（β频段，P < 0.001；α频段，P < 0.001）：小波熵能反映失眠症患者清醒和不同睡眠阶段脑电信号复杂性的变化，为了解失眠症的病理生理机制提供了一种新的方法和见解。小波熵为评估睡眠质量提供了一个客观指标。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature and Science of Sleep Neuroscience-Behavioral Neuroscience

CiteScore

5.70

自引率

5.90%

发文量

245

审稿时长

16 weeks

期刊介绍： Nature and Science of Sleep is an international, peer-reviewed, open access journal covering all aspects of sleep science and sleep medicine, including the neurophysiology and functions of sleep, the genetics of sleep, sleep and society, biological rhythms, dreaming, sleep disorders and therapy, and strategies to optimize healthy sleep. Specific topics covered in the journal include: The functions of sleep in humans and other animals Physiological and neurophysiological changes with sleep The genetics of sleep and sleep differences The neurotransmitters, receptors and pathways involved in controlling both sleep and wakefulness Behavioral and pharmacological interventions aimed at improving sleep, and improving wakefulness Sleep changes with development and with age Sleep and reproduction (e.g., changes across the menstrual cycle, with pregnancy and menopause) The science and nature of dreams Sleep disorders Impact of sleep and sleep disorders on health, daytime function and quality of life Sleep problems secondary to clinical disorders Interaction of society with sleep (e.g., consequences of shift work, occupational health, public health) The microbiome and sleep Chronotherapy Impact of circadian rhythms on sleep, physiology, cognition and health Mechanisms controlling circadian rhythms, centrally and peripherally Impact of circadian rhythm disruptions (including night shift work, jet lag and social jet lag) on sleep, physiology, cognition and health Behavioral and pharmacological interventions aimed at reducing adverse effects of circadian-related sleep disruption Assessment of technologies and biomarkers for measuring sleep and/or circadian rhythms Epigenetic markers of sleep or circadian disruption.