{"title":"失眠症患者清醒和不同睡眠阶段脑电信号的小波熵分析","authors":"Qian Yang, Lingfeng Liu, Jing Wang, Ying Zhang, Nan Jiang, Meiyun Zhang","doi":"10.2147/nss.s452017","DOIUrl":null,"url":null,"abstract":"<strong>Objective:</strong> To investigate the changes in the wavelet entropy during wake and different sleep stages in patients with insomnia disorder.<br/><strong>Methods:</strong> 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.<br/><strong>Results:</strong> 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 <em>P</em> < 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, <em>P</em> < 0.01; α band, <em>P</em> < 0.001), whereas they showed higher En(a) in the β and α frequency bands during the N3 stage than normal controls (β band, <em>P</em> < 0.001; α band, <em>P</em> < 0.001).<br/><strong>Conclusion:</strong> 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.<br/><br/><strong>Keywords:</strong> insomnia disorder, sleep stages, wavelet entropy, polysomnography<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wavelet Entropy Analysis of Electroencephalogram Signals During Wake and Different Sleep Stages in Patients with Insomnia Disorder\",\"authors\":\"Qian Yang, Lingfeng Liu, Jing Wang, Ying Zhang, Nan Jiang, Meiyun Zhang\",\"doi\":\"10.2147/nss.s452017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Objective:</strong> To investigate the changes in the wavelet entropy during wake and different sleep stages in patients with insomnia disorder.<br/><strong>Methods:</strong> 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.<br/><strong>Results:</strong> 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 <em>P</em> < 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, <em>P</em> < 0.01; α band, <em>P</em> < 0.001), whereas they showed higher En(a) in the β and α frequency bands during the N3 stage than normal controls (β band, <em>P</em> < 0.001; α band, <em>P</em> < 0.001).<br/><strong>Conclusion:</strong> 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.<br/><br/><strong>Keywords:</strong> insomnia disorder, sleep stages, wavelet entropy, polysomnography<br/>\",\"PeriodicalId\":18896,\"journal\":{\"name\":\"Nature and Science of Sleep\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature and Science of Sleep\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/nss.s452017\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature and Science of Sleep","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/nss.s452017","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Wavelet Entropy Analysis of Electroencephalogram Signals During Wake and Different Sleep Stages in Patients with Insomnia Disorder
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.
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.