【摘要】：隨著生活步驟的加快和工作壓力的加大,越來越多的人開始感受到睡眠問題帶來的困擾。睡眠質(zhì)量關(guān)系著身體健康與和工作效率,睡眠分期結(jié)果是衡量睡眠質(zhì)量的重要指標(biāo)和診治睡眠障礙性疾病的重要途徑。EEG是腦部電位活動的反映,通過對睡眠EEG的研究可以獲得睡眠時腦部活動概況,所以通過睡眠EEG的分期研究對改善睡眠質(zhì)量或者診治睡眠障礙性疾病有很大的意義。 EEG是非線性信號,EEG的非線性分析是目前睡眠研究的熱點。ECG也是非線性信號,本文通過基于睡眠EEG、ECG的符號轉(zhuǎn)移熵的睡眠分析方法和基于EEG的熵產(chǎn)生率即平均能量耗散的睡眠分析方法來進(jìn)行清醒期和非快速眼動睡眠Ⅰ期的分期研究。研究發(fā)現(xiàn):符號轉(zhuǎn)移熵、平均能量耗散很好的體現(xiàn)了睡眠狀態(tài)的變化,在清醒期較大,在非快速眼動睡眠Ⅰ期較小,并經(jīng)過差異顯著性檢驗和多樣本驗證。 經(jīng)分析認(rèn)為隨著睡眠加深,身體單元不斷耦合,因此符號轉(zhuǎn)移熵變小;隨著睡眠加深,神經(jīng)細(xì)胞突觸連接強(qiáng)度減弱,減弱了基因表達(dá)的失衡和無序性趨勢,因此熵產(chǎn)生率減小�？梢妼嶒灲Y(jié)果與理論分析是相符合的。因此符號轉(zhuǎn)移熵、平均能量耗散可以作為睡眠自動化分期參數(shù)補(bǔ)充到睡眠分期研究中來,在臨床上可以通過多參數(shù)分析,達(dá)到睡眠分期的更高的準(zhǔn)確性。
[Abstract]:As life steps accelerate and work stress increases, more and more people begin to experience sleep problems. Sleep quality is related to physical health and work efficiency. Sleep staging is an important index to measure sleep quality and an important way to diagnose and treat sleep disorders. EEG is a reflection of brain potential activity. A study of sleep EEG provides an overview of brain activity during sleep. Therefore, it is of great significance to improve the quality of sleep or to diagnose and treat sleep disorders by stages of sleep EEG. EEG is the nonlinear analysis of nonlinear signal, which is a hot spot in sleep research. EEG is also a nonlinear signal. In this paper, sleep analysis method based on symbol transfer entropy of sleep EEG,ECG and sleep analysis method of average energy dissipation based on entropy production rate of EEG were used to study the stages of waking and non-REM sleep stages. It was found that the change of sleep state was well reflected in the symbol transfer entropy and the average energy dissipation. It was larger in awake stage and smaller in non-REM sleep stage I, and was verified by difference significance test and multi-sample test. It is concluded that with the deepening of sleep, the body units are coupled continuously, so the symbol transfer entropy becomes smaller; with the deepening of sleep, the synaptic connection intensity of nerve cells weakens, which weakens the imbalance and disordered tendency of gene expression, so the entropy production rate decreases. It can be seen that the experimental results are in agreement with the theoretical analysis. So the symbol transfer entropy and the average energy dissipation can be used as sleep automatic staging parameters to supplement the sleep stage study, and the higher accuracy of sleep staging can be achieved through multi-parameter analysis in clinic.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：R318

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 吳鋒,俞夢孫,張宏金,金璋瑞;心率變化特征與睡眠分期耦合關(guān)系研究[J];北京生物醫(yī)學(xué)工程;2003年03期

2 解幸幸;李舒;張春利;李建康;;Lempel-Ziv復(fù)雜度在非線性檢測中的應(yīng)用研究[J];復(fù)雜系統(tǒng)與復(fù)雜性科學(xué);2005年03期

3 劉建平，，鄭崇勛;腦電信號的分析──一種探索大腦功能狀態(tài)及活動規(guī)律的途徑[J];國外醫(yī)學(xué).生物醫(yī)學(xué)工程分冊;1995年05期

4 李勇;腦電信號現(xiàn)代分析方法的發(fā)展[J];國外醫(yī)學(xué)(生物醫(yī)學(xué)工程分冊);1996年04期

5 謝松云;張振中;楊金孝;張坤;;腦電信號的若干處理方法研究與評價[J];計算機(jī)仿真;2007年02期

6 和衛(wèi)星;陳曉平;邵s

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