發(fā)布時(shí)間：2018-03-04 19:32

  本文選題：阿爾茨海默病　切入點(diǎn)：腦電圖　出處：《生物醫(yī)學(xué)工程學(xué)雜志》2014年04期 　論文類型：期刊論文

【摘要】：子波熵是衡量信號(hào)復(fù)雜程度的指標(biāo),本文采用連續(xù)子變換的方法對(duì)輕、中、重度阿爾茨海默病(AD)患者及正常對(duì)照老年人的腦電(EEG)信號(hào)進(jìn)行子波分析,根據(jù)子波系數(shù)計(jì)算EEG信號(hào)的子波功率譜分布,提取描述EEG信號(hào)復(fù)雜程度的定量指標(biāo)——子波熵。對(duì)輕、中、重度AD患者和正常對(duì)照的自發(fā)狀態(tài)下EEG信號(hào)的子波熵值進(jìn)行比較,并將子波熵值與MMSE進(jìn)行相關(guān)性分析。結(jié)果顯示,輕、中、重度AD組和正常對(duì)照組之間EEG信號(hào)的子波熵存在顯著差異(P0.01)。組間比較顯示輕、中、重度AD患者EEG信號(hào)的子波熵均低于正常對(duì)照,差異具有統(tǒng)計(jì)學(xué)意義(P0.05)。這與AD患者EEG信號(hào)的功率譜分布單一有關(guān)。進(jìn)一步研究表明EEG信號(hào)的子波熵與其MMSE評(píng)分均存在顯著相關(guān)(r=0.601~0.799,P0.01)。子波熵可以作為描述EEG信號(hào)復(fù)雜程度的定量指標(biāo),子波熵值有可能成為AD診斷和病情評(píng)估的電生理指標(biāo)。
[Abstract]:Wavelet entropy is an index to measure the signal complexity. In this paper, wavelet analysis of EEG (EGG) signals in patients with mild, moderate and severe Alzheimer's disease (ADD) and normal controls was carried out by means of continuous subtransform. The wavelet power spectrum distribution of EEG signal was calculated according to wavelet coefficients, and wavelet entropy, a quantitative index describing the complexity of EEG signal, was extracted. The wavelet entropy values of EEG signal in spontaneous state of light, moderate and severe AD patients and normal controls were compared. The correlation between wavelet entropy and MMSE was analyzed. The results showed that there were significant differences in wavelet entropy of EEG signal between mild, moderate and severe AD groups and normal controls. The wavelet entropy of EEG signal in patients with severe AD was lower than that in normal controls. The difference is statistically significant (P 0.05), which is related to the single distribution of power spectrum of EEG signal in AD patients. Further study shows that there is a significant correlation between the wavelet entropy of EEG signal and its MMSE score. The wavelet entropy can be used to describe the complexity of EEG signal. Quantitative indicators of degree, Wavelet entropy may be an electrophysiological index for diagnosis and assessment of AD.
【作者單位】： 天津市人民醫(yī)院神經(jīng)內(nèi)科;天津醫(yī)科大學(xué)總醫(yī)院神經(jīng)內(nèi)科;
【基金】：天津市衛(wèi)生局科技基金資助項(xiàng)目(2011KY21) 天津市自然科學(xué)基金資助項(xiàng)目(14JCYBJC27000)
【分類號(hào)】：R749.16

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1 張美云;阿爾茨海默病腦電信號(hào)多尺度時(shí)空定量特征研究[D];天津醫(yī)科大學(xué);2012年

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