本文選題：老年癡呆 + 輕度認(rèn)知障礙　； 參考：《燕山大學(xué)》2013年碩士論文

【摘要】：老年性癡呆是一種常見的功能性精神疾病，，隨著社會老齡化的到來，老年性癡呆疾病已經(jīng)給很多家庭帶來沉重的負(fù)擔(dān)，也越來越受到社會的重視。然而，當(dāng)前對于這種疾病確切的病因和發(fā)病機(jī)制尚不清楚，且老年性癡呆前期的癥狀不明顯，目前只有通過在腦皮質(zhì)區(qū)域中發(fā)現(xiàn)廣泛存在的老年斑及神經(jīng)纖維纏結(jié)才能確診，而確診之后，病人已經(jīng)處于較嚴(yán)重的疾病狀態(tài)。大腦是老年癡呆的發(fā)病部位，由于功能性的變化要早于器質(zhì)性變化，所以前期通過功能性診斷對于及早的發(fā)現(xiàn)和治療老年癡呆具有重要意義。腦電分析是老年性癡呆診斷的重要途徑，腦電中包含了認(rèn)知和其它腦功能方面的豐富信息，我們可以通過研究腦電信號來揭示老年性癡呆疾病發(fā)作的生理機(jī)制，并采用腦電信號分析做為老年癡呆的診斷依據(jù)。 本文采用全局同步指數(shù)方法和平行因子分析方法首次分別對輕度認(rèn)知障礙患者和正常對照組進(jìn)行分析。全局同步指數(shù)側(cè)重于大腦的同步性，它可以綜合整個腦區(qū)計算同時記錄的多變量時間序列，結(jié)合所有特征值得到一個同步指數(shù)，根據(jù)其大小來判斷同步性大小。與其他的同步算法相比，這種方法整合信息的能力更強(qiáng)，同時還據(jù)有靈敏度高、計算誤差相對小和時間穩(wěn)定性強(qiáng)等特性。因此可以將全局同步指數(shù)應(yīng)用到復(fù)雜的、多維的、不穩(wěn)定的系統(tǒng)中。平行因子分析是將連續(xù)小波變換得到的三維張量數(shù)據(jù)降維分解成時間域、頻率域和空間域上的二維信息，然后利用統(tǒng)計方法分別揭示時域、頻域和空間域上的腦電信號特征。這種方法對于多通道腦電信號的時間、空間和頻率分解具有唯一性，能夠準(zhǔn)確提取出腦電信號中包含的信息。 分析結(jié)果顯示，經(jīng)全局同步指數(shù)方法分析后，輕度認(rèn)知障礙患者在δ，α和β3頻帶處的同步指數(shù)與對照組的同步指數(shù)有顯著性差異，而且在這三個頻帶處的同步指數(shù)與癥狀的嚴(yán)重程度顯著相關(guān)。經(jīng)平行因子分析后，與對照組相比輕度認(rèn)知障礙患者的優(yōu)勢節(jié)律顯著降低，對應(yīng)的能量大小也有所下降。
[Abstract]:Alzheimer's disease (AD) is a common functional mental disease. With the coming of aging society, Alzheimer's disease has brought heavy burden to many families and has been paid more and more attention by the society. However, the exact etiology and pathogenesis of the disease are not clear, and the symptoms of Alzheimer's disease are not obvious. It is only through the discovery of widespread senile plaques and neurofibrillary tangles in the cortical area of the brain that the diagnosis can be confirmed. After the diagnosis, the patient has been in a more serious state of disease. The brain is the site of Alzheimer's disease, because the functional changes are earlier than the organic changes, so the early functional diagnosis is of great significance for the early detection and treatment of Alzheimer's disease. EEG analysis is an important approach to the diagnosis of Alzheimer's disease. EEG contains rich information in cognitive and other brain functions. We can reveal the physiological mechanism of Alzheimer's disease by studying EEG. EEG analysis was used as the basis for the diagnosis of senile dementia. The global synchronous index method and parallel factor analysis method were used to analyze the patients with mild cognitive impairment and the normal control group for the first time. The global synchronization index focuses on the synchronicity of the brain. It can synthesize the whole brain region to calculate the multivariable time series recorded simultaneously, and combine all the eigenvalues to obtain a synchronization index, which can be used to judge the synchronicity. Compared with other synchronization algorithms, this method is more capable of integrating information, and has the characteristics of high sensitivity, relatively small calculation error and strong time stability. Therefore, the global synchronization index can be applied to complex, multidimensional, unstable systems. Parallel factor analysis (PFA) decomposes 3D Zhang Liang data obtained by continuous wavelet transform into two dimensional information in time domain, frequency domain and spatial domain, and then uses statistical methods to reveal EEG characteristics in time domain, frequency domain and spatial domain, respectively. This method is unique for the decomposition of time, space and frequency of multichannel EEG signals, and can extract the information contained in EEG signals accurately. The results showed that there was a significant difference between the synchro index at 未, 偽 and 尾 3 bands in mild cognitive impairment patients and the control group after global synchronization index analysis. And the synchronization index at these three bands was significantly correlated with the severity of the symptoms. After parallel factor analysis, compared with the control group, the dominant rhythm of patients with mild cognitive impairment decreased significantly, and the corresponding energy decreased.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TN911.6;R749.16

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