冷執(zhí)行任務下精神分裂癥患者腦電信號非線性動力學分析
發(fā)布時間：2019-02-26 17:39
【摘要】：精神分裂癥是精神疾病中較為嚴重的一種,病因未明和癥狀復雜導致其診斷困難。目前,精神分裂癥的診斷在很大程度上依賴于精神科醫(yī)生的臨床經(jīng)驗以及國內外的疾病分類手冊(CCMD-3和DSM-IV-TR等),至今未有一種確切的客觀的診斷標準。隨著電生理學和數(shù)字信號處理技術的發(fā)展,腦電信號分析輔助精神分裂癥診斷成為國內外學者研究熱點。腦電信號是非線性的、復雜的信號,傳統(tǒng)的線性分析方法不適用于其特征分析,故本文采用非線性動力學分析精神分裂癥患者的腦電信號,尋找有效表征精神分裂癥的非線性特征,以期建立精神分裂癥診斷的一個相對客觀的標準。精神分裂癥的發(fā)病機理至今尚未清楚,但研究表明精神分類癥有多種認知障礙,而執(zhí)行功能障礙是最主要的認知障礙。執(zhí)行功能可以分為兩個方面:冷執(zhí)行功能(Cool Executive Function)和熱執(zhí)行功能(Hot Executive Function)。其中,冷執(zhí)行功能主要涉及反應抑制、注意和個體執(zhí)行任務的有效性、靈活性,體現(xiàn)被試對任務的規(guī)劃處理能力。冷執(zhí)行功能不涉及情緒喚醒的內容,較為客觀,故本文選擇冷執(zhí)行能力任務作為實驗刺激。本文分別對17名首發(fā)未服藥精神分裂癥患者與對應的17名健康正常志愿者在三種冷執(zhí)行任務(連線測驗A、連線測驗B和河內塔)狀態(tài)下采集的多導聯(lián)各波段腦電信號進行非線性動力學分析,計算其C0復雜度、分形維數(shù)和近似熵等非線性特征,分析首發(fā)精神分裂癥患者與正常人腦電信號之間的差異,進而采用統(tǒng)計學分析和支持向量機分類器(SVM)驗證其效果。結果顯示,首發(fā)精神分裂癥患者腦電信號更不規(guī)則、更復雜,在冷執(zhí)行任務,特別是連線測試B任務下,近似熵與分形維數(shù)能夠較好地揭示首發(fā)精神分裂癥患者組與健康對照組腦電信號非線性動力學特征之間的差異,而C0復雜度的表征效果并不理想。因此,通過選擇合適的非線性動力學算法分析患者在冷執(zhí)行任務狀態(tài)下的腦電信號能夠較好地、客觀地揭示精神分裂癥患者抽象的認知功能障礙,為精神分裂癥的診斷及治療提供新的客觀參考依據(jù)。
[Abstract]:Schizophrenia is one of the most serious mental diseases, which is difficult to diagnose because of unknown etiology and complicated symptoms. At present, the diagnosis of schizophrenia depends to a large extent on the clinical experience of psychiatrists and the domestic and foreign disease classification manuals (CCMD-3 and DSM-IV-TR, etc.), so far there is no definite objective diagnostic criteria. With the development of electrophysiology and digital signal processing technology, EEG analysis-assisted diagnosis of schizophrenia has become a hot research topic at home and abroad. The EEG signal is nonlinear and complex, and the traditional linear analysis method is not suitable for its characteristic analysis. Therefore, this paper uses nonlinear dynamics to analyze the EEG signal of schizophrenic patients. In order to establish a relatively objective criterion for the diagnosis of schizophrenia, we look for the nonlinear characteristics of schizophrenia. The pathogenesis of schizophrenia is still unclear, but studies have shown that there are many cognitive disorders in psychotaxonomy, and executive dysfunction is the most important cognitive disorder. The execution function can be divided into two aspects: the cold execution function (Cool Executive Function) and the hot execution function (Hot Executive Function). Among them, the cold execution function mainly involves the response inhibition, the effectiveness and flexibility of attention and individual task execution, which reflects the ability of the subjects to plan and deal with the task. Cold execution function does not involve the content of emotional arousal, so this paper chooses cold execution ability task as experimental stimulus. In this paper, 17 first-episode schizophrenic patients and 17 healthy volunteers were assigned three cold tasks (A, C), respectively. The nonlinear dynamic analysis of the multi-channel EEG signals collected under the state of connection test B and Hanoi tower was carried out, and the nonlinear characteristics such as C _ 0 complexity, fractal dimension and approximate entropy were calculated. The difference between the first-episode schizophrenic patients and normal EEG signals was analyzed, and the results were verified by statistical analysis and support vector machine classifier (SVM). The results showed that the EEG signals of the first-episode schizophrenic patients were more irregular and complex, especially in the cold task execution, especially under the B task of the wired test. Approximate entropy and fractal dimension can well reveal the difference between the first-episode schizophrenia group and the healthy control group in nonlinear dynamic characteristics of EEG signal, but the representation effect of C _ 0 complexity is not ideal. Therefore, by choosing a suitable nonlinear dynamic algorithm to analyze the EEG signals in the cold task state, we can objectively reveal the abstract cognitive dysfunction in schizophrenic patients. To provide a new objective reference for the diagnosis and treatment of schizophrenia.
【學位授予單位】：新鄉(xiāng)醫(yī)學院
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：R749.3
本文編號：2430993
[Abstract]:Schizophrenia is one of the most serious mental diseases, which is difficult to diagnose because of unknown etiology and complicated symptoms. At present, the diagnosis of schizophrenia depends to a large extent on the clinical experience of psychiatrists and the domestic and foreign disease classification manuals (CCMD-3 and DSM-IV-TR, etc.), so far there is no definite objective diagnostic criteria. With the development of electrophysiology and digital signal processing technology, EEG analysis-assisted diagnosis of schizophrenia has become a hot research topic at home and abroad. The EEG signal is nonlinear and complex, and the traditional linear analysis method is not suitable for its characteristic analysis. Therefore, this paper uses nonlinear dynamics to analyze the EEG signal of schizophrenic patients. In order to establish a relatively objective criterion for the diagnosis of schizophrenia, we look for the nonlinear characteristics of schizophrenia. The pathogenesis of schizophrenia is still unclear, but studies have shown that there are many cognitive disorders in psychotaxonomy, and executive dysfunction is the most important cognitive disorder. The execution function can be divided into two aspects: the cold execution function (Cool Executive Function) and the hot execution function (Hot Executive Function). Among them, the cold execution function mainly involves the response inhibition, the effectiveness and flexibility of attention and individual task execution, which reflects the ability of the subjects to plan and deal with the task. Cold execution function does not involve the content of emotional arousal, so this paper chooses cold execution ability task as experimental stimulus. In this paper, 17 first-episode schizophrenic patients and 17 healthy volunteers were assigned three cold tasks (A, C), respectively. The nonlinear dynamic analysis of the multi-channel EEG signals collected under the state of connection test B and Hanoi tower was carried out, and the nonlinear characteristics such as C _ 0 complexity, fractal dimension and approximate entropy were calculated. The difference between the first-episode schizophrenic patients and normal EEG signals was analyzed, and the results were verified by statistical analysis and support vector machine classifier (SVM). The results showed that the EEG signals of the first-episode schizophrenic patients were more irregular and complex, especially in the cold task execution, especially under the B task of the wired test. Approximate entropy and fractal dimension can well reveal the difference between the first-episode schizophrenia group and the healthy control group in nonlinear dynamic characteristics of EEG signal, but the representation effect of C _ 0 complexity is not ideal. Therefore, by choosing a suitable nonlinear dynamic algorithm to analyze the EEG signals in the cold task state, we can objectively reveal the abstract cognitive dysfunction in schizophrenic patients. To provide a new objective reference for the diagnosis and treatment of schizophrenia.
【學位授予單位】：新鄉(xiāng)醫(yī)學院
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：R749.3
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