發(fā)布時間：2018-06-09 22:37

  本文選題：復(fù)雜網(wǎng)絡(luò) + 癲癇腦電�。� 參考：《山東大學(xué)學(xué)報(工學(xué)版)》2017年03期

【摘要】：為提取癲癇發(fā)作與間歇期腦電信號的特征,提出利用構(gòu)建癲癇EEG(electroencephalogram)網(wǎng)絡(luò)的方法來刻畫腦電信號。研究各變量均可測情況下的Lorenz和R9ssler混沌系統(tǒng),利用其各變量的輸出混沌時間序列構(gòu)建復(fù)雜網(wǎng)絡(luò),發(fā)現(xiàn)構(gòu)建的復(fù)雜網(wǎng)絡(luò)拓?fù)鋱D與其混沌吸引子存在形態(tài)相似性,說明由時間序列構(gòu)建的復(fù)雜網(wǎng)絡(luò)能刻畫其原信號特征。對于多維系統(tǒng)中僅有一維可測時,多維時間序列由相空間重構(gòu)得到。利用相空間重構(gòu)方法對癲癇發(fā)作和間歇期腦電信號構(gòu)建復(fù)雜網(wǎng)絡(luò)進(jìn)行分析。研究結(jié)果表明,癲癇發(fā)作時其網(wǎng)絡(luò)拓?fù)漭^間歇期存在明顯不同,且其平均路徑長度顯著增加,而遞歸率及其波動范圍都顯著降低,這些網(wǎng)絡(luò)特性可以用來刻畫腦電信號的特征,從而為癲癇疾病的自動辨識與預(yù)測提供基礎(chǔ)。
[Abstract]:In order to extract the characteristics of epileptic seizures and EEG signals, a method of constructing epileptic EEG (electroencephalogram) network is proposed to characterize EEG signals. The chaotic systems of Lorenz and R9ssler are studied under the conditions of all variables, and complex networks are constructed by using the output chaotic time series of its variables to find the complex network constructed. The topological graph is similar to the chaotic attractor. It shows that the complex network constructed by the time series can depict its original signal characteristics. For only one dimension in the multidimensional system, the multidimensional time series is reconstructed by phase space. The complex network of epileptic seizures and the intermittent period of EEG is constructed by phase space reconstruction. The results show that the network topology of epileptic seizures is significantly different from that in the intermittent period, and the average path length of the epileptic seizures is significantly increased, and the recurrence rate and its fluctuation range are significantly reduced. These network characteristics can be used to characterize the EEG signal and provide the basis for the automatic identification and prediction of epilepsy.
【作者單位】： 河北科技大學(xué)電氣工程學(xué)院;天津大學(xué)電氣與自動化工程學(xué)院;
【基金】：河北省自然科學(xué)基金資助項目(F2014208013)
【分類號】：O157.5;R742.1

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