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基于多变量相空间重构的癫痫脑电分析

Analysis of epileptic electroencephalogram based on multi-variable state space reconstruction
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摘要 目的:应用多变量相空间重构对分析脑电信号,获取癫痫脑电的非线性特征。方法:鉴于脑电(EEG)的高维混沌特性,通过多变量相空间重构分析方法,将大脑分为左右2个半区,分别以8个EEG导联作为重构样本进行非线性分析,可以得到线性区域,从而得到相关维数的估计值。结果:5例确诊癫痫患者的脑电分析结果基本一致,癫痫发作前、中、后期相关维数有明显变化,与对照组的结果差异显著。结论:多变量相空间重构法适用于对短时含噪声的时间序列进行分析,能够避免延迟时间和嵌入维数等参数的选择,得到更可靠的结果。 Based on the high-dimension chaos characteristics of electroencephalogram (EEG) and the analysis by the multivariable state space reconstruction, better estimation of the correlative dimension can be obtained by dividing the brain into two parts and using eight EEG channels as the reconstruction samples. Lorenz system was firstly tested by request of the amount of data to test the feasibility of the algorithms. After Comparing the high-dimension data of the EEG of epileptic patients with the results of control subjects, it is indicated that the multi-variable state space reconstruction is applicable in short time noise-containing time sequences to ohtain reliable results and can free the researchers from the hard choice of delay time and embedding dimension.
出处 《医疗卫生装备》 CAS 2006年第5期7-8,共2页 Chinese Medical Equipment Journal
关键词 脑电 相关维数 多变量相空间重构 癫痫 electroencephalogram (EEG) correlation dimension multi-variable state space reconstruction epileptic
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