利用双谱分析的癫痫脑电特征研究

根据癫痫患者脑电信号具有非高斯、非线性随机特性,应用高阶累积量技术对癫痫患者的脑电信号进行双谱估计,研究了在不同发病阶段的脑电信号的高斯偏离程度,以获取更加敏感和准确的临床监护和发病预报参量.用参数模型法进行双谱估计,并根据奇异值分解最小二乘法求解模型参数,从而获得高分辨率的双谱估计值和有效的脑电相位信息.用功率谱对高阶谱进行规范,规范化结果可作为相关系数,通过估计双相关系数找出它与癫痫发作的关系.实验结果表明,患者在癫痫发作前、开始发作和发作期,双谱的等高线图具有明显的尖峰,在癫痫发作时的脑电双相关系数值要比癫痫发作前和发作后的系数值高得多,使得脑电波的非高斯性和非线性增强.双谱分析为癫痫脑电信号的研究提供了一些新的思路,双相关系数有望成为临床监护、预报癜痫发作的一个指标.

Study of Epileptic Electroencephalogram Using Bispectrum Analysis

Based on the fact that the signals of epileptic electroencephalogram (EEG) possess non-Gaussian and nonlinear stochastic properties, the higher-order statistic methods were used to estimate the bispectrum of epileptic EEG. The Guassian deviations of the EEGs in different stages of seizure were studied, in order to obtain more sensitive and accurate parameters for clinical epileptic monitoring and seizure prediction. By using the parameter model method to estimate bispectrum of EEG, model parameters are determined based on the singular value decomposition least square method. Thereby the bispectrum estimation with a high resolution and some available EEG phase information can be obtained. The higher order spectrum is normalized with conventional power spectrum, and the result show can be used as coherence coefficient, and its relation with epileptic seizure can be found by estimating the coefficient. The experimental results show that contour diagrams of bispectrum possess obvious peaks in paroxysm,so and before-begin paroxysm of epileptic, and bicoherence coefficient of EEG is very high before-after paroxysm,so it boosts up non-Gaussian and nonlinear of brain wave.It can offer some new ideas for research of epileptic EEG and they may be potential parameters for clinical epileptic monitoring.