Analysis on the EEG Signal Based on Phase Space
- 物理技术－已发表论文 
为寻求脑电(Electroencephalogram,EEG)分析的新途径,提出了一种基于状态空间的脑电分析的新方法.利用状态空间点间的欧氏距离来计算脑电状态空间的态密度和态方差.实验结果表明,态密度和态方差不仅计算简单,而且与脑电的关联维数和Lyapunov指数相比,更能有效地反映混沌系统非线性动力学的特征.此外,还计算了基于距离协方差的脑电信号的奇异谱,并对结果作了分析.In order to seek new approaches to the analysis of EEG, a new method based on the phase space analysis of EEG is proposed.By using the Euclidian distances of the phase point in phase space, both the phase density and the phase variance are calculated. The experimental results show that, the phase density and the phase variance both are not only simple in calculation , but also more efficient than the correlation dimension and the Lyapunov Exponents of EEG in reflecting the features of nonlinear dynamics of chaotic system. Moreover, the singular spectra based on the distance covariance of EEG are calculated,and the experimental results are analysed.