Department of Technology, Elizabeth City State University, Elizabeth City, NC 27909, USA.
Adv Exp Med Biol. 2010;680:677-83. doi: 10.1007/978-1-4419-5913-3_75.
In this study, the nonlinear properties of the electroencephalograph (EEG) signals are investigated by comparing two sets of EEG, one set for epileptic and another set for healthy brain activities. Adopting measures of nonlinear theory such as Lyapunov exponent, correlation dimension, Hurst exponent, fractal dimension, and Kolmogorov entropy, the chaotic behavior of these two sets is quantitatively computed. The statistics for the two groups of all measures demonstrate the differences between the normal healthy group and epileptic one. The statistical results along with phase-space diagram verify that brain under epileptic seizures possess limited trajectory in the state space than in healthy normal state, consequently behaves less chaotically compared to normal condition.
在这项研究中,通过比较两组脑电图(EEG)信号,一组用于癫痫,另一组用于健康的大脑活动,研究了脑电图信号的非线性特性。采用 Lyapunov 指数、关联维数、Hurst 指数、分形维数和 Kolmogorov 熵等非线性理论的测度,对这两组脑电图信号的混沌行为进行了定量计算。两组所有测度的统计数据都表明了正常健康组和癫痫组之间的差异。统计结果以及相空间图验证了癫痫发作时大脑在状态空间中的轨迹有限,因此与正常状态相比,混沌行为较少。