摘要
癫痫脑电信号是非平稳、非线性的,根据此特性我们提出一个基于Lempel-Ziv复杂度和经验模态分解(EMD)的癫痫脑电信号的检测方法,首先将癫痫脑电信号用EMD分解,再分别计算每阶固有模态函数(IMF)的复杂度,最后将得到的复杂度作为特征进行检测.实验用波恩数据库来评估提出的方法.结果表明,该方法检测准确率可达到95.25%,具有准确率高、适应性强等优点.
Taking non-stationary and nonlinearity of epilepsy signals into consideration,we proposed a method for detection of epilepsy,based on Lempel-Ziv（ LZ） complexity and empirical mode decomposition（ EMD）. EMD first decomposed epilepsy signals into a set of intrinsic mode functions（ IMFs）. Then calculated complexity of each IMF. Bonn dataset was utilized for evaluating the method. Experimental results showed that the highest accuracy could be achieved to 95. 25%. It has advantages of high accuracy,strong adaptability and so on.
出处
《计算物理》
CSCD
北大核心
2015年第6期709-714,共6页
Chinese Journal of Computational Physics
基金
国家自然科学基金(61201428,61070130)资助项目
