脑电信号的多尺度排列熵分析

Multiscale permutation entropy analysis of electroencephalogram

本文利用多尺度排列熵对正常脑电信号和癫痫脑电信号进行了详细的分析和比较,研究了脑电图信号多尺度排列熵值和年龄的关系以及尺度因子对多尺度排列熵值的影响.通过对处于各个年龄段的22组正常人和22组患有癫痫人群的脑电图进行多尺度排列熵分析,发现在相同年龄段的人群中,正常脑电信号的多尺度排列熵值要高于癫痫脑电信号,熵值平均高出约0.19,约7.9%.另外,在尺度因子小于15的情况下,对于在30到35的年龄段正常人群,其多尺度排列熵值最大,随着年龄段的增大或降低熵值都一定程度的降低.结果证明,多尺度排列熵可以成功区分正常脑电信号和癫痫脑电信号,并且熵值可以正确地反映人体大脑发育的一般过程.

We carried out a detailed analysis and a comparison between normal and epileptic electroencephalogram （EEG） based on multiscale permutation entropy. The relationship between multiscale permutation entropy values of EEG and age, and the effect of scale factor on multiscale permutation entropy value were also discussed. By analyzing normal and epileptic EEG based on multiscale permutation entropy, we found that, at the same age, multiscale permutation entropy value of the normal group＇s EEG is higher than that of the epileptic group by an average of 0.19, about 7.9%. In addition, for people of age 3 to 35, their multiscale permutation entropies are clearly maximum. When scale factor is smaller than 15, the value of their entropy would reduce no matter whether the age increases or decreases. The results indicate that multiscale permutation entropy can distinguish between normal and epileptic EEG and reflect the general process of human brain development.