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用熵的方法在癫痫脑电信号中预测发病
摘 要
小波分析理论作为新的时频分析工具，在信号分析与处理中得到了很好的应用。而癫痫病的发作原理是大脑神经元突发性异常放电，导致短暂的大脑功能障碍。目前广泛应用的癫痫诊断方法就是对患者的脑电信号进行研究。
基于脑电信号和小波变换的基本理论，从基本概念过渡到到小波分析等一系列相关内容，最终引出小波分析中非常重要的MATLAB程序。通过对正常人和癫痫病症患者在相同环境下的脑电信号的提取，利用小波熵理论的MATLAB程序计算出两组脑电信号的小波熵，并进行对比和统计分析。实验分析结果表明癫痫患者和正常人自发脑电信号的小波熵有着显著的差异：在相同状态下，癫痫患者各导联脑电的小波熵大于正常人对应导联的脑电小波熵。相同情况下癫痫患者的脑电信号复杂程度要明显高于健康受测者。这样得出的癫痫患者和正常人的脑电信号的差异，为癫痫病症的诊断与治疗提供有力的依据。
关键词：癫痫；小波熵；脑电信号；MATLAB
ABSTRACT
Wavelet analysis theory , as a new time-frequency analysis tool , has been well applied in the area of signal analysis and processing . And principle of epileptic attack is a sudden abnormal discharge of brain neurons , leading to transient brain dysfunction . At present , the diagnosis method of eeg signals studied is widely applied in patients with epilepsy.
Based on the basic theory of eeg signals and wavelet transform , transition from basic concept to the wavelet analysis and a series of related content , then led to very important matlab wavelet analysis . Through to the patients with normal and epilepsy disease of brain electrical signal extraction in the same environment , wavelet entropy theory of matlab to calculate the wavelet entropy of the eeg signals in both groups , and comparison and statistical analysis . Analysis of experimental results show that the epileptic patients and normal person of spontaneous eeg signals wavelet entropy has obvious differences : under the same condition , people with epilepsy wavelet entropy of each lead eeg of corresponding lead is greater than the normal wavelet entropy of eeg ; Epilepsy in patients with brain electric signal complexity is significantly higher than the healthy subjects in the same case. Such of epilepsy patients and normal differences in eeg signals , disease diagnosis and treatment for epilepsy provide powerful basis.
Key words: Epilepsy ; The wavelet entropy ; Brain electrical signal ; MATLAB
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