小波变换下的脑电信号癫痫特征波识别算法研究  

Identify Algorithm of Epileptic Characteristic Waves for EEG based on Wavelet Transform

作　　者：王鹏翔 张兆基[1] Wang Pengxiang;Zhang Zhaoji(School of Information Engineering,Tibet Nationalities University,Xianyang Shaanxi 712082,China)

机构地区：[1]西藏民族大学信息工程学院,陕西咸阳712082

出　　处：《信息与电脑》2017年第17期63-65,共3页Information & Computer

基　　金：2015年西藏自治区高校青年教师创新支持计划项目"基于非线性算子的癫痫实时预测DSP实现与自动释药预治疗模型研究"(项目编号:QC2015-56)的成果

摘　　要：为了能够实现癫痫脑电信号的有效识别,笔者提出了基于小波变换的脑电信号癫痫特征波识别算法。将临床收集的癫痫发作过程中患者的数据作为样本,使用小波变换实现信号的分析,以此实现癫痫病情的诊断,之后将癫痫特征反射到标准电极中,使用相关的源点位软件定位癫痫病灶。研究结果显示,小波变换下的识别算法能够实现癫痫脑电信号特征的自动检测,并且还能够准确定位病灶,能够实现临床诊断及癫痫病情的筛查。In order to effectively identify the epilepsy EEG signal,the author proposes a identify algorithm of epilepsy EEG signalbased on wavelet transform.Patient data collected during epileptic seizure are taken as samples and the wavelet transform is used to analyze EEG,which can effectively diagnose epilepsy.Then the epileptic characteristic is reflected into the standard electrode and the source point position is employed to locate epileptic focus.The results show that the recognition algorithm based on wavelet transform can automatically identify epilepsy EEG signal and accurately locate epileptic focus,so the algorithm proposed is conducive to clinically diagnose and screen epilepsy.

关 键 词：小波变换 脑电信号 癫痫特征波 识别算法 

分 类 号：R318[医药卫生—生物医学工程] R742.1[医药卫生—基础医学]