基于小波包分解的精神分裂症脑电信号分析  

Analysis of the EEG in Schizophrenia Based on Wavelet Packet Decomposition

作　　者：许慰玲[1] 黄静霞[1] 沈民奋[1] 

机构地区：[1]汕头大学广东省数字图像处理重点实验室,汕头515063

出　　处：《电子测量与仪器学报》2004年第2期35-40,共6页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金 ( 60 2 71 0 2 3 ) ;广东省自然科学基金重点项目 ( 0 2 1 2 64)资助项目

摘　　要：本文针对脑电信号的非平稳性 ,引入小波包分解理论研究精神分裂症脑电。根据脑电信号的不同节律特性 ,提出应用小波包分解构造不同频率特性的滤波器 ,提取脑电信号不同节律的动态特性 ,并由此构造各种节律的动态脑电地形图。为了研究精神分裂症脑电信号各种节律的动态特性 ,文中对正常人和精神分裂症病人的临床脑电数据进行分析与比较 ,分析两组脑电信号各种节律的动态特性。实验结果表明 。In this paper, the theory of wavelet packet decomposition is employed to investigate the schizophrenia EEG signals according to its nonstationarity. On the basis of the property of different EEG rhythms, wavelet packet decomposition is used for designing filters with different frequency characteristics to detect the dynamic characteristics of different EEG rhythms, which are used to form the dynamic electrical brain activity mapping (DBEAM). In order to examine the dynamic characteristics of all sorts of rhythms which were generated by schizophrenic patients, two kinds of clinical EEG data from normal person and schizophrenic patient are analyzed and compared. The experimental results indicate that compared with normal person, the α rhythm of schizophrenic patients are quite different under the reposed eyes-closing and conscious state with any load.

关 键 词：小波包分解 非平稳脑电信号 精神分裂症 节律提取 背景节律 动态脑电图 信号分析 

分 类 号：R749.3[医药卫生—神经病学与精神病学]