基于小波变换的麻醉监测脑电信号的分析与处理  

Analysis and processing of anesthesia monitoring of EEG based on wavelet transformation

作　　者：张烈平[1] 莫玮[2] 牛秦洲[1] 

机构地区：[1]桂林工学院电子与计算机系,广西桂林541004 [2]桂林电子工业学院,广西桂林541004

出　　处：《桂林工学院学报》2002年第1期66-70,共5页Journal of Guilin University of Technology

基　　金：国家自然科学基金资助项目 (6 98710 10 )

摘　　要：针对中潜伏期听觉诱发脑电的特点 ,提出了利用小波变换的多分辨分析技术滤除被测信号的强噪声成分 ,重构真实信号来实现对中潜伏期听觉诱发脑电的提取方法 ;通过实验仿真表明 :小波变换提取技术比其他传统提取方法更有效 ,可以减少试验次数 ,可以提供更为可靠的特征提取和模式识别的分析数据 。The principle of wavelet transformation,multiresolution analysis and Mallat algorithm are introduced in this paper.According to the characters of MLAEP, the extraction method is proposed to denoise and reconstruct the MLEAP signal from strong noise background. The simulation results show that the extraction method based on wavelet transformation is more effective than other traditional methods.It can considerally reduce the tests,provide more useful analysis data for feature extraction and mode identification,and offer an important theory basis for clinic anesthesia monitoring.

关 键 词：小波变换 多分辨分析 MALLAT算法 麻醉监测 中潜伏期听觉诱发脑电信号 

分 类 号：R614[医药卫生—麻醉学] R318.04[医药卫生—外科学]