基于小波变换模极大的脉象信号研究  

Study of Pulse Signal Based on Wavelet Transform Modulus Maxima

作　　者：唐富华[1] 郭银景[2] 杨阳[1] 康景利[1] 

机构地区：[1]北京理工大学机电工程学院,北京100081 [2]山东科技大学信息与电气工程学院,山东青岛266510

出　　处：《北京理工大学学报》2005年第6期538-542,共5页Transactions of Beijing Institute of Technology

摘　　要：针对脉象信号的时变、非线性和低频特性,提出了应用小波变换模极大对脉象信号进行研究的方法.介绍了利用小波变换模极大对信号局部特征进行描述的三个参数:Lipschitz指数α、平滑因子σ和分形维数D(α),并提出了对小波变换模极大曲线进行滤波的算法.用高斯一阶导数和二阶导数小波变换分别对单周期三峰脉象信号进行了实验.实验结果表明,该方法可以描述一些时域难以表达的特征,并能对脉象信号的局部特征点进行准确定位,从而为各项脉象特征的定量化描述和脉象分类识别奠定基础.<Abstrcat> To deal with time-varying, nonlinear and low frequency characteristics of pulse signal, a method based on wavelet transform modulus maxima is presented. The three parameters of wavelet transform modulus maxima namely the Lipschitz exponent α, smooth factor σ and fractal dimension D(α) are introduced, and a filtering algorithm of wavelet transform modulus maxima curve is put forward. Experiments are performed on a three peaks pulse signal using Gaussian first-order derivative and second-order derivative wavelet transforms. Experimental results show that some characteristics that cannot be described in time domain can be extracted using this method, and the local feature points of pulse signal can be located precisely. It establishes the foundation of the quantitative description of the pulse characteristics and the recognition of pulse.

关 键 词：小波变换模 脉象 信号 Lipschitz指数 极大的 低频特性 局部特征 分形维数 平滑因子 二阶导数 一阶导数 准确定位 分类识别 非线性 单周期 特征点 定量化 实验 滤波 

分 类 号：TN911.7[电子电信—通信与信息系统] TP391.41[电子电信—信息与通信工程]