一种面向体域网的ECG信号小波阈值去噪法  

Wavelet Threshold De-noising Method Oriented to Body Area Networks

作　　者：刘毅[1] 宋余庆[1] 刘哲[1] 徐力彬[1] 包翔[1] 

机构地区：[1]江苏大学计算机科学与通信工程学院,镇江212013

出　　处：《计算机科学》2014年第11期175-177,202,共4页Computer Science

基　　金：江苏省普通高校研究生科研创新计划(CXZZ11_0575);高等学校博士学科点专项科研基金资助课题(20113227110010);江苏省自然科学基金(BK20130529);江苏省博士后科研资助计划项目(1202037C);中国博士后科学基金(2013M541616)资助

摘　　要：ECG信号的处理在体域网环境下面临资源受限、随机噪声多等问题,这对ECG信号的去噪方法提出了更高的要求。在提升小波变换的基础上,提出了一种新的基于双阈值函数的ECG信号去噪法。利用该双阈值函数对提升小波分解后的ECG细节信号进行处理,可以更加精确地将噪声信号从原始信号中分离出去。仿真实验表明,本算法在一定程度上克服了软、硬阈值去噪法的缺陷,获得了更好的去噪性能,去噪速度快,设计简单灵活,为计算资源受限的体域网等环境下的ECG信号的下一步处理奠定了基础。ECG signal processing in body area network environment is faced with many problems,including limited resources and random noise.So it is essential to propose a better algorithm which is used for ECG signal de-noising.On the basis of lifting wavelet transform,we proposed a new de-noising method of ECG signal based on dual-threshold function.With this dual-threshold function processing the detail ECG signal decomposed by lifting wavelet,more accurate noise signal will be separated from the original signal.Simulation results show that the proposed de-noising algorithm overcomes the disadvantages of both soft and hard threshold methods to some degree,and obtains better de-noising performance.The de-noising speed is fast and the design of program is flexible and simple.The algorithm lays the foundation of the further processing of the ECG signal in some restricted environments such as body area networks.

关 键 词：体域网 提升小波 去噪 心电图 双阈值函数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]