期刊文献+

基于SWT和双变量阈值函数的ECG信号去噪 被引量:4

ECG signal denoising based on stationary wavelet transform and bivariate threshold function
下载PDF
导出
摘要 针对心电信号易受到肌电噪声、工频噪声、基线漂移、电极接触噪声以及环境噪声等的干扰,提出一种基于平稳小波变换和双变量阈值函数的ECG信号去噪方法。通过对ECG信号进行多层平稳小波变换,依据噪声在不同分解层的特点,对变换后的细节系数采用不同的阈值去噪方案。这种方法可避免信号重构后的丢失,能较好地保留原始信号的完整性,在提高信号信噪比的同时降低均方误差。通过对MIT-BIH数据库的实测数据进行仿真实验分析,验证了所提算法的有效性。 An ECG signal denoising method based on stationary wavelet transform and bivariate threshold function was proposed, since the ECG signal is easily subjected to electromyography noise, power frequency noise, baseline drift, electrode contact noise and ambient noise. Multi-layer stationary wavelet transform was used for ECG signals, and different threshold de-noising schemes were used for the transformed detail coefficients obtained according to the characteristics of the noise in different decomposition layers. The method can avoid the loss of signal reconstruction, preserve the integrity of the original signal better, and improve the signal to noise ratio of the signal while reducing the mean square error. Through simulation experiments on the measured data of MIT-BIH database, the validity of the proposed method is verified.
作者 汤伟 王玲利 税宇阳 王帅 TANG Wei;WANG Ling-li;SHUI Yu-yang;WANG Shuai(College of Electrical and Information Engineering,Shaanxi University of Science and Technology,Xi ’an 710021,China;College of Mechanical and Electrical Engineering,Shaanxi University of Science and Technology,Xi ’an 710021,China)
出处 《计算机工程与设计》 北大核心 2019年第3期725-730,共6页 Computer Engineering and Design
基金 陕西省科技统筹创新工程计划基金项目(2016KCTQ-35) 陕西省重点科技创新团队计划基金项目(2014KCT-15)
关键词 ECG信号去噪 双变量阈值 平稳小波变换 MIT-BIH数据库 信噪比 均方误差 ECG signal denoising bivariate threshold stationary wavelet transform MIT-BIH database signal noise ration mean squared error
  • 相关文献

参考文献2

二级参考文献18

  • 1吕丹,张欣,王艳,莫国民,刘红.基于滤波器系数变长度优化方法的心电信号滤波处理[J].中国医疗器械信息,2009,15(8):36-38. 被引量:3
  • 2侯铁双,相敬林,韩鹏.基于DT-CWT统计模型的舰船噪声信号中线谱信号检测研究[J].西北工业大学学报,2009,27(6):801-805. 被引量:3
  • 3石宏理,胡波.双树复小波变换及其应用综述[J].信息与电子工程,2007,5(3):229-234. 被引量:24
  • 4MALLAT S G. A theory for multiresolution signal decom- position : the wavelet representation [ J ]. IEEE Trans PA- MI, 1989,11 (7) :674-693.
  • 5DAUBECHIES I. Where dowavelets come from? Aperson- al point of view[J]. Proc IEEE,1996,84(4) :510-513.
  • 6CAI T T, SILVERMAN B W. Incorporating information on neighboring coefficients into wavelet estimation [ J ]. The Indian Journal of Statistics .2001.63 (2"~ : 127-148.
  • 7KINGSBURY N G. The dual-tree complex wavelet trans- form:A New technique for shift invariance and directional filter [ J ]. IEEE Digital Signal Processing Workshop, 1998,98(1) :2-5.
  • 8SELESNICK I W, BARANIUK R G, KINGSBURY N G. The dual-tree complex wavelet transform [ J ]. IEEE Signal Processing Magazine,2005,22 (6) : 123-151.
  • 9SENDUR L, SELESNICK I W. Bivariate shrinkage func- tions for wavelet-based denoising exploiting interscale de- pendency [ J ]. IEEE Transactions on Image Processing, 2002,11 (50) :2744-2756.
  • 10钱苏敏,张琳絮,张云等.基于小波阈值改进的去噪算法研究[J].国外电子测量技,2012,31(5):49_51.

共引文献55

同被引文献33

引证文献4

二级引证文献19

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部