刘春,谢皓,肖奕霖,邓传远.EWT算法在ECG信号滤波中的研究[J].电子测量与仪器学报,2017,31(11):1835-1842
EWT算法在ECG信号滤波中的研究
Research on empirical wavelet transform algorithm in ECG signal filtering
  
DOI:10.13382/j.jemi.2017.11.021
中文关键词:  经验小波变换  心电图  实时性  自适应滤波
英文关键词:EWT  ECG  real time  adaptive filtering
基金项目:国家重大仪器开发专项(2013YQ220643)资助项目
作者单位
刘春 合肥工业大学电气与自动化工程学院合肥230009 
谢皓 合肥工业大学电气与自动化工程学院合肥230009 
肖奕霖 合肥工业大学电气与自动化工程学院合肥230009 
邓传远 合肥工业大学电气与自动化工程学院合肥230009 
AuthorInstitution
Liu Chun School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China 
Xie Hao School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China 
Xiao Yilin School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China 
Deng Chuanyuan School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China 
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中文摘要:
      针对经验模态分解(EMD)算法存在的模态混叠问题和集合经验模态分解(EEMD)算法实时性不足的缺点,采用EMD与小波分析相结合的EWT算法,对ECG信号的频谱自适应分割,在分割区间上构建小波滤波器组,提取具有紧支撑的单分量成分,剔除直流分量和噪声余项,并将其余分量重构。实验数据来自MIT BIH数据库中真实的心电图(ECG)信号,仿真结果表明,该算法能有效去除ECG信号中的基线漂移和工频干扰,信噪比(SNR)、均方根误差(RMSE)和自相关系数(AC)优于其他两种自适应算法EMD和EEMD;算法整体运行时间小于1 s,满足了心电监测的实时性与准确性要求。
英文摘要:
      The algorithm empirical mode decomposition(EMD) has the issue of mode mixing, and the algorithm ensemble empirical mode decomposition(EEMD) has poor real time performance. Aiming at these defects, the method of empirical wavelet transform (EWT) combining the EMD with wavelet analysis is proposed. In this paper, the method is taken to segment ECG signal spectrum adaptively, and constructs wavelet filter banks in segmental intervals to extract the single component equipped with tight support, then eliminates direct component and noise residual. After that the signal from other component can be reconstructed. The experimental data comes from the real ECG signal in the MIT BIH database, and the simulation result shows that the algorithm removes baseline wander and power line interference. The parameters of signal noise ratio, mean root square error and autocorrelation coefficient are better than other two adaptive algorithms: EMD and EEMD. The whole running time of algorithm is less than 1 s, which can satisfy the requirements of real time and accurate ECG monitor.
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