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  • 标题:Enhancement of ECG Signal Using Ensemble EMD Algorithm and Higher Order Statistics
  • 本地全文:下载
  • 作者:Mohit Tyagi ; Ranjeeta Yadav ; Sanjay K. Singh
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2018
  • 卷号:7
  • 期号:6
  • 页码:6417-6423
  • DOI:10.15680/IJIRSET.2018.0706005
  • 出版社:S&S Publications
  • 摘要:There are different techniques and methods used in ECG signal processing that is denoising of ECG signal. The Ensemble Empirical Mode Decomposition Algorithm is one of them and is both an iterative and empirical process to decompose signal into IMF and further to decomposition instantaneous frequency data is extracted. This new intermittence approach avoided the problem of mode mixing happens during the original EMD process. EEMD method is designed to work well on nonlinear and nonstationary data set. As EEMD is a time-space analysis method, the length of the IMFs is same as the original signal thereby keeps the characteristics of varying frequency unchanged. The performance of this technique in denoising of ECG signal is based on the numerical values in terms of SNR and RMSE. The study is limited to signals corrupted by additive white Gaussian random noise.
  • 关键词:Empirical mode decomposition (EMD); Intrinsic mode function (IMF); Hilbert;Huang transform (HHT) Statistical parameters; RMSE; SNR
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