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首页> 外文期刊>Chinese Journal of Electronics >A Novel Adaptive Wavelet Thresholding with Identical Correlation Shrinkage Function for ECG Noise Removal
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A Novel Adaptive Wavelet Thresholding with Identical Correlation Shrinkage Function for ECG Noise Removal

机译：具有相同相关收缩功能的新型自适应小波阈值消除心电图噪声

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摘要

On the basis of wavelet theory, a novel Adaptive wavelet thresholding method (AWT) is proposed for the ECG signal enhancement. The best base wavelet for ECG signal filtering can be automatically obtained through the cross correlation coefficient and the energy to entropy ratio. The variable universal threshold (VarUniversal) is applied to different decomposition level so as to suppress diverse noise. To achieve a smooth cut-off transition, an identical correlation shrinkage function (IcoShrinkage) is also adopted in the AWT according to its correlation coefficients with the hard thresholding and the soft thresholding. The performance of AWT is compared with four threshold approaches and six shrinkage functions, respectively, on the basis of 150 practical ECG signals of 30 subjects. The filtering results reveal that the AWT can adaptively choose an optimal base wavelet for a specific ECG signal. With the VarUniversal threshold and IcoShrinkage, the AWT obtains the better filtering results than the other compared methods.
机译：在小波理论的基础上，提出了一种新的自适应小波阈值化方法。通过互相关系数和能量熵比，可以自动获得用于ECG信号滤波的最佳基本小波。可变通用阈值（VarUniversal）应用于不同的分解级别，以抑制各种噪声。为了实现平滑的截止过渡，AWT还根据其具有硬阈值和软阈值的相关系数，采用了相同的相关收缩函数（IcoShrinkage）。在30个对象的150个实际ECG信号的基础上，分别将AWT的性能与四个阈值方法和六个收缩功能进行比较。滤波结果表明，AWT可以针对特定的ECG信号自适应地选择最佳基本小波。借助VarUniversal阈值和IcoShrinkage，AWT可获得比其他比较方法更好的过滤结果。

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