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Wavelet-Based Wiener Filter for Electrocardiogram Signal Denoising

机译:基于小波的维纳滤波器用于心电图信号去噪

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The aim of this study is suppression of parasite electromyographic (EMG) signals (myopotentials) included in ECG signals with use of the Wiener filtering in shift-invariant wavelet domain with pilot estimation of the signal. The wavelet filtering with hybrid thresholding was used for pilot estimation. The four-levels shift-invariant dyadic discrete-time wavelet transform decomposition was used for both main blocks of pilot estimation and Wiener filtering. Sampling frequency of used signals was 500 Hz. The testing set have included signals with small waves Q, high R waves and significant variations of precipitousness in onsets and offsets of QRS complexes. These signals were additionally noised by normal distribution noise its power spectrum was adjusted according to typical form of power spectrum of EMG signals.
机译:该研究的目的是抑制ECG信号中包括的寄生电矿石(EMG)信号(Myopotensions),其利用换档不变小波域中的Wiener滤波,具有信号的导频估计。使用混合阈值化的小波滤波用于导频估计。四级移位不变的二级离散时间小波变换分解用于导频估计和维纳滤波的主要块。使用信号的采样频率为500 Hz。测试集包括具有小波,高R波的信号,高R波以及QRS复合物的悬浮液中的陡峭变化和QRS复合物的偏移变化。通过正常分布噪声另外发出这些信号,其功率谱根据EMG信号的典型功率谱进行调整。

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