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An ECG signal denoising method based on enhancement algorithms in EMD and Wavelet domains

机译:基于EMD和小波域增强算法的心电信号去噪方法

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This paper presents a new method based on enhancement algorithms in Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) domains for ECG signal denoising. Unlike the conventional EMD based ECG denoising methods that neglect a number of initial IMFs containing the QRS complex as well as noise, we propose a windowing method in EMD domain to filter out the noise from the initial IMFs without discarding them completely thus preserving the QRS complex. The comparatively cleaner ECG signal thus obtained from the EMD domain is employed to perform an adaptive soft thresholding in the DWT domain considering the advantageous properties of the DWT compared to EMD in preserving the energy and reconstructing the original ECG signal with a better time resolution. The performance of the proposed method is evaluated in terms of standard metrics by performing extensive simulations using the MIT-BIH arrhythmia database. The simulation results show that the proposed method is able to enhance the noisy ECG signals of different levels of SNR more accurately and consistently in comparison to some of the state-of-the-art methods.
机译:本文提出了一种基于经验模式分解(EMD)和离散小波变换(DWT)域增强算法的ECG信号去噪新方法。与传统的基于EMD的ECG去噪方法忽略了许多包含QRS复数以及噪声的初始IMF的方法不同,我们提出了一种EMD域中的加窗方法,可以从初始IMF中滤除噪声而不完全丢弃它们,从而保留QRS复数。考虑到DWT与EMD相比在保存能量和以更好的时间分辨率重建原始ECG信号方面的优势,考虑到DWT的有利特性,从EMD域中获得的相对较干净的ECG信号被用于在DWT域中执行自适应软阈值处理。通过使用MIT-BIH心律失常数据库进行广泛的模拟,根据标准指标评估了所提出方法的性能。仿真结果表明,与某些最新方法相比,该方法能够更准确,更一致地增强不同信噪比级别的嘈杂ECG信号。

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