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Electrocardiogram (ECG) denoising method utilizing Empirical Mode Decomposition (EMD) with SWT and a Mean based filter

机译:利用SWT和平均滤波器利用经验模式分解(EMD)的心电图(ECG)去噪方法

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Electrocardiogram is an pivotal physiological signal that is exploited for the detection of cardiological ailments. An ECG signal necessarily gets polluted with different types of unwanted noise during its acquisition phase thereby deteriorating its quality. This imposes a constraint on its utility in disease diagnosis. It thus becomes necessary to remove these artifacts while at the same time preserving the main features of the signal. EMD based methods have been extensively used for the purpose. In this paper, we utilized a blended method that explores the denoising capability of EMD along with that of SWT and NLM filtering techniques to filter out 50 Hz sinusoidal AC noise and white noise. The efficiency of the presented method has been demonstrated in respect of the empirical parameters like SNR improvement and mean of square error values whilst using various records from the arrhythmia database of the MIT Beth Israel Hospital. The excellence of the method presented has been exhibited through comparison of the obtained results with an existing method
机译:心电图是枢转生理信号,用于检测心脏病学疾病。在其采集阶段期间,ECG信号必然被不同类型的不需要的噪声污染,从而降低了其质量。这对其在疾病诊断中的效用施加了限制。因此,必须在保持信号的主要特征的同时删除这些伪像。基于EMD的方法已广泛用于此目的。在本文中,我们利用了一种混合方法,探讨了EMD的去噪能力以及SWT和NLM过滤技术的滤波功能,以滤除50 Hz正弦响应噪声和白噪声。已经证明了所提出的方法的效率,例如SNR改善和平方误差值的平均值,同时使用来自MIT Beth以色列医院的心律失常数据库的各种记录。通过将所得结果与现有方法的比较进行了展示了所呈现的方法的卓越

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