降噪
噪音(视频)
信号(编程语言)
计算机科学
信号重构
滤波器(信号处理)
信噪比(成像)
相关系数
模式识别(心理学)
人工智能
均方误差
信号处理
语音识别
数学
数字信号处理
统计
计算机视觉
电信
机器学习
图像(数学)
程序设计语言
计算机硬件
作者
Shahid Malik,Shabir A. Parah,Bilal A. Malik
标识
DOI:10.1109/iciip53038.2021.9702571
摘要
During its acquisition phase an ECG signal gets adulterated with distinct variants of undesirable noise thereby degrading its qualitative nature thereby inflicting a restraint on its clinical applicability. Hence it becomes imperative to design efficient methods to remove these artifacts specifically without deteriorating the signal quality. From classical approaches to modern digital methods, a multitude of methods have been reported in the literature for this purpose. In this paper, we have employed a computer-based hybrid approach that scrutinizes the denoising potential of VMD method. It proceeds by disintegrating an ECG signal polluted with high frequency PLI and low frequency noise into a band of VMFs with PLI distributed over lower order modes while as the low frequency noise distributed over the higher order modes. The higher order modes are then separately fed to an SWT system while as the sum of the lower order modes is fed to a non-local mean filter. Finally, the signal is reconstructed from the processed modes to generate a pure ECG signal free from artefacts. The prowess of the given method has been experimentally validated through the improvements in the three empirical parameters viz.: output SNR, cross-correlation coefficient and percentage root-mean-square difference. These parameters ascertain that the ECG signal has been efficiently denoised and faithfully reconstructed whilst maintaining and preserving its overall features. The experiments have been performed on the various recordings available online at MIT-BIH arrhythmia database.
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