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Hybrid ICA algorithm for ECG analysis

机译:用于ECG分析的混合ICA算法

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摘要

Electrocardiogram (ECG) signals are among the most important sources of diagnostic information in healthcare, so improvements in their analysis are also of growing importance. The rapidly developing signal technology and a flourishing variety of algorithms have proved successful targets for recent advances in research. Several techniques have been proposed to extract the ECG components contaminated with the background noise and allow the measurement of subtle features in the ECG signal. This paper illustrates the ability of Independent Component Analysis (ICA) for removal of noises and artifacts and source separation. With the discussions on some ICA schemes such as JADE algorithm, Fast ICA and constrained ICA (cICA), a hybrid algorithm using Fast ICA for noise removal and cICA for source separation has been proposed along with their simulation results.
机译:心电图(ECG)信号是医疗保健中最重要的诊断信息来源之一,因此对其分析的改进也变得越来越重要。迅速发展的信号技术和种类繁多的算法已被证明是近期研究进展的成功目标。已经提出了几种技术来提取被背景噪声污染的ECG分量,并允许测量ECG信号中的细微特征。本文说明了独立分量分析(ICA)去除噪声和伪影以及源分离的能力。通过对一些ICA方案(如JADE算法,Fast ICA和约束ICA(cICA))的讨论,提出了使用Fast ICA去除噪声和cICA进行信号源分离的混合算法,以及它们的仿真结果。

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