A Proposal of Optimal Wavelet Filter Design for EGG Signal Decomposition based on Modified ABC Evolutionary Optimization

2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2019-01-01 DOI:10.1109/SAMI.2019.8782785

J. Kubícek, M. Penhaker, David Oczka, M. Bužga, M. Augustynek, M. Cerný, Jaroslav Vondrák, Alice Krestanova

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引用次数: 4

Abstract

Electrogastrography (EGG) has a substantial importance for the clinical practice for examination of gastric disorders and the stomach function. From a view of the EGG signal processing, there is not a unified scheme for the EGG evaluation due to complex variable EGG representation. The most important issue of the EGG is an interference with other electrophysiological signals, particular attention is paid to the ECG (electrocardiography) signal. In this context, the Wavelet transformation gives satisfactory results. The main issue we have to deal with is an optimal setting of the Wavelet transformation for the EGG filtration. In this paper, we have proposed a novel scheme utilizing the modified Artificial Bee Colony algorithm with the goal of an optimal selection of the Wavelet filter design. Based on the ABC evolutionary process, we specify an optimal mother’s wavelet and the decomposition level for the ECG reduction. The optimization procedure has been objectively verified by using selected evaluation parameters.

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基于改进ABC进化优化的EGG信号分解小波滤波器优化设计

胃电图(EGG)在临床实践中对胃病和胃功能的检查具有重要意义。从EGG信号处理的角度来看，由于EGG的变量表示复杂，没有一个统一的EGG评估方案。EGG最重要的问题是对其他电生理信号的干扰，特别是对心电图信号的干扰。在这种情况下，小波变换得到了令人满意的结果。我们必须处理的主要问题是EGG滤波的小波变换的最佳设置。在本文中，我们提出了一种利用改进的人工蜂群算法来优化小波滤波器设计的新方案。在ABC进化过程的基础上，确定了最优的母小波和分解层次。利用选取的评价参数对优化过程进行了客观验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)

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