Unveiling fetal heart health: harnessing auto-metric graph neural networks and Hazelnut tree search for ECG-based arrhythmia detection.

IF 1.7 4区医学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-24 DOI:10.1080/10255842.2025.2481232

M Suganthy, B Sarala, G Sumathy, W T Chembian

引用次数: 0

Abstract

Fetal electrocardiogram (ECG) provides a non-invasive means to assess fetal heart health, but isolating the fetal signal from the dominant maternal ECG remains challenging. This study introduces the FHH-AMGNN-HTSOA-ECG-AD method for enhanced fetal arrhythmia detection. It employs Dual Tree Complex Wavelet Transform for denoising and utilizes an Auto-Metric Graph Neural Network (AMGNN) optimized by the Hazelnut Tree Search Algorithm (HTSOA). This integration enables accurate classification of normal and abnormal fetal heart signals. Experimental results demonstrate that the proposed approach significantly outperforms existing methods in terms of accuracy, precision, and specificity.

查看原文本刊更多论文

揭示胎儿心脏健康：利用自度量图神经网络和榛子树搜索心电图为基础的心律失常检测。

胎儿心电图（ECG）提供了一种评估胎儿心脏健康的非侵入性手段，但从主要的母体心电图中分离胎儿信号仍然具有挑战性。本研究介绍了FHH-AMGNN-HTSOA-ECG-AD方法对胎儿心律失常的增强检测。该算法采用对偶树复小波变换进行去噪，并利用由榛子树搜索算法（HTSOA）优化的自度量图神经网络（AMGNN）进行去噪。这种整合能够准确分类正常和异常的胎儿心脏信号。实验结果表明，该方法在准确性、精密度和特异性方面明显优于现有方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Computer Methods in Biomechanics and Biomedical Engineering 工程技术-工程：生物医学

CiteScore

4.10

自引率

6.20%

发文量

179

审稿时长

4-8 weeks

期刊介绍： The primary aims of Computer Methods in Biomechanics and Biomedical Engineering are to provide a means of communicating the advances being made in the areas of biomechanics and biomedical engineering and to stimulate interest in the continually emerging computer based technologies which are being applied in these multidisciplinary subjects. Computer Methods in Biomechanics and Biomedical Engineering will also provide a focus for the importance of integrating the disciplines of engineering with medical technology and clinical expertise. Such integration will have a major impact on health care in the future.