Enhancing single-lead ECG arrhythmia classification via multi-teacher decomposed feature distillation.

IF 1.6 4区医学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-08-09 DOI:10.1080/10255842.2025.2542947

Majid Sepahvand, Maytham N Meqdad, Fardin Abdali-Mohammadi

引用次数: 0

Abstract

When an arrhythmia occurs in the heart, all electrocardiogram (ECG) leads show evidence of it, but it is more prominent in some leads. This medical fact serves as the foundation for the knowledge distillation (KD) model proposed in this paper, which aims to enhance weak leads by leveraging information from stronger ones. The model employs single-lead signals for the student network and twelve-lead signals for the teacher network. Tucker decomposition is used in this KD model to decompose the teacher's feature maps. According to evaluations, the student model achieves an accuracy of 96.48% on the Chapman ECG dataset classification task.

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基于多导联特征分解的单导联心律失常分类方法。

当心律失常发生时，所有的心电图导联都显示出心律失常的迹象，但在某些导联中更为突出。这一医学事实是本文提出的知识蒸馏（KD）模型的基础，该模型旨在通过利用强线索的信息来增强弱线索。该模型对学生网络采用单导联信号，对教师网络采用十二导联信号。该KD模型采用Tucker分解对教师特征图进行分解。经评价，学生模型在Chapman心电数据集分类任务上的准确率达到96.48%。

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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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.