[1]薛栋超,朱俊杰.针对心磁信号的HISSA优化多模态协同降噪算法[J].中国医学物理学杂志,2025,42(9):1201-1211.[doi:DOI:10.3969/j.issn.1005-202X.2025.09.012]
　XUE Dongchao,ZHU Junjie,et al.HISSA-optimized multi-level cooperative denoising algorithm for magnetocardiogram signals[J].Chinese Journal of Medical Physics,2025,42(9):1201-1211.[doi:DOI:10.3969/j.issn.1005-202X.2025.09.012]
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针对心磁信号的HISSA优化多模态协同降噪算法()

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
42
期数:
2025年第9期
页码:
1201-1211
栏目:
医学信号处理与医学仪器
出版日期:
2025-09-30

文章信息/Info

Title:
HISSA-optimized multi-level cooperative denoising algorithm for magnetocardiogram signals
文章编号:
1005-202X（2025）09-1201-11
作者:
薛栋超1; 2; 朱俊杰1; 2
1.河南理工大学电气工程与自动化学院， 河南 焦作 454003； 2.河南省煤矿装备智能检测与控制重点实验室， 河南 焦作 454003
Author(s):
XUE Dongchao1;  2;  ZHU Junjie1;  2
1. School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, China 2. Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Jiaozuo 454003, China
关键词:
心磁图; 多层级降噪算法; 经验模态分解; 变分模态分解; 完全集成经验模态分解与自适应噪声; 猎人干扰麻雀搜索算法
Keywords:
magnetocardiogram multi-level denoising algorithm empirical mode decomposition variational mode decomposition complete ensemble empirical mode decomposition with adaptive noise hunter interferes with sparrow search algorithm
分类号:
R318；TN911.7；R540.4
DOI:
DOI:10.3969/j.issn.1005-202X.2025.09.012
文献标志码:
A
摘要:
心磁图因无创、无接触、精度高等优点在心脏病预防和诊断中备受关注，由于其信号微弱需对其进行降噪处理。针对心磁信号含有的噪音特性，提出一种多层级降噪算法，将经验模态分解、变分模态分解、完全集成经验模态分解与自适应噪声线性串联，依次通过经验模态分解去除基线漂移，采用猎人干扰麻雀搜索算法优化变分模态分解算法参数，以相关系数为阈值筛选出包含主要特征的分量，结合完全集成经验模态分解与自适应噪声算法精确滤除信号中含有的高斯白噪声。实验结果表明该算法能在保留心磁信号主要特征的同时尽可能滤除环境噪声，其平均基数方差为1.492 7、最大基数方差为1.649 4、平均信噪比达24.267 7、最小信噪比达22.867 7，各项指标优于传统算法，噪声滤除效果良好。
Abstract:
Magnetocardiography (MCG) has attracted considerable attention in the field of heart disease prevention and diagnosis, attributed to its non-invasive, contact-free, and high-precision characteristics. However, MCG signals are extremely weak, making denoising processing imperative for subsequent analysis. Herein, a multi-level cooperative denoising algorithm tailored to the noise characteristics of MCG signals is proposed. This algorithm linearly integrates empirical mode decomposition, variational mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. Specifically, empirical mode decomposition is firstly employed to eliminate baseline drift. Subsequently, hunter interferes with sparrow search algorithm is utilized to optimize the parameters of variational mode decomposition, and components carrying the principal features are filtered out using the correlation coefficient as the threshold. Finally, complete ensemble empirical mode decomposition with adaptive noise is incorporated to accurately remove Gaussian white noise from the signals. Experimental comparisons demonstrate that the proposed algorithm can preserve the principal features of MCG signals while maximizing the filtration of environmental noise, achieving an average base variance of 1.492 7, a maximum base variance of 1.649 4, an average signal-to-noise ratio of 24.267 7, and a minimum signal-to-noise ratio of 22.867 7, outperforming traditional algorithms, and exhibiting the excellent noise filtering performance.

相似文献/References:

[1]李浩然,朱俊杰.基于信号子空间主特征向量的心磁源重构[J].中国医学物理学杂志,2022,39(10):1280.[doi:DOI:10.3969/j.issn.1005-202X.2022.10.017]
　LI Haoran,ZHU Junjie.Magnetocardiogram source reconstruction based on principal eigenvector of signal subspace[J].Chinese Journal of Medical Physics,2022,39(9):1280.[doi:DOI:10.3969/j.issn.1005-202X.2022.10.017]
[2]徐俊,朱俊杰.基于改进最小方差波束成形的心磁信号的源重建[J].中国医学物理学杂志,2024,41(7):870.[doi:DOI:10.3969/j.issn.1005-202X.2024.07.013]
　XU Jun,ZHU Junjie,et al.Source reconstruction from magnetocardiography signals based on improved minimum variance beamforming[J].Chinese Journal of Medical Physics,2024,41(9):870.[doi:DOI:10.3969/j.issn.1005-202X.2024.07.013]

备注/Memo

备注/Memo:
【收稿日期】2025-02-23 【基金项目】国家自然科学基金（61601173） 【作者简介】薛栋超，硕士研究生，研究方向：信号与信息处理，E-mail：xdc990320@163.com 【通信作者】朱俊杰，博士研究生，讲师，研究方向：生物医学信号处理，E-mail: junjiezhu@hpu.edu.cn
更新日期/Last Update: 2025-09-30