一个新的可控制的能量约束-变量模式分解无效化算法
Yue Yu1, Zilong Zhou1, Chaoyang Song1
1Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122 Jiangsu China.
Biomedical engineering letters
|March 3, 2025
概括
本研究介绍了控制式能量约束-变化模式分解 (CEC-VMD) 用于消除心电图 (ECG) 信号的噪声. 这种新的方法有效地消除噪音,同时保留了改善心脏病诊断的关键信号特征.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 电心电图 (ECG) 信号对于诊断心脏病至关重要.
- 电脑心电图信号中的噪音显著影响诊断的准确性.
- 现有的无声化方法往往难以平衡消除噪音和保护特征.
研究的目的:
- 开发一种用于消除心电图信号的新型算法.
- 为了提高基于心电图的心脏病诊断的准确性.
- 改进现有的信号处理技术,以减少ECG噪声.
主要方法:
- 采用了拟议的控制能量约束-变化模式分解 (CEC-VMD) 算法.
- 噪音性心电图信号被分解成内在模式函数 (IMF) 和残余.
- 使用调制因子和基于ADMM的更新来改进模态属性并最大限度地减少剩余信息.
主要成果:
- 在模拟和MIT-BIH信号上,CEC-VMD的平均SNR达到22.5139,RMSE为0.1128,CC为0.9882.
- 该算法显著提高了分类准确度,达到99.0% (SVM) 和99.9% (KNN).
- CEC-VMD在消毒和特征保存方面表现优于EMD,VMD和SWT等传统方法.
结论:
- CEC-VMD技术有效地消除了ECG信号中的噪声.
- 这种方法增强了 ECG 信号的基本特征的保存.
- 信号质量的提高导致了更准确的心脏病分类.
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