使用VMD和EWT在心电图中消除电力线干扰和基线流浪
Haroon Yousuf Mir1, Omkar Singh1
1Department of Electronics and Communication Engineering, National Institute of Technology Srinagar (J&K), India.
这项研究引入了一种新的混合方法,用于通过变化模式分解 (VMD) 和实证波波变换 (EWT) 消除心电图 (ECG) 信号的噪声. 新技术有效减少噪音,提高心血管疾病的诊断准确度.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 心脏病学 心脏病学
背景情况:
- 电心电图 (ECG) 信号对于诊断心血管疾病至关重要.
- 临床心电图采集通常被电源线干扰 (PLI) 和基线漫游 (BLW) 等噪音污染.
- 噪音导致的信号扭曲会导致误解和不准确的诊断.
研究的目的:
- 开发和评估一种新型的混合ECG无声化方法.
- 提高心电图信号分析的可靠性,以便更好地进行心血管诊断.
- 为了应对临床心电图数据中降噪的挑战.
主要方法:
- 这是一种混合方法,结合了变化模式分解 (VMD) 和经验波纹变换 (EWT).
- 噪声的心电图信号被分解成窄带变化模式函数 (VMF).
- 适应波纹过器银行是使用基于VMF中心频率的EWT设计的,用于消除噪音.
主要成果:
- 拟议的方法应用于来自MIT-BIH心律失常数据库的ECG信号.
- 使用MIT-BIH噪音压力测试数据库 (NSTDB) 评估性能,主要指标是:百分比-根-平均平方差 (PRD) 和信号对噪声比 (SNR).
- 混合VMD-EWT方法实现了较低的PRD和较高的SNR,与现有的排污技术相比,平均SNR为24.03和5%的PRD降低.
结论:
- 新的混合VMD-EWT方法在ECG无声化方面表现出卓越的性能.
- 这种技术为可靠的心电图信号分析和心血管诊断提供了显著的改进.
- 这种方法有效地消除了噪声组件,提高了生物医学信号的质量.
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