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一种高效的ECG信号消噪技术,基于粒子群优化和波形变换的组合

Abdallah Azzouz¹, Billel Bengherbia¹, Patrice Wira²

¹Research Laboratory in Advanced Electronics Systems (LSEA), University of Medea, Pole Urbain, Medea, 26000, Algeria.

|March 8, 2024

概括

这项研究引入了一种新的粒子集群优化-波形转换 (PSO-WT) 技术,用于消除心电图 (ECG) 信号的噪声. 该PSO-WT方法有效地消除噪声,显著提高临床诊断和物联网应用的信号质量.

科学领域:

生物医学工程生物医学工程
信号处理信号处理
计算智能是一种计算智能.

背景情况:

电心电图 (ECG) 信号容易产生各种噪音,如肌肉活动,白色高斯噪声 (WGN),基线流浪和电力线干扰 (PLI).
有效的心电图信号消噪对于准确的特征提取和临床诊断至关重要.
传统的波纹变换 (WT) 方法需要费力的参数调整,这限制了它们的实际应用.

研究的目的:

通过优化波形变换 (WT) 参数来开发一种自动化和高效的ECG信号消噪方法.
将粒子优化 (PSO) 与WT结合起来,以确定ECG无声化的最佳配置.
根据现有的最先进的方法,评估拟议的PSO-WT技术的性能.

主要方法:

开发了一种新的技术,将粒子集群优化 (PSO) 与波形转换 (WT) 集成在一起.
采用PSO自动确定最佳WT参数,包括波段基础函数,值函数,分解水平,值选择规则和重新缩放方法.
用MIT-BIH心律失常数据库来测试拟议的PSO-WT方法的效率.

主要成果:

与现有方法相比,拟议的PSO-WT技术在ECG信号消噪方面表现出优异的性能.
信号与噪声比 (SNR) 得到显著改善,特别是在60Hz的电力线干扰 (PLI) 中 (例如,从10dB输入到27.47dB输出SNR).
该方法还在消除被白色高斯噪声 (WGN) 损坏的信号方面表现出高效率,这表明它对物联网和射频应用具有相关性.

结论:

PSO-WT技术为ECG信号消噪提供了有效的自动化解决方案,克服了传统WT方法中手动参数调节的局限性.
通过PSO-WT实现的增强信号质量提高了ECG信号对临床诊断的适用性.
该方法对不同类型的噪声的稳定性使其对现代医疗保健和通信技术具有高度价值.

关键词:

一个AWGN的AWGN.电心电图 (ECG) 是一种心电图.粒子群集优化粒子群集优化电力线路干扰干扰的情况.波段变换的波段变换是什么

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