基于公平成本函数的汉默斯坦分线自适应过的性能,用于拒绝心电图信号
Suchada Sitjongsataporn1, Theerayod Wiangtong2
1Department of Electronic Engineering, School of Electrical and Electronic Engineering (SEE), Faculty of Engineering and Technology, Mahanakorn University of Technology, Nongchok, Bangkok 10530, Thailand.
Biomimetics (Basel, Switzerland)
|December 24, 2025
概括
这项研究引入了一种新的自适应非线性过器,用于消除心电图 (ECG) 信号的噪声,改进个人心脏信号分析. 汉默斯坦螺纹自适应波器具有公平成本功能,与传统方法相比,有效降低噪声.
科学领域:
- 生物医学信号处理
- 适应性过是一种自适应性过.
- 非线性系统是非线性系统.
背景情况:
- 线性过器在现实应用中存在局限性,特别是对于复杂的生物信号,如心电图.
- 适应性非线性过提供了一种有前途的方法来解决仿生系统中的个体变化和噪声.
- 电脑心电图信号无声化对于准确的心脏诊断和监测至关重要.
研究的目的:
- 提出一种简化的自适应非线性过方法,用于消除心电图 (ECG) 信号的噪声.
- 开发一种能够适应独特的ECG特征并有效消除噪音的个人生物医学过器.
- 通过使用公平成本函数来增强自适应过器的融合和性能.
主要方法:
- 设计了一个汉默斯坦螺纹自适应波器 (HSAF) 架构,结合了非线性和线性块.
- 整合了公平成本功能,以提高收流性和效率.
- 具有公平成本函数的亲缘投影算法 (APA) 用于消除受污染的心电图信号.
- 使用了MIT-BIH12-lead数据库,使用Cauchy分布建模的噪声.
主要成果:
- 拟议的HSAF-APA-Fair算法证明了在拒绝ECG信号时估计误差减少.
- 与传统的最小平均平方 (LMS) 算法相比,该算法显示出更好的性能.
- 公平成本功能有助于更快的融合,并提高了报销准确性.
结论:
- 开发的自适应型非线性波器为个人心电图信号消噪提供了有效的方法.
- HSAF-APA-Fair算法提供了一种强大的解决方案,可以消除噪音,同时保持基本的心电图特征.
- 这种方法推动了生物医学信号处理领域的发展,用于个性化医疗保健应用.
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