小波多分辨率理论在心音信号分析中的应用

Application of Wavelet Multi-resolution Theory to Heart Sounds Analysis

目的:心音信号是人体重要生理信号之一,通过小波多分辨率理论,能够准确地区分正常心音与杂音成分,使用现代信号处理技术能有效地提高诊断效果。方法:以LabVIEW8.6为开发平台,利用小波多分辨率理论,对心音信号进行多层分解。结果:通过对心音信号不同层中的分析,可以准确地区分S1、S2以及心脏杂音,还可将心音信号正确地划分为收缩期杂音信号(SM)、舒张期杂音信号(DM)和正常信号。结论:分析结果证明,该方法能准确地区分正常心音与杂音成分,为心脏病的辅助诊断提供有效的参考。

Objective Heart sounds signal is one of the most important human physiological signal which can distinguish normal heart sound from murmurs through Wavelet Multi-resolution Theory.The efficiency of this diagnosis can be improved considerably by using modern signal processing techniques.Methods Based on LabVIEW8.6 virtual instrument developing platform,the heart sounds signal was decomposed into many levels using wavelet multi-resolution.Results The analysis can accurately identify S1,S2 and murmurs from different levels and can also classify the heart sounds signals into three categories：signal with systolic murmur,signal with diastolic murmur,or normal signal.Conclusion This method can distinguish normal heart sound from murmurs and provides an effective reference for the diagnosis of heart disease.