A new framework for wavelet based analysis of acoustical cardiac signals

S. Mandal, J. Chatterjee, A. Ray
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引用次数: 6

Abstract

Cardiac auscultation is one of the classical methods used by the physicians for diagnosis of cardiac abnormalities. There have been attempts to develop complex algorithms for automated diagnosis based on heart sounds. It is however, observed that developmental work towards integrated automated auscultation system targeted towards mass screening has been relatively low. In this paper, we propose a new framework for analysis of acoustical cardiac signals which is suitable for development of point of care cardiac healthcare products. Wavelet analysis has been employed for denoising of the signal which enables the systems applicability in a rural health centre. The new framework also effectively focuses on selection of best wavelet basis through entropy measures and reducing the time-frequency decomposition cycles.
心音信号小波分析的新框架
心脏听诊是内科医生诊断心脏异常的经典方法之一。已经有人尝试开发基于心音的自动诊断的复杂算法。然而,观察到针对大规模筛查的综合自动化听诊系统的开发工作相对较少。在本文中,我们提出了一个新的框架来分析心脏的声音信号,这是适合于开发的护理点心脏保健产品。采用小波分析对信号进行去噪,使系统适用于农村卫生中心。新框架还有效地关注了通过熵度量选择最佳小波基和减少时频分解周期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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