Denoising and characterization of heart sound signals using optimal intrinsic mode functions

D. Boutana, M. Benidir, B. Barkat
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引用次数: 8

Abstract

Empirical mode decomposition (EMD) allows decomposing an observed multicomponent signal into a set of monocomponent signals, called Intrinsic Mode Functions (IMFs). The aim of this paper is to characterize some heart sound (HS) signals embedded in noise using the EMD approach. In particular, the proposed technique automatically selects the most appropriate IMFs achieving the denoising based on EMD and Euclidean measure. Synthetic and real-life signals are used in the various examples to validate, and demonstrate the effectiveness, of the proposed method. Furthermore, this technique is compared to the commonly known approach based on the noise model.
利用最优固有模态函数对心音信号进行去噪和表征
经验模态分解(EMD)允许将观测到的多分量信号分解为一组单分量信号,称为内禀模态函数(IMFs)。本文的目的是利用EMD方法对嵌入在噪声中的心音信号进行表征。特别地,该方法基于EMD和欧几里得度量自动选择最合适的imf来实现去噪。在各种例子中使用合成信号和实际信号来验证和证明所提出方法的有效性。此外,还将该方法与基于噪声模型的常用方法进行了比较。
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