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Computer based analysis for heart and lung signals separation

机译:基于计算机的心脏和肺信号分离分析

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In this paper, two methodologies are proposed to enhance the automatic noise cancellation and signal separation between heart and lung sounds. In fact, transient signals such as heart and lung signals may undergo abrupt or sharp change in the first and second derivatives. A real separation between such two interfering mixed signals needs an efficient approach to avoid losing important information in both signals. Rhythmic cardiac signal contains important characteristics which can be exploited to develop adaptive based algorithms that allow efficient separation between lung and heart signals when they are mixed in a recorded signal. In the first proposed methodology we have developed an algorithm based on adaptive filtering technique and build using multiple filtering functions with coefficients correlated to the mixed source signal. In the second methodology, fast independent component analysis was developed to cancel heart sound in lung mixed sound. Both methods are well detailed in this work, and a comparative study is achieved to evaluate the efficiency of each method. A high accuracy of the new proposed algorithms is found and many applications are used to quantify the performances of these techniques.
机译:在本文中,提出了两种方法来增强心脏和肺部声音之间的自动噪声消除和信号分离。实际上,诸如心脏和肺信号的瞬态信号可能发生在第一和第二衍生物中的突然或急剧变化。这种两个干扰混合信号之间的实际分离需要有效的方法来避免在两个信号中丢失重要信息。节奏心脏信号包含重要特征,可以利用以开发基于自适应的基于自适应的算法,当它们在记录的信号中混合时允许在肺和心脏信号之间有效分离。在第一种提出的方​​法中,我们开发了一种基于自适应滤波技术的算法,并使用与混合源信号相关的系数的多滤波功能构建。在第二种方法中,开发了快速独立的分量分析,以取消肺部混合声音的心声。在这项工作中详述了两种方法,实现了比较研究以评估每种方法的效率。找到了新的提出算法的高精度,并且许多应用程序用于量化这些技术的性能。

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