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经验模态分解在动静脉内瘘狭窄杂音研究中的应用。

Application of the Empirical Mode Decomposition in the study of murmurs from Arteriovenous fistula stenosis.

作者信息

Vasquez Pablo, Marco Munguia M, Mattsson Elisabeth, Mandersson Bengt

机构信息

UNI-Asdi-FEC Group, Faculty of Electrical Engineering and Computer Science, National University of Engineering, Managua, Nicaragua.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:947-50. doi: 10.1109/IEMBS.2010.5627552.

Abstract

The Empirical Mode Decomposition (EMD) is a method to decompose non linear, non stationary time series into a sum of different modes, named Intrinsical Mode Functions each one having a characteristic frequency. In the present work we used the EMD to investigate the properties of the recorded sounds from the Arteriovenous fistula on hemodialysis patients. Phonoangiographic signals coming from two different vessel conditions, stenotic and non-stenotic, were analyzed by using EMD, the mean energy and mean instantaneous frequency per IMF proved to be good features for classification. Three types of classification schemes were tested on data from the first IMf features achieving good results.

摘要

经验模态分解(EMD)是一种将非线性、非平稳时间序列分解为不同模式之和的方法,这些模式被称为固有模态函数,每个固有模态函数都有一个特征频率。在本研究中,我们使用EMD来研究血液透析患者动静脉瘘记录声音的特性。通过使用EMD分析来自两种不同血管状况(狭窄和非狭窄)的血管造影信号,结果表明每个固有模态函数的平均能量和平均瞬时频率是用于分类的良好特征。对来自第一个固有模态函数特征的数据测试了三种分类方案,均取得了良好的结果。

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