Segmentation of respiratory signals by Evidence Theory

被引：1

作者：

Belghith, Akram ^{[1
]}

Collet, Christophe ^{[1
]}

机构：

[1] Strasbourg Univ, LSIIT, CNRS, UMR 7005, Strasbourg, France

来源：

2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20 | 2009年

关键词：

Data fusion; segmentation; imprecision; evidence theory; fuzzy membership function;

D O I：

10.1109/IEMBS.2009.5333026

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper presents an evidential segmentation scheme of respiratory signals for the detection of the wheezing sounds. The segmentation is based on the modeling of the data by evidence theory which is well suited to represent such uncertain and imprecise data. In this paper, we particularly focus on the modelization of the data imprecision using the fuzzy theory. The modelization result is then used to define the mass function. The effectiveness of the method is demonstrated on synthetic and real signals.

引用

页码：1905 / 1908

页数：4

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