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Proceedings Paper

An evidence segmentation scheme for asthma detection using a priori wavelet respiratory sound information
Author(s): Akram Belghith; Christophe Collet
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Paper Abstract

This paper presents an evidential segmentation scheme of respiratory sounds for the detection of wheezes. The segmentation is based on the modeling of the data by evidence theory which is well suited to represent such uncertain and imprecise data. Moreover, this paper studies the efficiency of the fuzzy theory for modelizing data imprecision. The segmentation results are improved by adding a priori information to the segmentation scheme. The effectiveness of the method is demonstrated on synthetic and real signals

Paper Details

Date Published: 4 February 2010
PDF: 10 pages
Proc. SPIE 7535, Wavelet Applications in Industrial Processing VII, 753509 (4 February 2010); doi: 10.1117/12.841714
Show Author Affiliations
Akram Belghith, LSIIT, CNRS, Strasbourg Univ. (France)
Christophe Collet, LSIIT, CNRS, Strasbourg Univ. (France)

Published in SPIE Proceedings Vol. 7535:
Wavelet Applications in Industrial Processing VII
Frédéric Truchetet; Olivier Laligant, Editor(s)

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