An evidence segmentation scheme for asthma detection using a priori wavelet respiratory sound information

Akram Belghith; Christophe Collet

doi:10.1117/12.841714

4 February 2010 An evidence segmentation scheme for asthma detection using a priori wavelet respiratory sound information

Akram Belghith, Christophe Collet

Author Affiliations +

Proceedings Volume 7535, Wavelet Applications in Industrial Processing VII; 753509 (2010) https://doi.org/10.1117/12.841714
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

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

Citation Download Citation

Akram Belghith and Christophe Collet "An evidence segmentation scheme for asthma detection using a priori wavelet respiratory sound information", Proc. SPIE 7535, Wavelet Applications in Industrial Processing VII, 753509 (4 February 2010); https://doi.org/10.1117/12.841714

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