DocumentCode :
3512841
Title :
Wheezing sounds detection using multivariate generalized gaussian distributions
Author :
Le Cam, S. ; Belghith, A. ; Collet, Ch ; Salzenstein, F.
Author_Institution :
LSIIT, Univ. Strasbourg 1 (ULP), Strasbourg
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
541
Lastpage :
544
Abstract :
A wheeze is a continuous, coarse, whistling sound produced in the respiratory airways during breathing, commonly experienced by persons suffering from asthma. In this paper, we present a new method for the detection of wheezing sounds in the normal breathing sounds. In our study we perform an accurate statistical analysis of breathing signals. We suggest a modeling for wheezing and normal sounds in the wavelet packet domain using generalized Gaussian distributions. Our detection method is based on a specific multimodal Markovian modeling proposed in a Bayesian framework. We cope with the multidimensional aspect of the generalized Gaussian distribution by using the theory of copulas. Experimental results are given in detail in this paper.
Keywords :
Gaussian distribution; Markov processes; acoustic signal processing; belief networks; medical computing; statistical analysis; wavelet transforms; Bayesian framework; breathing signals; multimodal Markovian modeling; multivariate generalized Gaussian distributions; normal breathing sounds; respiratory airways; statistical analysis; wavelet packet domain; wheezing sounds detection; Cepstral analysis; Frequency; Gaussian distribution; Hidden Markov models; Image analysis; Probability density function; Shape; Statistical analysis; Wavelet domain; Wavelet packets; Adventitious Respiratory Sounds; Copulas; Data Fusion; Generalized Gaussian Distribution; Hidden Markov Chain; Theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4959640
Filename :
4959640
Link To Document :
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