Title: The influence of respiratory disease on the energy envelope dynamics of pig cough sounds
Authors: Silva, Mitchell ×
Exadaktylos, Vasileios
Ferrari, Sara
Guarino, Marcella
Aerts, Jean-Marie
Berckmans, Daniel #
Issue Date: Nov-2009
Publisher: Elsevier sci ltd
Series Title: Computers and electronics in agriculture vol:69 issue:1 pages:80-85
Abstract: The objective of this paper is to assess if the dynamics in the energy envelope of pig cough sounds are related to pathological conditions of the respiratory system. Two groups of pigs are compared. The first group, the sick pigs, is suffering from pneumonia by infection of Pasteurella Multocida. The second group, the control group, consists of healthy pigs which produced induced coughs by nebulisation of citric acid. The cough sounds of both groups were used to calculate the energy envelope, after which two signals are derived for further modelling. The first signal is an artificial step input, the second signal is part of the energy envelope of the cough signal that starts at the maximum level and decays in time. Using an autoregressive model estimation technique, the decay of the energy envelope is modelled as an input-output system. Based on the Young Identification Criterion (YIC) and R-2, the optimal model is proven to be a first order model with a first order denominator. Using this first order transfer function structure to model all cough sounds, the time constant of the simulated output is estimated based on the model parameters. The time constant shows significant higher values for the decay of the cough signals from pigs which are infected with Pasteurella Multocida compared to non-infected pigs (P < 0.0001). The results are in accordance with previous work in which pathological conditions have shown to influence cough sound duration. This modelling technique gives more insight in the effect of changes in lung condition on cough sound generation and might be incorporated in techniques for automatic cough evaluation. (c) 2009 Elsevier B.V. All rights reserved.
ISSN: 0168-1699
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division M3-BIORES: Measure, Model & Manage Bioresponses (-)
× corresponding author
# (joint) last author

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