The influence of respiratory disease on the energy envelope dynamics of pig cough sounds

  • Authors:

  • Mitchell Silva;Vasileios Exadaktylos;Sara Ferrari;Marcella Guarino;Jean-Marie Aerts;Daniel Berckmans

  • Affiliations:

  • Measure, Model and Manage Bioresponse (M3-BIORES), Department of Biosystems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 30, 3001 Heverlee, Belgium;Measure, Model and Manage Bioresponse (M3-BIORES), Department of Biosystems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 30, 3001 Heverlee, Belgium;Department of Veterinary Sciences and Technologies for Food Safety, Faculty of Veterinary Medicine, Via Celoria 10, 20133 Milan, Italy;Department of Veterinary Sciences and Technologies for Food Safety, Faculty of Veterinary Medicine, Via Celoria 10, 20133 Milan, Italy;Measure, Model and Manage Bioresponse (M3-BIORES), Department of Biosystems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 30, 3001 Heverlee, Belgium;Measure, Model and Manage Bioresponse (M3-BIORES), Department of Biosystems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 30, 3001 Heverlee, Belgium

  • Venue:
  • Computers and Electronics in Agriculture
  • Year:
  • 2009

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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