This item still needs to be validated !
Title: Neural recognition system for swine cough
Authors: Moshou, Dimitrios ×
Chedad, Allel
Van Hirtum, A
De Baerdemaeker, Josse
Berckmans, Daniel
Ramon, Herman #
Issue Date: Jun-2001
Publisher: Elsevier science bv
Series Title: Mathematics and Computers in Simulation vol:56 issue:4-5 pages:475-487
Conference: Proceedings of the third International IMACS/IFAC symposium on Mathematical modelling and simulation in Agricultural and Bio-industries. location:Sweden date:June
Abstract: Coughing is one of the most frequent presenting symptoms of many diseases affecting the airways and the lungs of humans and animals. The aim of this paper is to build up an intelligent alarm system that can be used for the early detection of cough sounds in piggeries. Registration of coughs from different pigs in a metallic chamber was done in order to analyse the acoustical signal. A new approach is presented to distinguish cough sounds from other sounds Like grunts, metal clanging and noise using neural networks (NN) as classification method. Other signals (grunts, metal clanging, etc.) could also be detected. Self-organising maps are used for visualisation of data relationships. Several types of NN are compared with statistical methods for the classification of the cough sounds. The early detection of coughs can be used for the construction of an intelligent alarm that can inform about the presence of a possible viral infection. (C) 2001 IMACS. Published by Elsevier Science B.V. All rights reserved.
ISSN: 0378-4754
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Mechatronics, Biostatistics and Sensors (MeBioS)
Division M3-BIORES: Measure, Model & Manage Bioresponses (-)
Faculty of Science, Campus Kulak Kortrijk
× corresponding author
# (joint) last author

Files in This Item:

There are no files associated with this item.

Request a copy


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science