Neural recognition system for swine cough
D Moshou,
A Chedad,
A Van Hirtum,
J De Baerdemaeker,
D Berckmans and
H Ramon
Mathematics and Computers in Simulation (MATCOM), 2001, vol. 56, issue 4, 475-487
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.
Keywords: Neural networks; Self-organising maps; Intelligent systems; Sound analysis (search for similar items in EconPapers)
Date: 2001
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475401003160
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:56:y:2001:i:4:p:475-487
Access Statistics for this article
Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens
More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().