AP—Animal Production Technology: Recognition System for Pig Cough based on Probabilistic Neural Networks
✍ Scribed by A. Chedad; D. Moshou; J.M. Aerts; A. Van Hirtum; H. Ramon; D. Berckmans
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 534 KB
- Volume
- 79
- Category
- Article
- ISSN
- 0021-8634
No coin nor oath required. For personal study only.
✦ Synopsis
Until now the use of acoustic bio-responses in bio-environment control as indicators of animal-condition is limited to human perception. Coughing is a frequent symptom of many respiratory diseases a!ecting the airways and lungs of humans and animals.
Registration of coughs from di!erent pigs in a controlled test chamber was done in order to analyse the acoustical signal. A new approach is presented to distinguish cough sounds from other sounds, such as grunts, metal clanging and background noise, using neural networks as the classi"cation method. Other signals (such as grunts, metal clanging, etc.) could also be detected.
The best performance was obtained with a hybrid classi"er that classi"es coughs and metal clanging separately from the rest, giving better results compared to a probabilistic neural network (PNN) alone. The hybrid classi"er, which consists of a 2-and a 4-class PNN, gave high discrimination performance in the case of grunts, metal clanging and background noise (91)4, 63)9 and 82)6%, respectively) and a performance of (91)9%) for correct classi"cation in the case of coughs.