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Cough sound analysis to identify respiratory infection in pigs

Ferrari, Sara, Silva, Mitchell, Guarino, Marcella, Aerts, Jean Marie, Berckmans, Daniel
Computers and electronics in agriculture 2008 v.64 no.2 pp. 318-325
cough, disease detection, respiratory tract diseases, swine, recording equipment, sounds, swine diseases, swine housing, algorithms, automatic detection, acoustics
Cough sound detection is a central element to diagnose common respiratory diseases like pneumonia in intensive pig farming. The aim of this work is the description of acoustic features of cough sounds originating from a lung infection and the comparison between these kind of cough sounds with those provoked by inhalation of citric acid. Coughs have been recorded from infected animals in field conditions (pneumonia) and from healthy animals in laboratory (induced). After having completed the classification, the investigation on infectious and non-infectious cough sounds has involved the main differences among acoustic parameters, like the Root Mean Square (RMS), the peak frequency (Hz), the duration and the time occurring between successive coughs in a cough attack. The results show a significant difference among the RMS, peak frequency and duration in cough sounds from healthy and infected animals. RMS was 0.215 for healthy animals and 0.124 for infected ones (P =0). Non-infectious coughs have an average peak frequency of 1600Hz, while infectious coughs stand around 600Hz. Also the length of sounds is significantly lower (P <0.001) for non-infectious coughs (average 0.43s) than for infectious ones (average 0.67s). The space of time between each sick cough in a cough sequence seems shorter than the interval occurring between healthy coughs (0.37s versus 0.52s). The above mentioned findings could be surely helpful to develop a real-time cough classification algorithm, based on sound feature analysis, in order to acquire a monitoring system for automatic and continuous infection in pig houses.