Classification of respiratory sounds based on wavelet packet decomposition and learning vector quantization

Authors:
L. Pesu;P. Helistö;E. Ademovič;J.-C. Pesquet;A. Saarinen;A. R. A. Sovijärvi
Affiliations:
-;-;-;-;-;-
Venue:
Technology and Health Care
Year:
1998

Citing 0
Cited 6

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Abstract

In this paper, a wavelet packet-based method is used for detectionof abnormal respiratory sounds. The sound signal is divided intosegments, and a feature vector for classification is formed usingthe results of the search for the best wavelet packetdecomposition. The segments are classified as containing crackles,wheezes or normal lung sounds, using Learning Vector Quantization.The method is tested using a small set of real patient data whichwas also analysed by an expert observer. The preliminary resultsare promising, although not yet good enough for clinical use.