TY - JOUR
T1 - Classification of respiratory sounds based on wavelet packet decomposition and learning vector quantization
AU - Pesu, Leena
AU - Helistö, Panu
AU - Ademovic, E.
AU - Pesquet, J.-C.
AU - Saarinen, Ari
AU - Sovijärvi, A.
N1 - BIOMED 1 programme of the European Community financed Concerted Action project CORSA (Computerized Respiratory Sound Analysis), Workpackage III
PY - 1998
Y1 - 1998
N2 - In this paper, a wavelet packet-based method is used for detection of abnormal respiratory sounds. The sound signal is divided into segments, and a feature vector for classification is formed using the results of the search for the best wavelet packet decomposition. 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 which was also analysed by an expert observer. The preliminary results are promising, although not yet good enough for clinical use.
AB - In this paper, a wavelet packet-based method is used for detection of abnormal respiratory sounds. The sound signal is divided into segments, and a feature vector for classification is formed using the results of the search for the best wavelet packet decomposition. 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 which was also analysed by an expert observer. The preliminary results are promising, although not yet good enough for clinical use.
U2 - 10.3233/THC-1998-6108
DO - 10.3233/THC-1998-6108
M3 - Article
SN - 0928-7329
VL - 6
SP - 65
EP - 74
JO - Technology and Health Care
JF - Technology and Health Care
IS - 1
ER -