TY - GEN
T1 - Segmentation of S1-S2 sounds in phonocardiogram records using wavelet energies
AU - Yamaçh, Mustafa
AU - Dokur, Zümray
AU - Ölmez, Tamer
PY - 2008
Y1 - 2008
N2 - Locating S1 and S2 sounds in order to diagnose diseases by classifying through the determination of systole and diastole phases is of great significance. The method suggested in this study is available for the segmentation of S1-S2 sounds in heart sounds (HSs) acquired in real-time and it also renders the classifying possible, thereby ensuring a correct diagnosis. In this study, multi-band wavelet energy (WTE) method was proposed for the segmentation of S1-S2 sounds in 16 different HS types. After normalizing the heart sound, the signal is filtered by using wavelet transform, after than S1-S2 sounds are segmented by using multi-band wavelet energy method. For comparison, besides the method which is proposed, two different methods are investigated. One of them is segmentation of S1-S2 sounds using multi-band wavelet Shannon energy (WSE) method and the other is segmentation of S1-S2 sounds using homomorphic filtering (HMF) method. The highest performances are achieved by the proposed WTE method; 91% and 89% segmentation accuracies are obtained for S1 and S2 sounds, respectively. The methods' robustness to noise was also analysed.
AB - Locating S1 and S2 sounds in order to diagnose diseases by classifying through the determination of systole and diastole phases is of great significance. The method suggested in this study is available for the segmentation of S1-S2 sounds in heart sounds (HSs) acquired in real-time and it also renders the classifying possible, thereby ensuring a correct diagnosis. In this study, multi-band wavelet energy (WTE) method was proposed for the segmentation of S1-S2 sounds in 16 different HS types. After normalizing the heart sound, the signal is filtered by using wavelet transform, after than S1-S2 sounds are segmented by using multi-band wavelet energy method. For comparison, besides the method which is proposed, two different methods are investigated. One of them is segmentation of S1-S2 sounds using multi-band wavelet Shannon energy (WSE) method and the other is segmentation of S1-S2 sounds using homomorphic filtering (HMF) method. The highest performances are achieved by the proposed WTE method; 91% and 89% segmentation accuracies are obtained for S1 and S2 sounds, respectively. The methods' robustness to noise was also analysed.
KW - Heart sounds
KW - Multi-band wavelet energies
KW - Phonocardiogram
KW - Segmentation of S1-S2 sounds
UR - http://www.scopus.com/inward/record.url?scp=58449095888&partnerID=8YFLogxK
U2 - 10.1109/ISCIS.2008.4717964
DO - 10.1109/ISCIS.2008.4717964
M3 - Conference contribution
AN - SCOPUS:58449095888
SN - 9781424428816
T3 - 2008 23rd International Symposium on Computer and Information Sciences, ISCIS 2008
BT - 2008 23rd International Symposium on Computer and Information Sciences, ISCIS 2008
T2 - 2008 23rd International Symposium on Computer and Information Sciences, ISCIS 2008
Y2 - 27 October 2008 through 29 October 2008
ER -