PARAVALVULAR KAÇAKLI MEKANİK KALP KAPAK SES SİNYALLERİNİN AYRIK DALGACIK DÖNÜŞÜMÜYLE İNCELENMESİ

Year 2016, Volume: 4 Issue: 2, 65 - 72, 01.06.2016

Sabri Altunkaya

https://doi.org/10.15317/Scitech.2016218519

Abstract

Bu çalışmanın amacı mekanik kalp kapak değişiminden sonra kapak kenarında meydana gelen kaçağın belirlenmesine yönelik mekanik kalp kapak ses sinyallerinin ayrık dalgacık dönüşümü ile incelenmesidir. Bu amaçla mekanik kapak kenarında kaçak oluşmuş 2 hasta ile mekanik kalp kapağı normal çalışan 5 hastaya ait kalp kapak ses sinyalleri kayıt edilmiştir. Kayıt edilen mekanik kalp kapak ses sinyalleri ayrık dalgacık dönüşümü ile detay ve yaklaşım katsayılarına ayrıştırılmıştır. Ayrışım sonucu elde edilen detay ve yaklaşım katsayılarından özellikler çıkarılarak normal ve hasta gruba ait özellikler istatistiksel olarak karşılaştırılmıştır. Karşılaştırma sonucunda Daubechies 2 dalgacık fonksiyonundan elde edilen özelliklerin mekanik kalp kapağı kenarında oluşan kaçağın tespitinde kullanılabileceği görülmüştür.

Keywords

Mekanik kalp kapak ses sinyalleri, Ayrık dalgacık dönüşümü, Ayrık dalgacık dönüşümü

Investigation of Mechanical Heart Valve Leakage Using Discrete Wavelet Transform

Abstract

The aim of this study is to examine mechanical heart valve sounds using discrete wavelet transform for the diagnosis of paravalvular leakage (PVL) occurs after mechanical heart valve (MHV) replacement. For this aim, mechanical heart sounds of 2 patients with PVL and 5 volunteers with normal MHV was recorded. The recorded mechanical heart valve sounds are decomposed to detail and approximation coefficient using discrete wavelet transform. Features extracted from detail and approximation coefficients used for statically comparison of normal and patients data groups. As a result of comparison, it seen that the features obtained from Daubechies 2 wavelet function can be used to detect paravalvular leakage on mechanical heart valve. As a result, it is statically shown that Daubechies 2 wavelet function is suitable for diagnosis of PVL.

Keywords

Sound Signals of Mechanical Heart Valve, Discrete Wavelet Transform.

References

• Altunkaya, S.; Kara, S.; Gormus, N. & Herdem S., 2013, “Comparison of first and second heart sounds after mechanical heart valve replacement", Computer Methods in Biomechanics and Biomedical Engineering, 16:4, 368-380
• Altunkaya, S.; Kara, S.; Gormus, N., 2014, "Wavelet analysis of mechanical heart valve sounds with paravalvular leakage," Computer Technologies in Physical and Engineering Applications (ICCTPEA), 2014 International Conference on , vol., no., pp.7,8, June 30 2014-July 4 2014
• Addison, P.S,, 2002, “Illustrated wavelet transform handbook introductory theory and applications in science, engineering, medicine and finance, IOP Publishing Ltd., London, UK.
• Adeli, H., Zhou, Z., Dadmehr, N. , 2003, Analysis of EEG records in an epileptic patient using wavelet transform, J. Neurosci. Methods,123 (1), 69-87.
• Burrus, C.S., Gopinath, R.A., Guo, H., 1998, Introduction the wavelet and wavelet transform, Prentice- Hall, USA, 10-30.
• Daubechies, I., 1990, The wavelet transform, time-frequency localization and signal analysis, IEEE Transactions On Information Theory, 36 (5), 961-1005.
• Dominik, J., Zacek, P., 2010, Heart valve surgery an illustrated guide, Springer-Verlag Berlin Heidelberg, 1.Basım, 383-386.
• Jayawardena, S., Sooriabalan, D., Burzyantseva, O., Sinnapunayagm, S., 2008, Paravalvular mitral valve leakage presenting as congestive heart failure, missed by TTE but diagnosed by TEE: a case report, Cases Journal, 1-216.
• Mallat, S., 1998, A wavelet tour of signal processing, Academic Press, USA.
• Rosenberg, G., 2006, Tissue engineering and artificial organs, Bronzino, J.D., (edt.) CRC Press, USA, 64- 1-64-21.
• Sampaio, R.O., Costa da Silva, F., Oliveira, I.S. ve diğ., 2009, postoperative outcome of patients with prosthetic valve leak, Arq Bras Cardiol, 93 (3), 262-267.
• Sava, H.P., McDonnell, J.T.E., 1996, “Spectral composition of heart sounds before and after mechanical heart valve implantation using modified forward-backward prony’s method”, IEEE Transactions On Biomedical Engineering, 43 (1), 734-742.
• Soltani, S., 2002, On the use of the wavelet decomposition for time series prediction, Neurocomputing, 48, 267–277. C., orange.fr/clemens/wavelets/wavelets.html, [Ziyaret Tarihi: 20.08.2015] friendly guide to wavelets,
• http://polyvalens.pagesperso
• Zhang, D., He, J., Yao, J., Wu, Z., Du, M., “Spectral analysis of heart sounds produced by disorder mechanical prosthetic heart valves”, 2nd International Conference on Biomedical Engineering and Informatics, BMEI’09, 17-19 Oct. 2009, Tianjin, China.