Abstract
It has been reported that heart sound detection is very useful in the diagnostic process of heart diseases, especially in patients with abnormality of the cardiac valves. Heart sounds originate from blood flow through the cardiac valves during heart contraction and relaxation, and they can be heard and recorded in the patient’s chest. In this study, two groups of patients, those with normal hearts and those with aortic stenosis, were investigated. This paper presents the application of wavelet transform analysis to the heart sound signals of both groups. The continuous wavelet transform plot shows that the patients with aortic stenosis are likely to have irregular patterns of heart sounds in a time-scale representation, whereas normal heart sounds are likely to have relatively smooth surfaces. The wavelet entropy is then applied to the heart sounds. A disordered signal gives a high entropy value. Observations of the preliminary results in this study found that the heart sounds from patients with aortic stenosis tend to have higher wavelet entropy than those from patients with normal hearts.
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References
Brusco M, Nazeran H (2004) Digital phonocardiography: a PDA-based approach. In: Proceedings of the 26th annual international conference of the IEEE EMBS, pp 2299–2302
Bunluechokchai S, English MJ (2003) Detection of wavelet transform-processed ventricular late potentials and approximate entropy. IEEE computers in cardiology, pp 549–552
Bunluechokchai S, English MJ (2003) Analysis of the high resolution ECG with the continuous wavelet transform. IEEE computers in cardiology, pp 553–556
Djebbari A, Reguig B (2002) Short-time Fourier transform analysis of the phonocardiogram signal. In: The 7th IEEE international conference on electronics, circuits and systems, pp 844–847
Durand LG and Pibarot P (1995) Digital signal processing of the phonocardiogram: review of the most recent advancements. Crit Rev Biomed Eng163–219
Kumar P, Carvalho M, Antunes M, Gil P, Henriques J, Eugenio L (2006) A new algorithm for detection of S1 and S2 heart sounds. In: IEEE international conference on acoustic, speech, and signal processing ICASSP, pp 1180–1183
Mgdob HM, Torry JN, Vincent R, Al-Naami B (2003) Application of Morlet transform wavelet in the detection of paradoxical splitting of the second heart sound. IEEE computers in cardiology, pp 323–326.
Omran S, Tayel M (2004) A heart sound segmentation and feature extraction algorithm using wavelets. In: First international symposium on control, communications and signal processing, pp 235–238
Tovar-Corona B, Torry JN (1998) Time-frequency representation of systolic murmurs using wavelets. IEEE computers in cardiology, pp 601–604
Zhidong Z, Zhijin Z, Yuquan C (2005) Time-frequency analysis of heart sound based on HHT. In: IEEE international conference on communications, circuits and systems, pp 926–929
Zin ZM, Salleh SH, Daliman S, Sulaiman MD (2003) Analysis of heart sounds based on continuous wavelet transform. In: IEEE conference on research and development, pp 19–22
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Bunluechokchai, S., Tosaranon, P. (2009). Analysis of Heart Sounds with Wavelet Entropy. In: Mastorakis, N., Mladenov, V., Kontargyri, V. (eds) Proceedings of the European Computing Conference. Lecture Notes in Electrical Engineering, vol 27. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-84814-3_72
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DOI: https://doi.org/10.1007/978-0-387-84814-3_72
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