Abstract
Currently, the fatality of cardiovascular diseases (CVDs) represents one of the global primary healthcare challenges and necessitates broader population checking for earlier intervention. The traditional auscultation is cost-effective and time-saving for broader population to diagnose CVDs early. While many approaches in analyzing heart sound (HS) signal from auscultation have been utilized successfully, few studies are focused on acoustic perspective to interpret the HS signal. This paper proposes a segmentation-free model that can interpret HS effectively, which aligns engineering with clinical diagnostic basis and medical knowledge much more. The presented model stems from timbre analysis model but is adapted for HS signal. The relevant theoretical analysis and simulation experiments indicate that the proposed method has good performance in HS analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Heidenreich, P.A.: Forecasting the Future of Cardiovascular Disease in the United States (2011)
Dokur, Z.: Dimension Reduction by a Novel Unified Scheme Using Divergence Analysis and Genetic Search. Digital Signal Processing 19, 521–531 (2009)
Liang, H., Hartimo, I.: Feature extraction algorithm based on wavelet packet decomposition for heart sound signals. Presented at the Proceedings of the IEEE-SP International Symposium (1998)
Vikhe, P., Hamde, S., Nehe, N.: Wavelet Transform Based Abnormality Analysis of Heart Sound. In: Proc. ACT 9th. International Conf. Advances in Computing, Control, & Telecommunication Technologies, pp. 367–371 (2009)
Kao, W., Wei, C., Liu, J., Hsiao, P.: Automatic Heart Sound Analysis with Short-time Fourier Transforms and Support Vector Machines. In: Proc. MWSCAS 9th IEEE International Midwest Symp. Circuits and Systems, August 2-5, pp. 188–191 (2009)
Djebbari, A., Bereksi, F.: Short-time Fourier Transform Analysis of the Phonocardiogram Signal. In: Proc. 7th IEEE International Conf. Electronics, Circuits and Systems, pp. 844–847 (2000)
Hadi, H.M., Mashor, M.Y., Suboh, M.Z., Mohamed, M.S.: Classification of Heart Sound Based on S-transform and Neural Network. Presented in 10th International Conference, 10-13 (2010)
Varanini, M., De Paolis, G., Emdin, M., Macerata, A., Pola, S., Cipriani, M., Marchesi, C.: Spectral Analysis of Cardiovascular Tme Series by theS-Transform. In: Computers in Cardiology, pp. 383–386 (1997)
Sunita, C., et al.: A computer-aided MFCC-based HMM system for automatic auscultation. Computers in Biology and Medicine 38, 221–233 (2008)
Wenjie, F., Yang, X., Wang, Y.: Heart sound diagnosis based on DTW and MFCC. In: Proc. 3rd International Congress, vol. 6, pp. 2920–2923 (2010)
Kamarulafiza, I., et al.: Heart Sound Analysis Using MFCC and Time Frequency Distribution. In: World Congress on Medical Physics and Biomedical Engineering 2006. Springer, Heidelberg (2007)
Grey, J.: An exploration of musical timbre. Ph.D. dissertation (Dept. of Music Report No. STAN-M-2, Stanford University, CA) (1975) (unpublished)
Lakatos, S.: A Common Perceptual Space for Harmonic and Percussive Timbres. Perception & Psychophysics 62, 1426–1439 (2000)
McAdams, S.: Perspectives on the Contribution of Timbre to Music Structure. Computer Music Journal 23, 85–102 (1999)
Gianpaolo Evangelista, H.V.: Separation of Harmonic Instruments with Overlapping Partialsin Muti-channel Mixtures. In: IEEE Workshop an Applications of Signal Prwessinp to Audio and Acoustics (2003)
Jensen, K.: Timbre Models of Musical Sounds. Nr. 99/7 (1999) ISSN 0107-8283
Caclin, A., McAdams, S., Bennett, K.: Smith, S.Winsberg.: Acoustic Correlates of Timbre Space Dimensions: A Confirmatory Study Using Synthetic Tones. Acoustical of Society Amecia 118, 471 (2005)
Altman, N.S.: An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression. The American Statistician 46(3), 175–185 (1992)
Egeneral Medical, http://www.egeneralmedical.com/listohearmur.html
Wang, H.Y., Li, G.P., Fu, B.B., Huang, J., Dong, M.C.: Multidimensional Feature Extraction Based on Timbre Model for Heart Sound Analysis. International Journal of Bioscience, Biochemistry and Bioinformatics 4(5), 318–321 (2014) ISSN: 2010-3638
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Wang, HY., Li, GP., Fu, BB., Yao, HD., Dong, MC. (2015). A Segmentation-Free Model for Heart Sound Feature Extraction. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2015. Lecture Notes in Computer Science(), vol 9043. Springer, Cham. https://doi.org/10.1007/978-3-319-16483-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-16483-0_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16482-3
Online ISBN: 978-3-319-16483-0
eBook Packages: Computer ScienceComputer Science (R0)