Abstract
This paper highlights in the field of advancement in heart sound diagnosis techniques. An important and huge amount of work has been performed in the domain of feature extraction and classification techniques of heart Sound. It is difficult for a physician to detect very feeble sound of diseased heart valve such as murmur using the regular stethoscope. The prediction of abnormal conditions of the human heart needs lots of hearing experience of a practicing doctor. In this research, the K-Mean Clustering, feature extraction, and classification techniques of heart Sound were investigated, which provides a better way of study of PCG Signals which at the end of the day proves to be very cost effective and compact. Discrete Wavelet Transform (DWT) also plays a vital role in feature extraction method. This paper can be used as a primary reading material for researchers doing research on PCG Signal 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
References
Randhawa, S.K., Singh, M.: Classification of heart sound signals using multimodal features. In: Second International Symposium on Computer Vision and the Internet, vol. 58, pp. 165–171. Elsevier, Amsterdam (2015)
Roy, J.K., Roy, T.S., Mandal, N., Postolache, O.A.: A Simple technique for heart sound detection and identification using Kalman filter in real-time analysis. In: ISSI 2018, First International Conference, 6–7 Sept 2018. 978-1-5386-5638-9/18/$31.00 ©2018 IEEE
Gupta, C.N., Palaniappan, R., Rajan, S., Swaminathan, S., Krishnan, S.M.: Segmentation and classification of heart sounds. In: International Conference: Canadian Conference on Electrical and Computer Engineering, June 2005. https://doi.org/10.1109/CCECE.2005.1557305
Roy, J.K., Roy, T.S.: A simple technique for heart sound detection and real-time analysis. In: Proceedings of ICST 2017 held at Macquarie University Sidney, Sensing Technology (ICST), 2017 Eleventh International Conference, 4–6 Dec 2017. https://doi.org/10.1109/ICSensT.2017.8304502
Roy, JU.K., Roy, T.S., Mukhopadhyay, S.C.: Heart sound: detection and analytical approach towards diseases. In: Mukhopadhyay, S.C. (eds.) Modern Sensing Technologies, pp. 103–145. Springer Nature, Switzerland. https://doi.org/10.1007/978-3-319-99540-3_7
Cardiac cycle, https://en.wikipedia.org/wiki/Cardiac_cycle
Amarnath, R.: Methods for classification of phonocardiogram. TENCON2003. In: Conference on Convergent Technologies for the Asia-Pacific Region 2003, vol. 4, pp. 1514–1515
Liang, H., Hartimo, I.: A heart sound feature extraction algorithm based on wavelet decomposition and reconstruction. In: Proceedings of 20th Annual International Conference on IEEE Engineering in Medicine and Biology Society, vol. 20, pp. 1539–1542 (1998)
Anju, Kumar, S.: Detection of Cardiac Murmur. Int J Comput Sci Mobile Comput 3(7):81–87. ISSN 2320–088X
Heart sounds - Wikipedia. https://en.wikipedia.org/wiki/Heart_sounds
Heart murmur causes, https://www.nhlbi.nih.gov/health/health-topics/topics/heartmurmur/causes
Dewangan, N.K., Shukla, S.P., Dewangan, K.: PCG signal analysis using discrete wavelet transform. Int. J. Adv. Manag. Technol. Eng. Sci. 8(III) (2018). ISSN NO: 2249–7455
Venkata Hari Prasad, G., Rajesh Kumar, P.: Analysis of various DWT methods for feature extracted PCG signals. Int. J. Eng. Res. Technol. (IJERT) 4(04) (2015). ISSN: 2278-0181
Roy, A.K., Misal, A., Sinha, G.R.: Classification of PCG signals: a survey. Int. J. Comput. Appl. Recent Adv. Inform. Technol. (2014). ISSN NO: 0975-8887
Mishra, G., Biswal, K., Mishra, A.K.: Denoising of heart sound signal using wavelet transform. Int. J. Res. Eng. Technol. 02(04) (2013). ISSN: 2319-1163
Singh, M., Cheema, A.: Heart sounds classification using feature extraction of phonocardiography signal. Int. J. Comput. Appl. 77 (4) (2013). ISSN NO:0975-8887
Liang, H., Lukkarinen, S., Hartimo, I.: Heart sound segmentation algorithm based on heart sound envelogram. Comput. Cardiol. 24(7), 105–108 (1997)
Misal, A., Sinha, G.R.: Denoising of PCG signal by using wavelet transforms. J. Adv. Comput. Res. 4(1), 46–49 (2012) ISSN: 0975-3273 & E-ISSN: 0975-9085
Muruganantham (2003) Methods for classification of phonocardiogram. TENCON (2003)
Debbal, S., Bereksi-Reguig, F.: Graphic representation and analysis of the PCG signal using the continuous wavelet transform. Internet J. Bioeng. 2(2)
Javed, F., Venkatachalam, P.A., Ahmad Fadzil, M.H.: A signal processing module for the analysis of heart sounds and heart murmurs. J. Phys. Conf. Ser. 34, 1098–1105 (2006)
Janse, V., Magre, S.B., Kurzekar, P.K., Deshmukh, R.R.: A comparative study between MFCC and DWT feature extraction technique, vol. 3(1), pp. 3124–3127
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Roy, T.S., Roy, J.K., Mandal, N. (2022). A Study of Phonocardiography (PCG) Signal Analysis by K-Mean Clustering. In: Mandal, J.K., Roy, J.K. (eds) Proceedings of International Conference on Computational Intelligence and Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-3368-3_16
Download citation
DOI: https://doi.org/10.1007/978-981-16-3368-3_16
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-3367-6
Online ISBN: 978-981-16-3368-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)