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Heart Sound: Detection and Analytical Approach Towards Diseases

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Part of the book series: Smart Sensors, Measurement and Instrumentation ((SSMI,volume 29))

Abstract

Usually, physicians use an acoustic stethoscope to detect abnormalities in the heart sound and predict abnormal conditions of the human heart. As the frequency range and intensity of heart sound is very low, doctors are facing problems while detecting the cardiac sound and its abnormalities. To eradicate these severe problems, it is required to design and develop an electronic stethoscope which would assist the doctor to analyze heart sound and to detect disease of the heart. Here an acoustic stethoscope along with microphone and preamplifier module is used to increase the amplitude of the input audio signal received by the stethoscope. The soft scope of MATLAB program has also been used for analyzing the continuous set of cardiac sound and to detect its various characteristics like frequency, amplitude, etc. It is aimed to design an electronic stethoscope which would assist the doctors to analyze heart sound and identify a disease condition of the heart, but preliminarily we have achieved to detect different components of it which are lub (s1), dub (s2), s3, s4, etc. Finally, the sound signal received from the heart in the MATLAB program after filtering the noise out of it also has been plotted and analyzed in the frequency domain. As the heart sound is a complex waveform signal, harmonic distribution is used. Amplitude and phase are the two essential parameters. Thus the harmonic distribution of Amplitude and Phase are carried out. Amplitude Distribution of harmonics leads to some crucial characteristics features like RMS Value, Mean Value, Average Energy, Average Power, Mean Squared Error, Spectrogram Analysis, Periodogram Analysis, and Kalman Filtered Response. These features will readily identify and distinguish between Normal heart sound, abnormal heart sound and cardiac murmurs in Matlab programming.

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References

  1. https://www.ukessays.com/essays/engineering/pest-detection-leafs-using-robot-processing-4110.php

  2. L.-G. Durand, Y.-E. Langlois, T. Lanthier, R. Chiarella, P. Coppens, S. Carioto, S. Bertrand-Bradley, Spectral analysis and acoustic transmission of mitral and aortic valve closure sounds in dogs. Med. Biol. Eng. Comput. 28(5), 439–445 (1990)

    Article  Google Scholar 

  3. World Health Organization, Global status report on noncommunicable diseases 2014 (2014)

    Google Scholar 

  4. A. Leatham, Auscultation and phonocardiography: a personal view of the past 40 years. Br. Heart J. 57, 397–403 (1987)

    Article  Google Scholar 

  5. J.R. Kindig, et al., Acoustical performance of the stethoscope: a comparative analysis. Am. Heart J. 104(2 Pt 1), 269–275 (1982); S. Lukkarinen, et al., A new phonocardiographic recording system. Comput. Cardiol. 24, 117–120 (1997)

    Google Scholar 

  6. D.A. Balster et al., Digital acoustic analysis of precordial innocent versus ventricular septal defect murmurs in children. Am. J. Cardiol. 79(11), 1552–1555 (1997)

    Article  Google Scholar 

  7. R.M. Rangayyan, R.J. Lehner, Phonocardiogram signal analysis: a review. Crit. Rev. Biomed. Eng. 15(3), 211–236 (1987)

    Google Scholar 

  8. https://www.gadgetsnow.com/tech-news/Govt-plans-Rs-10000cr-fund-to-create-tech-giants/articleshow/45041502.cms

  9. J.R. Bulgrin et al., Comparison of short-time Fourier, wavelet and time-domain analyses of intracardiac sounds. Biomed. Sci. Instrum. 29, 465–472 (1993)

    Google Scholar 

  10. P. Bentley, G. Nordehn, M. Coimbra, S. Mannor, R. Getz, Classifying heart sounds challenge. http://www.peterjbentley.com/heartchallenge/#downloads

  11. M. Abella, J. Formolo, D.G. Penney, Comparison of the acoustic properties of six popular stethoscopes. J. Acoust. Soc. Am. 91(4 Pt 1), 2224–2228 (1992)

    Article  Google Scholar 

  12. Y. Wapcaplet, Diagram of the human heart (2003) (Online). http://commons.wikimedia.org/wiki/File:Diagram_of_the_human_heart_(cropped).svg

  13. Anju, S. Kumar, Detection of cardiac murmur. Int. J. Comput. Sci. Mob. Comput. 3(7), 81–87 (2014). ISSN 2320–088X

    Google Scholar 

  14. B. Popov, G. Sierra, L.G. Durand, J. Xu, P. Pibarot, R. Agarwal, V. Lanzo, Automated extraction of aortic and pulmonary components of the second heart sound for the estimation of pulmonary artery pressure, in Proceedings of IEEE Engineering in Medicine and Biology Society, vol. 2, pp. 921–924 (2004)

    Google Scholar 

  15. Cardiac cycle, https://en.wikipedia.org/wiki/Cardiac_cycle

  16. M. Tavel, Classification of systolic murmurs: still in search of a consensus. Am. Heart J. 134(2), 330–336 (1997)

    Article  Google Scholar 

  17. C. Cortes, V. Vapnik, Support-vector networks. Mach. Learn. 20(3), 273–297 (1995)

    MATH  Google Scholar 

  18. Heart murmur, National Heart & Blood Institute, https://www.nhlbi.nih.gov/health/health-topics/topics/holes/types

  19. Z. Syed, D. Leeds, D. Curtis, F. Nesta, R.A. Levine, J. Guttag, A framework for the analysis of acoustical cardiac signals. IEEE Trans. Biomed. Eng. 54(4), 651–662 (2007)

    Google Scholar 

  20. H. Liang, I. Hartimo, A heart sound feature extraction algorithm based on wavelet decomposition and reconstruction, in Proceedings of 20th Annual International Conference IEEE Engineering in Medicine and Biology Society, vol. 20; Biomed. Eng. 3(3), 1539–1542 (1998), Towards Year 2000 Beyond (Cat. No. 98CH36286)

    Google Scholar 

  21. Z. Xiu-min, C. Gui-tao, A novel de-noising method for heart sound signal using improved thresholding function in wavelet domain, in 2009 International Conference on Future BioMedical Information Engineering (FBIE), pp. 65–68 (2009)

    Google Scholar 

  22. D.L. Donoho, De-noising by soft-thresholding. IEEE Trans. Inf. Theory 41(3), 613–627 (1995)

    Google Scholar 

  23. A. Zaeemzadeh, Z. Nafar, S.-K. Setarehdan, Heart sound segmentation based on recurrence time statistics, in 2013 20th Iranian Conference on Biomedical Engineering (ICBME), no. Icbme, pp. 215–218 (2013)

    Google Scholar 

  24. T.-H. Hung, C.-C. Chou, W.-C. Fang, A.H.-T. Li, Y.-C. Chang, B.-K. Hwang, Y.-W. Shau, Time-frequency analysis of heart sound signals based on Hilbert-Huang transformation, in 2012 IEEE 16th International Symposium on Consumer Electronics, pp. 1–3 (2012)

    Google Scholar 

  25. M. Singh, A. Cheema, Heart sounds classification using feature extraction of phonocardiography signal. Int. J. Comput. Appl. 77(4), 975–8887 (2013)

    Google Scholar 

  26. H. Nygaard et al., Assessing the severity of aortic valve stenosis by spectral analysis of cardiac murmurs (spectral vibrocardiography). Part II: Clinical aspects. J. Heart Valve Dis. 2(4), 468–475 (1993)

    Google Scholar 

  27. R.-E. Fan, P.-H. Chen, C.-J. Lin, Working set selection using second order information for training support vector machines. J. Mach. Learn. Res. 6, 1889–1918 (2005)

    MathSciNet  MATH  Google Scholar 

  28. D.B. Springer, L. Tarassenko, G.D. Clifford, Support vector machine hidden semi-Markov model-based heart sound segmentation time, in Computing in Cardiology (2014)

    Google Scholar 

  29. H.L. Baranek et al., Automatic detection of sounds and murmurs in patients with Ionescu-Shiley aortic bioprostheses. Med. Biol. Eng. Comput. 27(5), 449–455 (1989)

    Article  Google Scholar 

  30. Review on heart sound analysis technique. SpringerLink, https://link.springer.com/chapter/10.1007/978-81-322-1299-7_9

  31. Heart sounds—Wikipedia, https://en.wikipedia.org/wiki/Heart_sounds

  32. Heart sounds classification using feature extraction of …, https://pdfs.semanticscholar.org/73a7/3eb140b1f7b496f801d697174392c172c55c.pdf

  33. Recent advances in heart sound analysis—Physiological …, http://iopscience.iop.org/journal/0967-3334/page/Recent-advances-in-heart-sound-analysis

  34. J.K. Roy, T.S. Roy, A simple technique for heart sound detection and real time analysis, in Proceedings of ICST 2017, 2017 Eleventh International Conference on Sensing Technology (ICST) held at Maquare University Sidney, 4–6 Dec 2017, https://doi.org/10.1109/icsenst.2017.8304502

  35. A. Iwata et al., Algorithm for detecting the first and the second heart sounds by spectral tracking. Med. Biol. Eng. Comput. 18(1), 19–26 (1980)

    Article  Google Scholar 

  36. The Second Heart Sound—Clinical Methods—NCBI Bookshelf, https://www.ncbi.nlm.nih.gov/books/NBK341/

  37. Harvard Health Publishing, https://www.health.harvard.edu/heart-health/heart-valve-problems

  38. A Kalman Filtering Tutorial For Undergraduate Students, http://aircconline.com/ijcses/V8N1/8117ijcses01.pdf

  39. Heart murmur causes, https://www.nhlbi.nih.gov/health/health-topics/topics/heartmurmur/causes

  40. M. El-Segaier, O. Lilja, S. Lukkarinen, L. Sörnmo, R. Sepponen, E. Pesonen, Computer-based detection and analysis of heart sound and murmur, Ann. Biomed. Eng. 33(7), 937–942 (2005), http://www.ncbi.nlm.nih.gov/pubmed/16060534

  41. S.M. Debbal, Computerized heart sound analysis. Genie—Biomedical Laboratory (GBM), Department of electronic, Faculty of science engineering, University of Abou Bekr Belkaid, Algeria

    Google Scholar 

  42. R.L. Donnerstein, Continuous spectral analysis of heart murmurs for evaluating stenotic cardiac lesions. Am. J. Cardiol. 64(10), 625–630 (1989)

    Article  Google Scholar 

  43. B. Maurice, E.E. Rappaport, B. Haward, M.D. Sprague, The acoustic stethoscope and the electrical amplifying stethoscope and stethograph. Am. Heart J. 21(3), 257–318 (1940)

    Google Scholar 

  44. M. Nygards, L. Sornmo, Delineation of the QRS complex using the envelope of the E.C.G. Med. Biol. Eng. Comput. 21(5), 538–547 (1983)

    Google Scholar 

  45. H. Nygaard et al., Assessing the severity of aortic valve stenosis by spectral analysis of cardiac murmurs (spectral vibrocardiography). Part I: Technical aspects. J. Heart Valve Dis. 2(4), 454–467 (1993)

    Google Scholar 

  46. J.D. O’Toole et al., The mechanism of splitting of the secondheart sound in atrial septal defect. Circulation 56(6), 1047–1053 (1977)

    Article  Google Scholar 

  47. Gallop rhythm, https://en.wikipedia.org/wiki/Heart_sounds

  48. Cardiac sound generation, http://www.wisegeek.com/what-are-different-types-of-heart-sounds.htm#

  49. The circulatory system, http://lsa.colorado.edu/essence/texts/heart.html#Structure

  50. Pinterest, https://in.pinterest.com/pin/407505466254590427/?autologin=true

  51. Stethoscope, https://en.wikipedia.org/wiki/Stethoscope

  52. D. Gede, H. Wisana, Design electronic stethoscope for cardiac auscultation analyzed using wavelet decomposition. Int. J. Comput. Netw. Commun. Secur. 1(7), 310–315 (2013), www.ijcncs.org. ISSN 2308-9830

  53. K. Singh, P. Abrol, Design and development of a digital stethoscope for cardiac murmur. Int. J. Comput. Appl. (0975–8887) 73(22) (2013)

    Google Scholar 

  54. M. Singh, A. Cheema, Heart sounds classification using feature extraction of phonocardiography signal. Int. J. Comput. Appl. (0975–8887) 77(4) (2013)

    Google Scholar 

  55. D.D. Kadam Patil, R.K. Shastri, Design of wireless electronic stethoscope based on ZIGBEE, Cornell University Library, https://arxiv.org/abs/1202.1680

  56. L.B. Dahl, P. Hasvold, E.Arild, T. Hasvold, Heart murmurs recorded by a sensor based electronic stethoscope and e-mailed for remote assessment, Arch. Dis. Child 87, 297–301, 19 March 2002

    Google Scholar 

  57. W.W. Myint, B. Dillard, An electronic stethoscope with diagnosis capability. Department of Electrical & Computer Eng., Auburn University, College of Engineering, Auburn, AL 36849 USA

    Google Scholar 

  58. https://datasheets.maximintegrated.com/en/ds/MAX9812-MAX9813L.pdf

  59. http://telehealthtechnology.org/toolkits/electronic-stethoscopes/about-electronic-stethoscopes/technology-overview

  60. J. Peter Robinson, Digital electronic stethoscopes. 3 M Healthcare Ltd, Loughborough, UK

    Google Scholar 

  61. History of the Stethoscope—American Diagnostic Corporation, https://www.adctoday.com/learning-center/about-stethoscopes/history-stethoscope

  62. Introduction to Digital Stethoscopes and Electrical …, https://pdfserv.maximintegrated.com/en/an/AN4694.pdf

  63. Automatic detection of sounds and murmurs …. SpringerLink, https://link.springer.com/article/10.1007/BF02441460

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Correspondence to Joyanta Kumar Roy .

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Roy, J.K., Roy, T.S., Mukhopadhyay, S.C. (2019). Heart Sound: Detection and Analytical Approach Towards Diseases. In: Mukhopadhyay, S., Jayasundera, K., Postolache, O. (eds) Modern Sensing Technologies . Smart Sensors, Measurement and Instrumentation, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-319-99540-3_7

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  • DOI: https://doi.org/10.1007/978-3-319-99540-3_7

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