Table of Contents Author Guidelines Submit a Manuscript
Journal of Healthcare Engineering
Volume 3, Issue 1, Pages 125-139
http://dx.doi.org/10.1260/2040-2295.3.1.125
Research Article

Intelligent Identification of Childhood Musical Murmurs

Yuerong Chen, Shengyong Wang, Chia-Hsuan Shen, and Fred K. Choy

Department of Mechanical Engineering, University of Akron, Akron, Ohio, USA

Received 1 March 2011; Accepted 1 August 2011

Copyright © 2012 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Heron, D. Hoyert, S. Murphy, J. Xu, K. Kochanek, and B. Tejada-Vera, “Deaths: Final Data for 2006,” National Vital Statistics Reports, vol. 57, no. 14, 2009. View at Google Scholar
  2. D. Lloyd-Jones, R. Adams, T. Brown et al., “Heart Disease and Stroke Statistics—2010 Update: a Report from the American Heart Association,” Circulation, vol. 121, no. 7, pp. e46–e215, 2010. View at Google Scholar
  3. W. Myint and B. Dillard, “An electronic stethoscope with diagnosis capability,” in Conf Proc the 33rd Southeastern Symposium on System Theory, pp. 133–137, 2001.
  4. A. Tilkian and M. Conover, Understanding Heart Sounds and Murmurs: with an Introduction to Lung Sounds, Saunders, Philadelphia, 4th edition, 2001.
  5. A. Pelech, “The Physiology of Cardiac Auscultation,” Pediatric Clinics of North Amrica, vol. 51, pp. 1515–1535, 2004. View at Google Scholar
  6. A. Noponen, S. Lukkarinen, A. Angerla, K. Sikio, and R. Sepponen, “How to Recognize the Innocent Vibratory Murmur?” Computers in Cardiology, vol. 27, pp. 561–564, 2000. View at Google Scholar
  7. B. McCrindle, K. Shaffer, J. Kan, K. Zahka, S. Rowe, and I. Kidd, “An Evaluation of Parental Concerns and Misperceptions about Heart Murmurs,” Clin Pediatr, vol. 34, pp. 25–31, 1995. View at Google Scholar
  8. R. Geggel, L. Horowitz, E. Brown, M. Parsons, P. Wang, and D. Fulton, “Parental Anxiety Associated with Referral of a Child to a Pediatric Cardiologist for Evaluation of a Still's Murmur,” J Pediatr, vol. 140, pp. 747–752, 2002. View at Google Scholar
  9. I. Haney, M. Ipp, W. Feldmen, and B. McCrindle, “Accuracy of Clinical Assessment of Heart Murmurs by Office Based (General Practice) Paediatricians,” Arch Dis Child, vol. 81, no. 5, pp. 409–412, 1999. View at Google Scholar
  10. P. Gaskin, S. Owens, N. Talner, S. Sanders, and J. Li, “Clinical Auscultation Skills in Pediatric Residents,” Pediatrics, vol. 105, pp. 1184–1187, 2000. View at Google Scholar
  11. J. Vukanovic-Criley, S. Criley, C. Warde et al., “Competency in Cardiac Examination Skills in Medical Students, Trainees, Physicians, and Faculty: a Multicenter Study,” Arch Intern Med, vol. 166, pp. 610–616, 2006. View at Google Scholar
  12. A. Pease, “If the Heart could Speak. Pictures of the Future,” 2001, 60-61.
  13. E. Etchells, C. Bell, and K. Robb, “Does this Patient have an Abnormal Systolic Murmur?” JAMA, vol. 277, pp. 564–571, 1997. View at Google Scholar
  14. A. Noponen, S. Lukkarinen, A. Angerla, and R. Sepponen, “Phono-spectrographic Analysis of Heart Murmur in Children,” BMC Pediatrics, vol. 7:23, 2007. View at Google Scholar
  15. W. Thompson, C. Hayek, C. Tuchinda, J. Telford, and J. Lombardo, “Automated Cardiac Auscultation for Detection of Pathologic Heart Murmurs,” Pediatr Cardiol, vol. 22, pp. 373–379, 2001. View at Google Scholar
  16. N. Andrisevic, K. Ejaz, F. Rios-Gutierrez, R. Alba-Flores, G. Nordehn, and S. Burns, “Detection of Heart Murmurs Using Wavelet Analysis and Artificial Neural Networks,” Journal of Biomedical Engineering, vol. 127, no. 6, pp. 899–904, 2005. View at Google Scholar
  17. S. Strunic, F. Rios-Gutierrez, R. Alba-Flores, G. Nordehn, and S. Burns, “Detection and classification of cardiac murmurs using segmentation techniques and artificial neural networks,” in Conf Proc IEEE Symposium on Computational Intelligence and Data Mining, pp. 397–404, 2007.
  18. C. Ahlstrom, P. Hult, P. Rask et al., “Feature Extraction for Systolic Heart Murmur Classification,” Annals of Biomedical Engineering, vol. 34, no. 11, pp. 1666–1677, 2006. View at Google Scholar
  19. J. de Vos and M. Blanckenberg, “Automated Pediatric Cardiac Auscultation,” IEEE Transactions on Biomedical Engineering, vol. 54, no. 2, pp. 244–252, 2007. View at Google Scholar
  20. P. White, W. Collis, and A. Salmon, “Analysing heart murmurs using time-frequency methods,” in Conf Proc IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis, pp. 385–388, Paris, France, 1996.
  21. Z. Sharif, M. Zainal, A. Sha'ameri, and S. Salleh, “Analysis and classification of heart sounds and murmurs based on the instantaneous energy and frequency estimations,” in Conf Proc Tencon, vol. 2, pp. 130–134, Kuala Lumpur, Malaysia, 2000.
  22. S. Omran and M. Tayel, “A heart sound segmentation and feature extraction algorithm using wavelets,” in Conf Proc the First International Symposium on Control, Communications and Signal Processing, pp. 235–238, 2004.
  23. C. Ahlstrom, K. Höglund, P. Hult, J. Häggström, C. Kvart, and P. Ask, “Distinguishing Innocent Murmurs from Murmurs Caused by Aortic Stenosis by Recurrence Quantification Analysis,” International Journal of Biomedical Sciences, vol. 1, no. 1, pp. 213–218, 2006. View at Google Scholar
  24. T. Reed, N. Reed, and P. Fritzson, “Heart Sound Analysis for Symptom Detection and Computer-Aided Diagnosis,” Simulation Modelling Practice and Theory, vol. 12, pp. 129–146, 2004. View at Google Scholar
  25. T. Ölmez and Z. Dokur, “Classification of Heart Sounds Using an Artificial Neural Network,” Pattern Recognition Letters, vol. 24, pp. 617–629, 2003. View at Google Scholar
  26. C. Gupta, R. Palaniappan, S. Swaninathan, and S. Krishnan, “Neural Network Classification of Homomorphic Segmented Heart Sounds,” Applied Soft Computing, vol. 7, pp. 286–297, 2007. View at Google Scholar
  27. Ears On!, http://earson.ca/what.html, Accessed Dec 5, 2011.
  28. S. Ari and G. Saha, “In Search of an Optimization Technique for Artificial Neural Network to Classify Abnormal Heart Sounds,” Applied Soft Computing, vol. 9, pp. 330–340, 2009. View at Google Scholar
  29. M. Vetterli and J. Kovačević, Wavelets and Subband Coding, Prentice Hall, New Jersey, 1995.
  30. H. Hassanpour, M. Mesbah, and B. Boashash, “Time-Frequency Feature Extraction of Newborn EEG Seizure Using SVD-Based Techniques,” EURASIP Journal on Applied Signal Processing, vol. 16, pp. 2544–2554, 2004. View at Google Scholar
  31. G. Nakos and D. Joyner, Linear Algebra with Applications, Brooks/Cole Publishing Company, Pacific Grove, California, 1998.
  32. S. Theodoridis and K. Koutroumbas, Pattern Recognition, Academic Press, 4th edition, 2009.
  33. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, 2001.
  34. O. Doyle, A. Temko, W. Marnane, G. Lightbody, and G. Boylan, “Heart Rate Based Automatic Seizure Detection in the Newborn,” Medical Engineering & Physics, vol. 32, pp. 829–839, 2010. View at Google Scholar
  35. H. Cao, L. J. Eshelman, L. Nielsen, B. D. Gross, M. Saeed, and J. J. Frassica, “Hemodynamic Instability Prediction through Continuous Multiparameter Monitoring in ICU,” Journal of Healthcare Engineering, vol. 1, no. 4, pp. 509–534, 2010. View at Google Scholar