Skip to main content

Computer-Aided Diagnosis of Laryngopathies in the LabVIEW Environment: Exemplary Implementation

  • Chapter
Advances in Intelligent Analysis of Medical Data and Decision Support Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 473))

  • 1311 Accesses

Abstract

In the paper, we present a computer tool supporting a non-invasive diagnosis of selected larynx diseases. The tool is created on the basis of the LabVIEW environment. LabVIEW enables us to create, in an easy way, a user-friendly graphical interface facilitating both entering input data and visualizing results in order to make the platform ready to use directly in the medical community. Computer-aided diagnosis of laryngopathies, in the presented tool, is based on a family of coefficients reflecting spectrum disturbances around basic tones and their multiples for patients’ voice signals.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. LabVIEW, http://www.ni.com/labview/

  2. Multi-Dimensional Voice Program, MDVP (2011), http://www.kayelemetrics.com

  3. Bazan, J.G., Nguyen, H.S., Nguyen, S.H., Synak, P., Wroblewski, J.: Rough set algorithms in classification problem. In: Polkowski, L., Tsumoto, S., Lin, T.Y. (eds.) Rough Set Methods and Applications, pp. 49–88. Physica-Verlag, Heidelberg (2000)

    Chapter  Google Scholar 

  4. Bazan, J., Szczuka, M.S.: The Rough Set Exploration System. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III. LNCS, vol. 3400, pp. 37–56. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  5. Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Chapman & Hall, Boca Raton (1993)

    Google Scholar 

  6. Gelzinis, A., Verikas, A., Bacauskiene, M.: Automated speech analysis applied to laryngeal disease categorization. Computer Methods and Programs in Biomedicine 91(1), 36–47 (2008)

    Article  Google Scholar 

  7. Greenes, R.: Clinical Decision Support: The Road Ahead. Elsevier (2007)

    Google Scholar 

  8. Grzymala-Busse, J.: A new version of the rule induction system LERS. Fundamenta Informaticae 31, 27–39 (1997)

    MATH  Google Scholar 

  9. Hippe, Z.: Machine learning – a promising strategy for business information processing? In: Abramowicz, W. (ed.) Business Information Systems, pp. 603–622. Academy of Economics Editorial Office, Poznan (1997)

    Google Scholar 

  10. Pancerz, K., Paja, W., Szkola, J., Warchol, J., Olchowik, G.: A rule-based classification of laryngopathies based on spectrum disturbance analysis - an exemplary study. In: Van Huffel, S., et al. (eds.) Proc. of the BIOSIGNALS 2012, Vilamoura, Algarve, Portugal, pp. 458–461 (2012)

    Google Scholar 

  11. Pancerz, K., Szkola, J., Warchol, J., Olchowik, G.: Spectrum disturbance analysis for computer-aided diagnosis of laryngopathies: An exemplary study. In: Proc. of the International Workshop on Biomedical Informatics and Biometric Technologies (BT 2011), Slovak Republic, Zilina (2011)

    Google Scholar 

  12. Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about. Data. Kluwer Academic Publishers, Dordrecht (1991)

    Book  MATH  Google Scholar 

  13. Quinlan, J.: C4.5. Programs for machine learning. Morgan Kaufmann Publishers (1993)

    Google Scholar 

  14. Semmlow, J.: Biosignal and Medical Image Processing. CRC Press (2009)

    Google Scholar 

  15. Szkola, J., Pancerz, K., Warchol, J.: Computer diagnosis of laryngopathies based on temporal pattern recognition in speech signal. Bio-Algorithms and Med-Systems 6(12), 75–80 (2010)

    Google Scholar 

  16. Szkola, J., Pancerz, K., Warchol, J.: Recurrent neural networks in computer-based clinical decision support for laryngopathies: An experimental study. Computational Intelligence and Neuroscience Article ID 289398 (2011)

    Google Scholar 

  17. Verikas, A., Gelzinis, A., Bacauskiene, M., Uloza, V.: Towards a computer-aided diagnosis system for vocal cord diseases. Artificial Intelligence in Medicine 36(1), 71–84 (2006)

    Article  Google Scholar 

  18. Warchol, J.: Speech examination with correct and pathological phonation using the SVAN 912AE analyser (in Polish). Ph.D. thesis, Medical University of Lublin (2006)

    Google Scholar 

  19. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann (2005)

    Google Scholar 

  20. Wroblewski, J.: Genetic algorithms in decomposition and classification problem. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery 2, vol. 2, pp. 471–487. Physica-Verlag, Heidelberg (1998)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dominika Gurdak .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Gurdak, D., Pancerz, K., Szkola, J., Warchol, J. (2013). Computer-Aided Diagnosis of Laryngopathies in the LabVIEW Environment: Exemplary Implementation. In: Kountchev, R., Iantovics, B. (eds) Advances in Intelligent Analysis of Medical Data and Decision Support Systems. Studies in Computational Intelligence, vol 473. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00029-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00029-9_14

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00028-2

  • Online ISBN: 978-3-319-00029-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics