Skip to main content

Classification Based on the Self-Organization of Child Patients with Developmental Dysphasia

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7824))

Abstract

Involvement of mathematical and engineering methods in medicine makes it possible to perform research into processes in the human body by non-invasive methods. Our team cooperates with neurologists in the domain of developmental dysphasia. We search for correlations between the results of EEG, magnetic resonance (MR) tractography, speech signal analysis, clinical speech therapy and psychology. Our aim is to verify a hypothesis of the possibility of classifying and visual representing changes in pathological speech by means of artificial neural networks. This contribution concentrates on one part of this research: disordered children’s speech analysis and results from MR tractography. We try to divide the patients into three groups according to disorder relevance. For classification, we use PCA and SSOM. Evaluation of the results and preparation of a software pack with a user-friendly interface can facilitate the emergence of disease monitoring and improve the quality of therapy.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Tuckova, J., Komarek, V.: Effectiveness of speech analysis by self-organizing maps in children with developmental language disorders. Neuroendocrinology Letters 29(6), 939–948 (2008)

    Google Scholar 

  2. Saygin, A.P., et al.: Neural resources for processing language and environmental sounds Evidence from aphasia. Brain 126(4), 928–945 (2003), http://brain.oxfordjournals.org/

    Article  Google Scholar 

  3. Moineau, S., Dronkers, N.F., Bates, E.: Exploring the processing continuum of single-word comprehension in aphasia. J. Speech Lang. Hear. Res. 48(4), 884–896 (2005)

    Article  Google Scholar 

  4. de Guibert, C., et al.: Abnormal functional lateralization and activity of language brain areas in typical specific language impairment (developmental dysphasia). Brain (a Journal of Neurology) (2011), http://brain.oxfordjournals.org/ (September 19, 2012)

  5. Cuingnet, R., et al.: Spatial and anatomical regularization of SVM for brain image analysis (2010), http://cogimage.dsi.cnrs.fr/perso/colliot/files/nips2010-camera_ready.pdf (September 19, 2012)

  6. Kohonen, T.: Self-Organizing Maps, 3rd edn. Springer (2001)

    Google Scholar 

  7. Jolliffe, I.T.: Principal Component Analysis. Springer (2002) ISBN: 978-0387954424

    Google Scholar 

  8. Komarek, V., Kynčl, M., Šanda, J., Vránová, M.: Diffusion Tensor Imaging: Ventral and Dorsal Connections between Language Areas in Developmental Dysphasia. In: 9th EPNS Congress, Dubrovnik, Croatia (May 2011)

    Google Scholar 

  9. Psutka, J., Müller, L., Matousek, J., Radova, V.: Speaking with a Computer in Czech. Academia Praha (2006) (in Czech) ISBN 80-200-0203-0

    Google Scholar 

  10. Tuckova, J., Zetocha, P.: Speech analysis of children with developmental dysphasia by Supervised SOM. Neural Network World 16(6), 533–545 (2006) ISSN: 1210-0552

    Google Scholar 

  11. Vavrina, J., Zetocha, P., Tuckova, J.: Detection of degree of developmental dysphasia based on methods of vowel analysis. In: Proc. of the 36th Int. Conf. on Telecommunications and Signal Processing (TSP 2012), Prague, Czech Republic (2012) ISBN 978-1-4673-1116-8

    Google Scholar 

  12. Zetocha, P.: Design and realization of children speech database. Technical report, Ministry of Education grant FRVS, No.2453/2008 (2008) (in Czech)

    Google Scholar 

  13. Vesanto, J., Himberg, J., Alhoniemi, E., Parhankangas, J.: SOM Toolbox for Matlab. HUT (2000) ISBN 951-22-4951-0, http://www.cis.hut.fi/projects/somtoolbox

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tuckova, J., Vavrina, J., Sanda, J., Kyncl, M. (2013). Classification Based on the Self-Organization of Child Patients with Developmental Dysphasia. In: Tomassini, M., Antonioni, A., Daolio, F., Buesser, P. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2013. Lecture Notes in Computer Science, vol 7824. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37213-1_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37213-1_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37212-4

  • Online ISBN: 978-3-642-37213-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics