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.
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References
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)
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/
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)
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)
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)
Kohonen, T.: Self-Organizing Maps, 3rd edn. Springer (2001)
Jolliffe, I.T.: Principal Component Analysis. Springer (2002) ISBN: 978-0387954424
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)
Psutka, J., Müller, L., Matousek, J., Radova, V.: Speaking with a Computer in Czech. Academia Praha (2006) (in Czech) ISBN 80-200-0203-0
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
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
Zetocha, P.: Design and realization of children speech database. Technical report, Ministry of Education grant FRVS, No.2453/2008 (2008) (in Czech)
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
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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
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DOI: https://doi.org/10.1007/978-3-642-37213-1_42
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