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The diseases classification method on gait abnormalities characteristic contributions

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Present medicine uses computers in various applications, especially in a field of a diseases level classification and diagnosis. In many cases an automatic conclusion making units are the main goal of the computer systems usage. The software units are developed for the diseases classification or for monitoring of the disease medical treatment. An example application was described in this paper. It concerns a gait abnormalities level analysis that is described by a data records gathered by insoles of Parotec System for Windows (PSW) [17,18]. The PSW software package is used for visualisation of the gait characteristic static and dynamic characteristic features. In the authors' works many additional data components were distinguished. The field of the applications is located within the neurological gait characteristics also the source applications concern orthopaedics [16,18]. Careful analysis of the data provided the developers with new areas the PSW applications [4,11,13]. For conclusion making units the artificial networks theory was implemented [2,4,11,13]. For more effective training of the neural networks specific characteristic measures were introduced [4,5]. They allow controlling the training process more precisely, avoiding mistakes in current records classification.
Rocznik
Tom
Strony
187--194
Opis fizyczny
Bibliogr. 18 poz., rys.
Twórcy
autor
  • University of Silesia, Institute of Informatics, Dept. of Computer Systems, Katowice, Poland
autor
  • University of Silesia, Institute of Informatics, Dept. of Computer Systems, Katowice, Poland
  • Silesian University of Technology, Faculty of Transport, Department of Transport Informatics, Katowice, Poland
Bibliografia
  • [1] CHANDZLIK S., KOPICERA K.: Experiments with neural network parameters – selection for Foot abnormalities Recognition, Journal of Medical Informatics & Technologies. Vol. 5, pp: CS-71 – CS-78. ISBN 83-909517-2-7, 2000.
  • [2] CHANDZLIK S., PIECHA J.: Modelling the data record of a patient walk by Lagrange-polynomial method. Journal of Medical Informatics & Technologies. Vol. 3, pp: MI-143 – MI-152, 2002.
  • [3] CHANDZLIK S., PIECHA J.: A patient walk-data-record modelling using a spline interpolation method. Journal of Medical Informatics & Technologies. Vol. 3, pp: MIT-153 – MIT-160. ISSN 1642-6037, 2002.
  • [4] CHANDZLIK S., PIECHA J.: The body balance measures for neurological disease estimation and classification. Journal of Medical Informatics & Technologies, Vol. 6, pp: IT-87 – IT-94, 2003.
  • [5] CHANDZLIK S., PIECHA J.: The interference spectrum extraction of a gait characteristics data record. Journal of Medical Informatics & Technologies. Vol. 7, pp: KB-23 – KB-31, 2004.
  • [6] CHANDZLIK S., PIECHA J.: The Gait Characteristic Data Spectrum Extraction. Proc. 4th Inter. Conf. on Computer Recognition System CORES’05, Vol. 18, pp. 493-501, 2005.
  • [7] CLANE D.B.: Treatment of Parkinson Disease. New England J. Med., pp: 1021-1027, 1993.
  • [8] DESIENO D.: Adding a conscience to competitive learning. IEEE International Conference on Neural Networks, IEEE Press, New York, Vol. 1, pp: 117-124, 1988.
  • [9] FLOATER M.S.: Parameterization and smooth approximation of surface triangulations. Comp. Aided Geom. Des., Vol. 14, pp: 231-250, 1997.
  • [10] HURVICH C.M., TSAI C.L.: Regression and time series model selection in small samples, Biometrika, Vol. 76, pp: 297-307, 1989.
  • [11] KOPICERA K., PIECHA J., ZYGUŁA J.: The neural networks in diagnostics support for PSW system. Proc. of Int. Conference ASIS’99, pp. 113-118, Krnov, 1999.
  • [12] LEVIN D., NADLER E.: Convexity Preserving Interpolation by Algebraic Curves and Surfaces. Numerical Algorithms, Vol. 9, pp: 113-139, 1995.
  • [13] PIECHA J.: The neural network conclusion-making system for foot abnormality recognition. Proceedings of IMACS World Congress, Lausanne, Switzerland, August 2000.
  • [14] PIECHA J.: The neutral network selection for a medical diagnostic system using an artificial data set. Journal of Computing and Information Technology CIT, Vol.9, pp: 123–132, 2001.
  • [15] PIECHA J., KOPICERA K.: The conclusion making method using pathology classifiers, Proc. on KOSYR’01, pp: 29-33, 2001.
  • [16] PIECHA J., ZYGUŁA J., ŁYCZAK J., GAŹDZIK T., PROKSA J.: The advanced measuring system for orthopaedic pathologies diagnostics using a static and dynamic footprints, Chirurgia narządów ruchu i ortopedia polska vol. LXI 1996, suplement 3B, pp.119-124. (in polish)
  • [17] ZBROJKIEWICZ J.S., PIECHA J.: Parkinson disease examination using walk disturbances characteristics. Journal of Medical Informatics & Technologies. Vol. 3, pp: MI-134 – MI-142, 2002.
  • [18] ZYGUŁA J.: Przetwarzanie danych pomiarowych dla systemu wnioskowania o patologiach w obszarze stopy. PhD monograph available in main library of Silesian University of Technology in Gliwice (1997).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0012-0021
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