Abstract
The gait characteristic features can be used for various diseases source and level diagnosis. The interferences of a physiological data record caused by any characteristic abnormal data spectrum (of the disease) corresponds to the disease source and level. The disease source can easy be classified by the relevant periodical functions. The interferences characteristics were analysed then matched to the well defined mathematical expressions for doing several manipulations on the data set. Knowing a range of the data records disorders the physiological data record can be modified due to multiply the data set of the defined disease class. This way the efficient amount of the data for the neural network training can be obtained. The paper shows several aspects of the gait data record analysis concerning two neurological diseases.
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© 2005 Springer-Verlag Berlin Heidelberg
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Chandzlik, S., Piecha, J. (2005). The Gait Characteristic Data Spectrum Extraction. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_58
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DOI: https://doi.org/10.1007/3-540-32390-2_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
Online ISBN: 978-3-540-32390-7
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