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Decision Tree Approach to Rules Extraction for Human Gait Analysis

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Book cover Artificial Intelligence and Soft Computing (ICAISC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6113))

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Abstract

The article presents the application of decision tree techniques to exploring barometric information obtained with instruments measuring the pressure of the human plantar onto contact surface while walking. The investigation was carried out on a group of 28 typical subjects as well as the subjects affected by Pes Planovalgus and Cerebral Palsy. The decision tree has been inducted by means of the vector of 255 values describing single stride with 51 samples per each of five zones of the human foot. The classification made by the resultant decision tree was correct for more then 94% strides. This allows to point the parameters which are the best discriminators between the investigated types of human gait.

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Author information

Authors and Affiliations

  1. Faculty of Mechanical Engineering, Bialystok Technical University, Wiejska Street 45C, 15-351, Bialystok, Poland

    Marcin Derlatka

  2. The Research Center of Resources Saving Problems, National Academy of Sciences of Belarus, Tizenhauza sq., 7, 230023, Grodno, Belarus

    Mikhail Ihnatouski

Authors
  1. Marcin Derlatka
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  2. Mikhail Ihnatouski
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Academy of Humanities and Economics in Łódź,, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer

  3. Institute of Automatics,, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA,  

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Louisville, 40292, Louisville, KY

    Jacek M. Zurada

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© 2010 Springer-Verlag Berlin Heidelberg

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Derlatka, M., Ihnatouski, M. (2010). Decision Tree Approach to Rules Extraction for Human Gait Analysis. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13208-7_74

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  • DOI: https://doi.org/10.1007/978-3-642-13208-7_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13207-0

  • Online ISBN: 978-3-642-13208-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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