Paper Title:
Human Gait Analysis and Classification Based on Neural Networks and Fuzzy Logic
  Abstract

Human gait analysis and classification is the process of identifying individuals by their walking manners. Computerized gait analysis using neural networks and fuzzy logic has become an integral part of the treatment decision-making process. Authors proposed the integration of kinetic data, more specifically power joints in combination with neural networks and fuzzy logic. It is a relatively new addition to other types of data including temporal and stride parameters. The performance of our approach was verified in laboratory for motion analysis. The obtained results are satisfying.

  Info
Periodical
Solid State Phenomena (Volumes 147-149)
Edited by
Zdzislaw Gosiewski and Zbigniew Kulesza
Pages
600-605
DOI
10.4028/www.scientific.net/SSP.147-149.600
Citation
J. Pauk, M. Derlatka, R. Długosz, M. Kolasa, "Human Gait Analysis and Classification Based on Neural Networks and Fuzzy Logic", Solid State Phenomena, Vols. 147-149, pp. 600-605, 2009
Online since
January 2009
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Price
$32.00
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