Human Gait Analysis and Classification Based on Neural Networks and Fuzzy Logic

Abstract:

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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 et al., "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:

$35.00

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