Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/6730
Title: Predicting effect of physical factors on tibial motion using artificial neural networks
Authors: Sarı, Murat
Gultekin Cetiner, B.
Keywords: Artificial neural network
Biomechanics
Tibial rotation
Body mass
Conventional approaches
Data assessments
Healthy subjects
Physical factors
Processing systems
Backpropagation
Rotation
Neural networks
Abstract: The aim of this study was to predict the effect of physical factors on tibial motion by making use of artificial neural networks (ANNs). Since assessment of the tibial motion by the conventional approaches is generally difficult, this study aimed at the prediction of the relations between several physical factors (gender, age, body mass, and height) and tibial motion in terms of the ANNs. Data collected for 484 healthy subjects have been analyzed by using the ANNs. The study has given encouraging results for such a purpose. This investigation has been made to predict the rotations; especially the RTER prediction is highly satisfactory and the ANNs have been found to be very promising processing systems for modelling in the tibial rotation data assessments. © 2009 Elsevier Ltd. All rights reserved.
URI: https://hdl.handle.net/11499/6730
https://doi.org/10.1016/j.eswa.2009.02.030
ISSN: 0957-4174
Appears in Collections:Fen-Edebiyat Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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