Predicting effect of physical factors on tibial motion using artificial neural networks
Predicting effect of physical factors on tibial motion using artificial 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.
Authors: Murat Sari 1 and B. Gultekin Cetiner 2
1 Department of Mathematics, Faculty of Art and Science, Pamukkale University, 20070 Denizli, Turkey
2 Faculty of Engineering, Department of Manufacturing Engineering, IIUM, Jalan Gombak, 53100 Kuala Lumpur, Malaysia
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The above article was Published in the Journal Expert Systems with ApplicationsÂ
