Predicting effect of physical factors on tibial motion using artificial neural networks

SARI M., Cetiner B.

EXPERT SYSTEMS WITH APPLICATIONS, vol.36, no.6, pp.9743-9746, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36 Issue: 6
  • Publication Date: 2009
  • Doi Number: 10.1016/j.eswa.2009.02.030
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.9743-9746
  • Yıldız Technical University Affiliated: No


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. (C) 2009 Elsevier Ltd. All rights reserved,