Next Article in Journal
Improved Part Modeling in a Process Planning System
Previous Article in Journal
Peristaltic Flow of a Third-Grade Fluid in a Planar Channel
Article Menu

Article Versions

Export Article

Open AccessArticle
Math. Comput. Appl. 2010, 15(1), 34-44; doi:10.3390/mca15010034

Tibial Rotation Assessment Using Artificial Neural Networks

1
International University of Sarajevo, Faculty of Engineering and Natural Sciences, Sarajevo, Bosnia & Herzegovina
2
Pamukkale University, Faculty of Art and Science, Department of Mathematics, 20020, Denizli, Turkey
*
Author to whom correspondence should be addressed.
Published: 1 April 2010
Download PDF [501 KB, uploaded 1 April 2016]

Abstract

Assessment of the tibial rotations by the conventional approaches is generally difficult. An investigation has been made in this study to assess the tibial motions based on the prediction of the effects of physical factors as well as a portion of tibial measurements by making use of Artificial Neural Networks (ANN). Therefore, this study aimed at the prediction of the relations between several physical factors and tibial motion measurements in terms of Artificial Neural Networks. These factors include gender, age, weight, and height. Data collected for 484 healthy subjects have been analyzed by Artificial Neural Networks. Promising results showed that the ANN has been found to be appropriate for modeling and simulation in the data assessments. The paper gives detailed results regarding the use of ANN for modeling tibial rotations in terms of physical factors. The study shows the feasibility of ANN to predict the behaviour of knee joints.
Keywords: Tibial motion; Artificial Neural Networks Tibial motion; Artificial Neural Networks
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Çetiner, B.G.; Sarı, M. Tibial Rotation Assessment Using Artificial Neural Networks. Math. Comput. Appl. 2010, 15, 34-44.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top