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

Tibial Rotation Assessment Using Artificial Neural Networks

International University of Sarajevo, Faculty of Engineering and Natural Sciences, Sarajevo, Bosnia & Herzegovina
Pamukkale University, Faculty of Art and Science, Department of Mathematics, 20020, Denizli, Turkey
Author to whom correspondence should be addressed.
Published: 1 April 2010
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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).

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MDPI and ACS Style

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

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Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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