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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Articles in this Volume were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on mdpi.com as a courtesy and upon agreement with the previous journal publisher.
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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
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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).

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

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