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INVERSE KINEMATIC ANALYSIS OF A FOUR-BAR POLYCENTRIC KNEE MECHANISM APPLYING ARTIFICIAL NEURAL NETWORKS

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JANUARY-DECEMBER 2018   -  Volume: 5 -  Pages: [14 p.]

DOI:

https://doi.org/10.6036/NT8749

Authors:

OMAR ISMAEL LOPEZ SUAREZ - JONATHAN MARTINEZ PAREDES - ARIEL FUERTE HERNANDEZ - JUAN PABLO CAMPO LOPEZ - IVAN ALTAMIRANO OLGUIN - GERARDO HERNANDEZ VALENCIA - OSCAR TAXILAGA ZETINA

Disciplines:

  • INFORMATION TECHNOLOGY AND KNOWLEDGE (INTELIGENCIA ARTIFICIAL Y SIMULACION )

Downloads:   99

How to cite this paper:  
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Received Date :   26 February 2018

Reviewing Date :   27 February 2018

Accepted Date :   8 October 2018


Key words:
Rodilla, prótesis, mecanismos de cuatro barras, redes neuronales artificiales, poloide, Knee, prosthesis, artificial neural networks, centrode
Article type:
ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:
RESEARCH ARTICLES

ABSTRACT:
The knee is the largest joint of the human skeleton, located between the lever arms of the tibia and the femur. Its function is to provide leg flexion, a movement that makes it possible to perform daily activities such as walking, running, jumping, etc., which is why its joint mechanics are very complex. During human gait, in the flexion-extension of the knee an instantaneous center of rotation is generated, the trajectory generated forms a polar curve or centrode, being very important because it is related to the kinematics and the forces that develop during the cycle marching. Likewise, in a four-bar knee prosthetic mechanism during the intersection of two mobile links, a centrode is generated, which is related to the dimensions of the links of the mechanism. Derived from the above, in this work we propose the application of an optimization tool based on computational learning, with the main objective of proposing a four bars polycentric mechanism of voluntary control that is capable of producing the trajectory similar to that of the human knee during the flexo-extension. To achieve this, an inverse kinematic analysis of the mechanism is applied and artificial neural networks are applied, where, from a proposed trajectory, the ideal dimensions of the links that fully meet the needs for a specific patient are determined. In the final part of the work, obtained the optimized dimensions of the prosthesis, the computational model will be made, and in turn, manufacturing will be applied by means of three-dimensional printing.

Keywords: knee, prosthesis, artificial neural networks, centrode.

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