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2017, Number 1

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Revista Cubana de Informática Médica 2017; 9 (1)

Static Alignment of Prosthetics using Kinetic Variables and Machine Learning Methods

Luengas CLA, Sánchez PG, Vizcaya GPR

Language: Spanish
References: 36
Page: 3-17
PDF size: 443.96 Kb.


ABSTRACT

The complex process of alignment in prosthesis and the non-existence of a model for static alignment of transtibial prostheses is the focus of this research. Objective: Obtain a computational model to establish the existence of the static alignment of transtibial prostheses through kinetic parameters present in unilateral transtibial amputees. Methods: In the Amputee and Prosthetic Service of the Central Military Hospital, Bogotá, Colombia, the construction of a data base of Pressure Center (COP) and distribution of plantar pressure in amputees was carried out. The data include kinetic values measured with the prosthesis in alignment and misalignment. Results: Three computational models were developed, a neural network, vector support machines and decision trees, the performance of the models was compared. Conclusions: Models that make use of vector support machines and decision trees had higher performance than the neural network. In this way, it is verified that the static alignment can be carried out objectively using technological resources.


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