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Revista Cubana de Informática Médica

versión On-line ISSN 1684-1859

Resumen

LUENGAS CONTRERAS, Lely Adriana; SANCHEZ PRIETO, Giovanni  y  VIZCAYA GUARIN, Pedro Raúl. Static Alignment of Prosthetics using Kinetic Variables and Machine Learning Methods. RCIM [online]. 2017, vol.9, n.1, pp.3-17. ISSN 1684-1859.

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.

Palabras clave : prosthetics alignment; medical rehabilitation; simulation model.

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