A neural network approach to the alignment of transtibial prostheses
Un enfoque de redes neuronales para la alineación de prótesis transtibiales
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Introduction: The presence of diseases or musculoskeletal alterations, as well as trauma due to accidents have as a possible consequence amputation, in Colombia the armed conflict is added as a cause, since it has generated a population group with disabilities due to landmines, amputation being predominant in lower limb. The prosthesis is used so that the amputee can adapt to their condition and rejoin their daily activities, its use occurs after the alignment of the prosthesis. The alignment tends to be a subjective process, where knowledge and practice are essential at the time of carrying it out; there are no systems that allow knowing the affectation of the alignment on biomechanical variables of the amputee. For this reason, it was proposed to create a neural network that shows the incidence of the angular variation of the socket of the prosthesis in joint ranges, the distribution of body weight and the center of pressure.
Method: A descriptive study was carried out where the socket of the prosthesis of a transtibial amputee was placed in seven different angular positions, in each position biomechanical parameters were measured, with these data a generalized regression neural network (GRNN) was programmed to predict data biomechanics from the socket location and a graphical interface was generated to view the parameter changes.
Results: The neural network allowed predicting the behavior of the hip, knee and ankle angles, the location of the pressure center and the body weight supported both ipsilaterally (amputee) and contralaterally (non amputee); and in the graphical interface the affectation could be shown.
Conclusion: The use of technological tools allows the construction of support systems for medical personnel, in this case the prosthetist, to improve the rehabilitation process of a person with a transtibial prosthesis.
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