INTELLIGENT SYSTEM FOR THE CONTROL OF A HAND PROSTHESIS PROTOTYPE.

This article describes the design, prototyping and experimentation process of an intelligent system for the control of a hand prosthesis prototype using low-cost commercial sensors and easy access in any market, achieved through the use of artificial intelligence algorithms - machine learning. The developed system consists of an open source Arm Model capable of moving fingers independently and is controlled by a basic neural network developed using the multilayer perceptron architecture, the network consists of three layers, an input layer composed of 8 neurons, a single hidden layer containing 80 neurons, and an output layer consisting of a neuron that performs the classification. The developed prototype was evaluated with accuracy as a validation metric, presenting a percentage of 98.2%. As another validation measure, the average response time was measured, which was 0.97 seconds. Finally, with the tests carried out, the generality of the intelligent system developed was also evidenced, since it is possible to perform the classification of gestures successfully in the people regardless of gender or age.

Authors

Beltrán Castaño, David Alfonso

Trujillo Vargas, Brian José

ADVISOR

Quintero M., Christian G.

Cárdenas Pérez, Carlos Andrés

Autores

Banguera Naranjo, Marlon

Buelvas Terán, Ricardo

Andrés

Conrado Retamozo, Rafael

Ricardo

Martínez Paba, Byron

TUTOR

Montero, Brayan

Becerra, Luis

Schettini, Norelli