OPTIMIZACIÓN DE INTERFACES DE TRABAJO MEDIANTE EYE-TRACKING Y ALGORITMOS EVOLUTIVOS

Abstract

Optimizing human-computer interfaces lead to diminish errors and to increase efficiency in developed tasks. In the present study several tasks were carried out in a submarine simulator following a set of pre-established orders. The main objective of the study was to obtain an optimal distribution of a simulated working environment. The data was provided by the participants through an eye-tracking hardware that feed a genetic algorithm system. Another variables employed into the algorithm were time and the number of errors committed during the tasks performance. The study was divided into two phases. In the first phase, participants worked on a pre-established environment, thereafter, users customized the environment redesigning windows sizes and positions in order to facilitate the execution of tasks. In the second phase of the study, a second sample worked with the environment created by the genetic algorithm. As final result, the distribution obtained with the algorithm meant a significant reduction in the execution time of the tasks and the number of errors committed.