2021-04-262021-04-262020-01-19MELO JÚNIOR, Gilberto. Análise da classificação de sinais eletro-oculográficos utilizando aprendizado de máquina. 2020. 144 f. Dissertação (Mestrado em Engenharia Elétrica e da Computação) - Universidade Federal de Goiás, Goiânia, 2020.http://repositorio.bc.ufg.br/tede/handle/tede/11277This work aims at the comprehensive study involving electro-oculographic signals, acquisition methodologies, digital filters and Machine Learning algorithms. The research methodology was divided into three major stages. The first stage aimed at developing an environment and methods for acquiring electro-oculographic signals. In the second stage, digital filters were applied to the acquired signals. In the third and last stage, the signal patterns were analyzed using Machine Learning algorithms responsible for the classification of electro-oculographic signals. As a result, accuracy in the classification of 76.596 \% was obtained with the Random Forest algorithm.Attribution-NonCommercial-NoDerivatives 4.0 InternationalSinais eletro-oculográficosAprendizado de máquinaSinais biomédicosElectrooculography signalsMachine learningBiomedicals signalsENGENHARIAS::ENGENHARIA ELETRICADissertação