RT Journal Article
T1 Saccadic points classification using Multilayer Perceptron and Randon Forest classifiers in EOG recording of patients with Ataxia SCA2
A1 Becerra-García, Roberto Antonio
A1 Joya-Caparrós, Gonzalo
A1 García, Rodolfo
A1 Velázquez, Luis
A1 Rodríguez, Roberto
A1 Pino, Carmen
K1 Ojos - Movimiento
K1 Tecnología
AB In this paper, we compare the performance of two different methods for the task of electrooculogram saccadic points classification in Patients with Ataxia SCA2: Multilayer Perceptrons (MLP) and Random Forest. First we segment the recordings of 6 subjects into ranges of saccadic and non-saccadic points as the basis of supervised learning. Then, we randomly select a set of cases based on the velocity profile near each selected point for training and validation purposes using percent split scheme. Obtained results show that both methods have similar performance in classification matter, and seem to be suitable to solve theproblem of saccadic point classification in electrooculographic records from subjects with Ataxia SCA2.
YR 2013
FD 2013-10-23
LK http://hdl.handle.net/10630/6153
UL http://hdl.handle.net/10630/6153
LA eng
NO AECID: Agencia Española de Cooperación Internacional para el Desarrollo. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026