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oai:riuma.uma.es:10630/61532026-02-03T10:53:31Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Becerra-García, Roberto Antonio author Joya-Caparrós, Gonzalo author García, Rodolfo author Velázquez, Luis author Rodríguez, Roberto author Pino, Carmen author 2013-10-23 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. http://hdl.handle.net/10630/6153 Ojos - Movimiento Tecnología Saccadic points classification using Multilayer Perceptron and Randon Forest classifiers in EOG recording of patients with Ataxia SCA2