Examinando por Autor "Castro, J."
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Ítem An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform(SPRINGER, 2017-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y AplicacionesIn this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.Ítem An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform(SPRINGER, 2017-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoIn this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.Ítem An approach to emotion recognition in single-channel EEG signals: a mother child interaction(IOP Publishing, 2016) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombia; Medical Technology Laboratory, Faculty of Engineering, Universidad Nacional de San Juan, Argentina; Psychology, Education and Culture Research Group Faculty of Social Science Politécnico Grancolombiano University Institution, Argentina; Universidad EAFIT. Escuela de Ciencias; agomez13@eafit.edu.co; oquinte1@eafit.edu.co; Modelado MatemáticoIn this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology -- Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains -- Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadnessÍtem An approach to emotion recognition in single-channel EEG signals: A mother child interaction(IOP PUBLISHING LTD, 2016-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoIn this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains. Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadness.