2016-05-1120161742-6596http://hdl.handle.net/10784/8372In 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 sadnessapplication/pdfengSistemas dinámicosAtractores (Matemáticas)info:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessELECTROENCEFALOGRAFÍAREDES NEURALES (COMPUTADORES)EMOCIONESPROCESOS DE BIFURCACIÓNPROCESOS ESTOCÁSTICOSCOMUNICACIÓN NO VERBALEXPRESIÓNPROCESAMIENTO DE SEÑALESMADRE E HIJOSISTEMAS DE RECONOCIMIENTOElectroencephalographyNeural networks (Computer science)EmotionsBranching processesStochastic processesNonverbal communicationExpressionSignal processingMother and childRecognition systemsElectroencephalographyNeural networks (Computer science)EmotionsBranching processesStochastic processesNonverbal communicationExpressionSignal processingMother and childRecognition systemsSistemas dinámicosAtractores (Matemáticas)Acceso abierto2016-05-11Creative Commons Attribution 3.0 licence (CC BY 3.0)Gómez, A.Quintero, L.López, N.Castro, J.Gómez, A.Quintero, L.López, N.Castro, J.10.1088/1742-6596/705/1/012051