2021-04-122017-01-0116800737SCOPUS;2-s2.0-85018372191http://hdl.handle.net/10784/27897In 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.enghttps://v2.sherpa.ac.uk/id/publication/issn/1680-0737info:eu-repo/semantics/conferencePaperBiomedical engineeringElectroencephalographyElectrophysiologySignal processingSpeech recognition, Developmental psychologyEmotionEmotion recognitionEmotional stateFeaturesSingle channel eegSingle-channel signalsWavelet, Biomedical signal processing2021-04-12Gómez, A.Quintero, L.López, N.Castro, J.Villa, L.Mejía, G.10.1007/978-981-10-4086-3_164