In 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.
CITATION STYLE
Gómez, A., Quintero, L., López, N., Castro-Martínez, J., Villa, L., & Mejía, G. (2017). An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform. In IFMBE Proceedings (Vol. 60, pp. 654–657). Springer Verlag. https://doi.org/10.1007/978-981-10-4086-3_164
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