Abstract
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.
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Gómez, A., Quintero, L., López, N., Castro, J., Villa, L., Mejía, G. (2017). An approach to emotion Recognition in Single-channel EEG Signals using Stationary Wavelet Transform. In: Torres, I., Bustamante, J., Sierra, D. (eds) VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga, Santander, Colombia, October 26th -28th, 2016. IFMBE Proceedings, vol 60. Springer, Singapore. https://doi.org/10.1007/978-981-10-4086-3_164
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DOI: https://doi.org/10.1007/978-981-10-4086-3_164
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