An approach to emotion recognition in single-channel EEG signals using stationary wavelet transform
VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga …, 2017•Springer
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.
(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.
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.
Springer
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