Machine learning to differentiate between positive and negative emotions using pupil diameter

1Department of Electrical and Electronics Engineering & Centre for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Malaysia 2Department of Neurology & NeuroCure Clinical Research Center, Charité Universitätsmedizin Berlin, Germany 3Department of Fundamental and Applied Sciences & Centre for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Malaysia Pupil diameter (PD) has been suggested as a reliable parameter for identifying an individual’s emotional state. In this paper, we introduce a learning machine technique to detect and differentiate between positive and negative emotions. We presented 30 participants with positive and negative sound stimuli and recorded pupillary responses. The results showed a significant increase in pupil dilation during the processing of negative and positive sound stimuli with greater increase for negative stimuli. We also found a more sustained dilation for negative compared…


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