Young-Ji Eum

A Study on Analysis of Bio-Signals for Basic Emotions Classification: Recognition Using Machine Learning Algorithms

The most crucial feature of human computer interaction is computers and computer-based applications to infer the emotional states of humans or others human agents based on covert and/or overt signals of those emotional states. In emotion recognition, bio-signals reflect sequences of neural activity induced by emotional events and also, have many technical advantages. The aim of this study is to classify six emotions (joy, sadness, anger, fear, surprise, and neutral) that human have often experienced in real life from multi-channel bio-signals using machine learning algorithms. We have measured physiological responses of three-hundred participants for acquisition of bio-signals such as electrodermal activity, electrocardiograph, skin temperature, and photoplethysmograph during six emotions induction. Also, for emotion classification, we have extracted eighteen features from the signals and performed emotion classification using five algorithms, linear discriminant analysis, Naïve Bayes, classification and regression tree, self-organization map and support vector machine. The used algorithms were evaluated by only training, 10-fold cross-validation and repeated random sub-sampling validation. We have obtained recognition accuracy from 42.4 to 100% for only training and 39.2 to 53.9% for testing. Also, the result for testing showed that an accuracy of emotion recognition by Naïve Bayes and linear discriminant analysis were highest (53.9%, 52.7%) and was lowest by support vector machine (39.2%). This means that Naïve Bayes is the best emotion recognition algorithm for basic emotions. To apply to real system, we have to discuss in the view point of testing and this means that it needs to apply various methodologies for the accuracy improvement of emotion recognition in the future analysis.

The Effect of Personality on Psychological Responses Induced by Emotional Stimuli for Children

Objective: The aim of this study is to identify the relationship between personality and psychological responses induced by emotional stimuli (happiness, sadness, anger, boring and stress) for children. Background: Many researches are interested in assertion that there is close correlation between personality and emotion. The relationship between personality and emotion needs to be studied in view of the extended integration, not in view of respective property, because personality is deeply ingrained, and the relatively enduring patterns of thought, feeling and behavior and emotion can take advantage of individual differences in sensitivities to situational cues and predispositions to emotional state. In particular, studies on the personality and emotion for children are necessary in that childhood is an important period for formation of their personality and emotion expression and regulation. Method: Prior to the experiment, we made parents of 94 children rate personalities of their children, based on Korean Personality Inventory for Children (K-PIC). Results of 64 children without missing answers to all questions were analyzed. 64 children were exposed to five emotional stimuli and were asked to report the classification and intensity of their experienced emotion. Results: Children were classified into two groups of the lower 25% and higher 25% scores in twenty sub-scales of K-PIC, and psychological responses to five emotional stimuli between two groups were compared. Accuracy of emotion experienced by emotional stimuli showed a significant difference between the two groups, the lower and higher scores in Hyperactivity and Adjustment. Also, there was a significant difference in the intensity of experienced emotions between the two groups in Intellectual Screening and Psychosis. Conclusion: Our result has shown that hyperactivity, adjustment, intellectual screening and psychosis influence the accuracy and intensity of emotional responses. Application: This study can offer a guideline to overcome methodological limitation of emotion studies for children and help researcher basically understand and recognize human emotion in HCI.