In:
Bilişim Teknolojileri Dergisi, International Journal of Informatics Technologies, Vol. 13, No. 2 ( 2020-04-30), p. 137-144
Abstract:
Emotional state is controlled by the autonomous nervous system (ANS). Thus, in the presence of a positive or negative type of a stimulus, ANS responses occur in a short time which can be observed as various physical output, depending on the type of emotion triggered by the stimulus type in the individual. One of these physical differences related to the type of stimulus is the pupil size variation and can be named as a physiological change to examine one’s emotional state. According to previous studies, pupil size and eye movement measurements were shown to be a useful input signal. Relying on that, emotion recognition by extracting eye gaze pattern is aimed in the present study. When a negative type of a stimulus triggers a person, pupil size seems to dilate. On the other hand, in the presence of a positive type of stimulus, pupil size is tightened. Based on this information, in the concept of this study, stimuli are applied to male and female volunteers. Stimuli, a total of 60 pictures, are selected from the IAPS image database, where different emotional stimuli sets are chosen concerning valence scores to form positive, neutral and negative stimulus classes. Thirteen volunteers participated in the study to perform the test paradigm and to attend the eye tracker measurement. Left and right pupil size values and fixation time parameters are used for classification purposes. The input features are classified for three classes using kNN, Naive Bayes, Support Vector Machine, Linear Discriminant Analysis, decision tree and logistic regression techniques. Low classification accuracy yields us to apply classification based on positive and negative stimuli. Analysis results demonstrated the best success rate with 68% for kNN algorithm for classification within these two emotion groups, where the application of Naïve Bayes and SVM results in a success rate of 55%, Linear Discriminant Analysis 50%, decision tree and logistic regression 48%. To conclude, eye movements can reflect the emotional responses of the subject and also predictions of the arousal level of the subjects might be performed.
Type of Medium:
Online Resource
ISSN:
1307-9697
DOI:
10.17671/gazibtd.563830
Language:
Unknown
Publisher:
International Journal of Informatics Technologies
Publication Date:
2020
