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Abstract

The project focuses on design of a BCI system based on eye tracking and leading to classification of i.e. emotion state, mental workload. Here the system is proposed not only on a 64 channel EEG, also eye tracking technology is specifically aimed to be implemented where it is a rather easy tech to use in daily life. The background of the project as a BCI as a classifier of emotional state on eye movements is: 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 proposed project.
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 project, stimuli will be applied to male and female volunteers, where different emotional stimuli sets will be chosen concerning valence scores to form positive, neutral and negative stimulus classes. The design will be improved upon the measurements.

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