15:30 - 17:00
Fri-P2
Planck Lobby & Meitner Hall
Delivering olfactory stimuli based on odor categories for multimedia contents as a feasible method
Fri-P2-075
Presented by: Kwangsu Kim
Kwangsu Kim 1, 2, Jisub Bae 3, JeeWon Lee 1, SunAe Moon 1, Sang-ho Lee 2, 4, Won-seok Kang 2, 4, Cheil Moon 1, 2
1 Department of Brain Sciences, Graduate School, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Korea, 2 Convergence Research Advanced Centre for Olfaction, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea, 3 Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea, 4 Division of Intelligent Robot, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea
Although we have five senses to perceive numerous stimuli, multimedia has mainly focused on visual and auditory senses. As one of the attempts to extend senses used in multimedia, olfactory stimuli have been used in multimedia content to enhance the sense of multimedia's reality. Matching odors with objects in scenes is mainly conducted when selecting odors for multimedia. However, it is impractical to select and offer all odors matched with all objects in scenes to viewers. As an alternative, offering an odor in a category was suggested to represent odors belonging to the category. Indeed, matching odors based on these categories has been used in the multimedia and film industries. However, it is still unclear whether viewers' responses to videos with multiple odors (e.g., rose, lavender, lily) from a category (e.g., flower) can be comparable. Therefore, we studied whether odors belonging to the same categories could be similar by monitoring congruency and five frequency bands (delta, theta, alpha, beta, and gamma) of the EEG data in videos. We conducted questionnaires and EEG experiments to validate the effects of odors belonging to similar categories. Our result showed that odors in similar odor categories had higher congruency to videos than those in the different odor categories. Our EEG data mainly clustered delta and theta bands when odors were offered in similar categories in both videos. Primarily, the theta band was related to neural signals of odors during olfactory processing. However, alpha, beta, and gamma bands were not clustered depending on the categories despite being related to human emotional responses. Our studies showed the possibility that choosing the odors based on odor categories in multimedia can be partially feasible.