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Olfactory-Enhanced VR: What's the Difference in Brain Activation Compared to Traditional VR for Emotion Induction?.

Authors :
Zhong, Xinyue
Liu, Wanqing
Xie, Jialan
Gu, Yun
Liu, Guangyuan
Source :
IEEE Transactions on Affective Computing; Jul-Sep2024, Vol. 15 Issue 3, p1331-1342, 12p
Publication Year :
2024

Abstract

Olfactory-enhanced virtual reality (OVR) creates a complex and rich emotional experience, thus promoting a new generation of human-computer interaction experiences in real-world scenarios. However, with the rise of virtual reality (VR) as a mood induction procedure (MIP), few studies have incorporated olfactory stimuli into emotion induction in three-dimensional (3D) environments. Considering the differences in electroencephalography (EEG) dynamics between sensory stimuli, all previous two-dimensional (2D) and 3D emotional studies have been less effective in reality because they only use visual and audio senses. To overcome these limitations, we developed a novel EEG signal dataset based on OVR. We systematically analyzed the influence of olfactory stimuli on emotion induction in a VR environment from a neurophysiological perspective. Specifically, synchronous EEG signals were collected from 65 participants as they watched positive and negative videos in traditional VR and OVR. Their power spectral densities (PSDs) were then calculated to compare the differences in brain activation between their VR and OVR modes during the induction of positive and negative emotions, while their brain states were classified after feature selection. The results showed that olfactory stimuli enhanced EEG responses for positive emotions, but the opposite was true for negative emotions. Additionally, the recognition rate of brain emotional states was more than 90% under both positive and negative emotions, while the high-frequency β and γ bands could effectively distinguish VR and OVR modes. This study introduced the olfaction into the field of human-computer interaction, which could promote research on emotion induction and recognition in real-world environments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19493045
Volume :
15
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Affective Computing
Publication Type :
Academic Journal
Accession number :
179509535
Full Text :
https://doi.org/10.1109/TAFFC.2023.3337745