An Investigation of Olfactory-enhanced Video on EEG-based Emotion Recognition

Collecting emotional physiological signals is significant in building affective Human-Computer Interactions (HCI). However, how to evoke subjects' emotions efficiently in EEG-related emotional experiments is still a challenge. In this work, we developed a novel experimental paradigm that allows...

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Bibliographic Details
Published in:IEEE transactions on neural systems and rehabilitation engineering 2023-01, Vol.31, p.1-1
Main Authors: Wu, Minchao, Teng, Wei, Fan, Cunhang, Pei, Shengbing, Li, Ping, Lv, Zhao
Format: Article
Language:English
Subjects:
Brain
EEG
Efficiency
Electroencephalogram (EEG)
Electroencephalography
Electroencephalography - methods
Emotion recognition
Emotions
Emotions - physiology
Entropy
Human computer interaction
Human-computer interface
human-computer interface (HCI)
Humans
neural pattern
Odors
Olfactory
olfactory-enhanced video
Physiology
Recognition, Psychology
Video
Visualization
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Summary:Collecting emotional physiological signals is significant in building affective Human-Computer Interactions (HCI). However, how to evoke subjects' emotions efficiently in EEG-related emotional experiments is still a challenge. In this work, we developed a novel experimental paradigm that allows odors dynamically participate in different stages of video-evoked emotions, to investigate the efficiency of olfactory-enhanced videos in inducing subjects' emotions; According to the period that the odors participated in, the stimuli were divided into four patterns, i.e., the olfactory-enhanced video in early/ later stimulus periods (OVEP/ OVLP), and the traditional videos in early/ later stimulus periods (TVEP/ TVLP). The differential entropy (DE) feature and four classifiers were employed to test the efficiency of emotion recognition. The best average accuracies of the OVEP, OVLP, TVEP, and TVLP were 50.54%, 51.49%, 40.22%, and 57.55%, respectively. The experimental results indicated that the OVEP significantly outperformed the TVEP on classification performance, while there was no significant difference between the OVLP and TVLP. Besides, olfactory-enhanced videos achieved higher efficiency in evoking negative emotions than traditional videos. Moreover, we found that the neural patterns in response to emotions under different stimulus methods were stable, and for Fp1, FP2, and F7, there existed significant differences in whether adopt the odors.
ISSN:1534-4320
1558-0210
DOI:10.1109/TNSRE.2023.3253866