Combining eye movements and EEG to enhance emotion recognition

Wei‐Long Zheng · Bao‐Liang Lu

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Emotion and Mood Recognition EEG and Brain-Computer Interfaces Gaze Tracking and Assistive Technology

Abstract

In this paper, we adopt a multimodal emotion recognition framework by combining eye move-ments and electroencephalography (EEG) to en-hance emotion recognition. The main contribu-tions of this paper are twofold. a) We investigate sixteen eye movements related to emotions and i-dentify the intrinsic patterns of these eye move-ments for three emotional states: positive, neutral and negative. b) We examine various modality fu-sion strategies for integrating users external sub-conscious behaviors and internal cognitive states and reveal that the characteristics of eye move-ments and EEG are complementary to emotion recognition. Experiment results demonstrate that modality fusion could significantly improve emo-tion recognition accuracy in comparison with sin-gle modality. The best accuracy achieved by fuzzy integral fusion strategy is 87.59%, whereas the ac-curacies of solely using eye movements and EEG data are 77.80 % and 78.51%, respectively. 1

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References

1997Affective Computing 2010Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications 2013Differential entropy feature for EEG-based emotion classification 2008Emotion recognition based on physiological changes in music listening 2010EEG-Based Emotion Recognition in Music Listening 2009Assessing the effectiveness of a large database of emotion-eliciting films: A new tool for emotion researchers 2003Pupil size variation as an indication of affective processing 2011Multimodal Emotion Recognition in Response to Videos

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2023A systematic survey on multimodal emotion recognition using learning algorithms 2017Multimodal Emotion Recognition Using Deep Neural Networks 2018A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges 2021Plug-and-Play Domain Adaptation for Cross-Subject EEG-based Emotion Recognition 2017EEG-Based Emotion Recognition Using Hierarchical Network With Subnetwork Nodes

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