Evaluating 3D Visual Fatigue Induced by VR Headset Using EEG and Self-attention CNN
2022 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2022)(2022)
摘要
3D visual fatigue is one of the major factors that hinder the development of virtual reality contents towards larger population. We proposed an EEG-based self-attention CNN model to evaluate user's 3D visual fatigue in an end-to-end fashion. We adopted a wavelet-based convolution to extract spatiotemporal information and prevent overfitting. Besides, a self-attention layer was added to the feature extractor backbone to cope with the subject-variation problem in EEG-decoding. The proposed method is compared with four state-of-the-art methods, and the results demonstrate that our model has the best performance among all methods in subject-dependent and cross-subject scenarios.
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关键词
Human-centered computing, Human computer interaction (HCI), HCI design and evaluation methods, User studies, Social and professional topics, User characteristics, People with disabilities
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