计算机工程与科学2025，Vol.47Issue(5)：921-930,10.DOI:10.3969/j.issn.1007-130X.2025.05.016
基于非对称空间特征的脑电信号情感分析研究
Research on EEG signal emotion analysis based on asymmetric spatial features
摘要
Abstract
The asymmetry of the brain will have an impact on EEG emotion analysis,but many stud-ies have not considered this property.Combined with the asymmetry of brain space,this paper proposes a hybrid model,which uses multi-scale convolutional neural network to extract the EEG spatial features of left and right asymmetry of the brain,then uses bidirectional long short-term memory neural network to extract temporal features,and finally learns the relationship between features through the multi-head self-attention mechanism.The proposed model is experimentally validated on the publicly available DEAP dataset.The accuracy and F1-score for classifying the arousal dimension are 93.11％and 93.46％,respectively,while those for the valence dimension are 92.12％and 93.27％.Furthermore,the model is validated on the publicly available MAHNOB-HCI dataset,achieving accuracy and F1-score of 98.58％and 97.98％for the arousal dimension,and accuracy and F1-score of 98.76％and 98.25％for the valence dimension.The results demonstrate that the proposed model exhibits certain advantages in EEG-based emotion recognition.Furthermore,ablative experiments confirm the significance of the asym-metrical spatial layer.关键词
脑电情感识别/非对称空间特征/多尺度卷积神经网络/双向长短期记忆神经网络/多头自注意力机制Key words
EEG emotion recognition/asymmetric spatial feature/multi-scale convolutional neural network/bidirectional long short-term memory neural network/multi-head self-attention mechanism分类
信息技术与安全科学引用本文复制引用
王莹,杨青,王翔宇,张勇..基于非对称空间特征的脑电信号情感分析研究[J].计算机工程与科学,2025,47(5):921-930,10.基金项目
国家自然科学基金(61977032) （61977032）
