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Hierarchical Convolutional Neural Networks for EEG-Based Emotion Recognition
Li, Jinpeng1,2; Zhang, Zhaoxiang1,2,3; He, Huiguang1,2,3
2018-04-01
发表期刊COGNITIVE COMPUTATION
卷号10期号:2页码:368-380
文章类型Article
摘要Traditional machine learning methods suffer from severe overfitting in EEG-based emotion reading. In this paper, we use hierarchical convolutional neural network (HCNN) to classify the positive, neutral, and negative emotion states. We organize differential entropy features from different channels as two-dimensional maps to train the HCNNs. This approach maintains information in the spatial topology of electrodes. We use stacked autoencoder (SAE), SVM, and KNN as competing methods. HCNN yields the highest accuracy, and SAE is slightly inferior. Both of them show absolute advantage over traditional shallow models including SVM and KNN. We confirm that the high-frequency wave bands Beta and Gamma are the most suitable bands for emotion reading. We visualize the hidden layers of HCNNs to investigate the feature transformation flow along the hierarchical structure. Benefiting from the strong representational learning capacity in the two-dimensional space, HCNN is efficient in emotion recognition especially on Beta and Gamma waves.
关键词Affective Brain-computer Interface Emotion Recognition Brain Wave Deep Learning Eeg
WOS标题词Science & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1007/s12559-017-9533-x
关键词[WOS]BRAIN-COMPUTER INTERFACES ; VIGILANCE ESTIMATION ; CLASSIFICATION ; RESPONSES
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(91520202 ; CAS Scientific Equipment Development Project(YJKYYQ20170050) ; Youth Innovation Promotion Association CAS ; 81671651)
WOS研究方向Computer Science ; Neurosciences & Neurology
WOS类目Computer Science, Artificial Intelligence ; Neurosciences
WOS记录号WOS:000430190600016
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/21582
专题类脑智能研究中心
作者单位1.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing, Peoples R China
2.UCAS, Beijing, Peoples R China
3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
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Li, Jinpeng,Zhang, Zhaoxiang,He, Huiguang. Hierarchical Convolutional Neural Networks for EEG-Based Emotion Recognition[J]. COGNITIVE COMPUTATION,2018,10(2):368-380.
APA Li, Jinpeng,Zhang, Zhaoxiang,&He, Huiguang.(2018).Hierarchical Convolutional Neural Networks for EEG-Based Emotion Recognition.COGNITIVE COMPUTATION,10(2),368-380.
MLA Li, Jinpeng,et al."Hierarchical Convolutional Neural Networks for EEG-Based Emotion Recognition".COGNITIVE COMPUTATION 10.2(2018):368-380.
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