| Hierarchical Convolutional Neural Networks for EEG-Based Emotion Recognition | |
Li, Jinpeng1,2 ; Zhang, Zhaoxiang1,2,3; He, Huiguang1,2,3
| |
| 发表期刊 | COGNITIVE COMPUTATION
 |
| 2018-04-01 | |
| 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 |
| DOI | 10.1007/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 | 智能感知与计算研究中心 |
| 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 |
| 第一作者单位 | 类脑智能研究中心 |
| 推荐引用方式 GB/T 7714 | 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. |
| 条目包含的文件 | 下载所有文件 | |||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| cc.pdf（1800KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
修改评论