CASIA OpenIR  > 类脑智能研究中心  > 神经计算及脑机交互
Multisource Transfer Learning for Cross- Subject EEG Emotion Recognition
Jinpeng Li1,2; Shuang Qiu1,2; Yuan-Yuan Shen1,2; Cheng-Lin Liu1,2; Huiguang He1,2
Source PublicationIEEE Transactions Cybernetics
2019
IssueonlinePages:online
Abstract

Electroencephalogram (EEG) has been widely used in emotion recognition due to its high temporal resolution and reliability. Since the individual differences of EEG are large, the emotion recognition models could not be shared across persons, and we need to collect new labeled data to train personal models for new users. In some applications, we hope to acquire models for new persons as fast as possible, and reduce the demand for the labeled data amount. To achieve this goal, we propose a multisource transfer learning method, where existing persons are sources, and the new person is the target. The target data are divided into calibration sessions for training and subsequent sessions for test. The first stage of the method is source selection aimed at locating appropriate sources. The second is style transfer mapping, which reduces the EEG differences between the target and each source. We use few labeled data in the calibration sessions to conduct source selection and style transfer. Finally, we integrate the source models to recognize emotions in the subsequent sessions. The experiment results show that the three- category classification accuracy on benchmark SEED improves by 12.72% comparing with the non-transfer method. Our method facilitates the fast deployment of emotion recognition models by reducing the reliance on the labeled data amount, which has practical significance especially in fast-deployment scenarios. 

KeywordBrain-computer Interface, Emotion Recognition, Transfer Learning
Indexed BySCI
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23689
Collection类脑智能研究中心_神经计算及脑机交互
Corresponding AuthorHuiguang He
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Jinpeng Li,Shuang Qiu,Yuan-Yuan Shen,et al. Multisource Transfer Learning for Cross- Subject EEG Emotion Recognition[J]. IEEE Transactions Cybernetics,2019(online):online.
APA Jinpeng Li,Shuang Qiu,Yuan-Yuan Shen,Cheng-Lin Liu,&Huiguang He.(2019).Multisource Transfer Learning for Cross- Subject EEG Emotion Recognition.IEEE Transactions Cybernetics(online),online.
MLA Jinpeng Li,et al."Multisource Transfer Learning for Cross- Subject EEG Emotion Recognition".IEEE Transactions Cybernetics .online(2019):online.
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