模式识别与人工智能
Thursday, Apr. 3, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
  2018, Vol. 31 Issue (10): 941-949    DOI: 10.16451/j.cnki.issn1003-6059.201810008
Researches and Applications Current Issue| Next Issue| Archive| Adv Search |
EEG Emotion Recognition Based on Sparse Group Lasso-Granger Causality Feature
GUO Jinliang1,2, FANG Fang1, WANG Wei1,2, HE Hanna1,2
1.School of Computer and Information, Hefei University of Technology, Hefei 230601
2.Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, Hefei University of Technology, Hefei 230601

Download: PDF (870 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  Aiming at the current feature extraction based on the functional network level of single brain region, a sparse group lasso-granger causality method is proposed to extract the causal relation among different brain regions as the characteristics of EEG at the effectual brain network level. The α, β and γ EEG bands of participants are extracted. The sparse group lasso algorithm is used to filter the obtained values of the cascade causality measures to acquire high correlation feature subsets as the emotion classification features. Finally the SVM classifier is utilized for emotion classification. Moreover, the ReliefF(filter feature selection) algorithm is employed to select an effective EEG channels to reduce the computational time complexity. The experiments show that the proposed method obtains a higher average emotion classification accuracy on the Valence-Arousal two-dimensional emotion model, and the classification result of the proposed method is better than that of the contrast EEG features. The extracted emotion EEG features can effectively recognize the subjects in different emotional states.
Received: 26 April 2018     
ZTFLH: TP 391.4  
Fund:Supported by National Natural Science Foundation of China(No.61474035,61204046,61432004,61306049)
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
GUO Jinliang
FANG Fang
WANG Wei
HE Hanna
Cite this article:   
GUO Jinliang,FANG Fang,WANG Wei等. EEG Emotion Recognition Based on Sparse Group Lasso-Granger Causality Feature[J]. , 2018, 31(10): 941-949.
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201810008      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I10/941
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn