Fusing Frequency-Domain Features and Brain Connectivity Features for Cross-Subject Emotion Recognition

Author:

Chen Chuangquan1ORCID,Li Zhencheng1ORCID,Wan Feng2ORCID,Xu Leicai1ORCID,Bezerianos Anastasios3ORCID,Wang Hongtao1ORCID

Affiliation:

1. Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China

2. Department of Electrical and Computer Engineering, Faculty of Science and Technology, and the Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau

3. Hellenic Institute of Transport (HIT), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Special Projects in Key Fields Supported by the Technology Development Project of Guangdong Province

Special Fund for Science and Technology of Guangdong Province

Educational Commission of Guangdong Province

Wuyi University and Hong Kong and Macao Joint Research Project

Jiangmen Science and Technology Project

European Union’s Horizon 2020 Research and Innovation Program [Proactive Safety Systems and Tools for a Constantly Upgrading Road Environment (SAFE_UP)]

Science and Technology Development Fund, Macau

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Reference48 articles.

1. On the Nyström method for approximating a Gram matrix for improved kernel-based learning;drineas;J Mach Learn Res,2005

2. Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach

3. A note on the phase locking value and its properties

4. Differential entropy feature for EEG-based vigilance estimation;shi;Proc 35th Annu Int Conf IEEE Eng Med Biol Soc (EMBC),2013

5. Emotional state classification from EEG data using machine learning approach

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