EEG Based Emotion Recognition: A Tutorial and Review

Author:

Li Xiang1,Zhang Yazhou2,Tiwari Prayag3,Song Dawei4,Hu Bin5,Yang Meihong1,Zhao Zhigang1,Kumar Neeraj6,Marttinen Pekka3

Affiliation:

1. Qilu University of Technology (Shandong Academy of Sciences), Shandong Computer Science Center (National Supercomputer Center in Jinan), Jinan, China

2. Software Engineering College, Zhengzhou University of Light Industry, China and State Key Lab. for Novel Software Technology, Nanjing University, Nanjing, China

3. Department of Computer Science, Aalto University, Finland

4. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

5. Institute of Engineering Medicine, Beijing Institute of Technology, Beijing, China

6. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology (Deemed University), Patiala (Punjab), India

Abstract

Emotion recognition technology through analyzing the EEG signal is currently an essential concept in Artificial Intelligence and holds great potential in emotional health care, human-computer interaction, multimedia content recommendation, etc. Though there have been several works devoted to reviewing EEG-based emotion recognition, the content of these reviews needs to be updated. In addition, those works are either fragmented in content or only focus on specific techniques adopted in this area but neglect the holistic perspective of the entire technical routes. Hence, in this paper, we review from the perspective of researchers who try to take the first step on this topic. We review the recent representative works in the EEG-based emotion recognition research and provide a tutorial to guide the researchers to start from the beginning. The scientific basis of EEG-based emotion recognition in the psychological and physiological levels is introduced. Further, we categorize these reviewed works into different technical routes and illustrate the theoretical basis and the research motivation, which will help the readers better understand why those techniques are studied and employed. At last, existing challenges and future investigations are also discussed in this paper, which guides the researchers to decide potential future research directions.

Funder

Major Science and Technology Innovation Projects of Key R&D Programs of Shandong Province

Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Research on Cross-domain Emotion Recognition Based on Large-scale Pre-trained EEG Model

State Key Lab. for Novel Software Technology in Nanjing University

Industrial Science and Technology Research Project of Henan Province

Academy of Finland

Business Finland

EU H2020

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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