EEG Based Emotion Recognition: A Tutorial and Review

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.

Automated summary

Emotion recognition technology using EEG signals is crucial in Artificial Intelligence, with applications in emotional health care, human-computer interaction, and multimedia content recommendation. This paper reviews recent representative works in EEG-based emotion recognition research from the perspective of researchers taking the first step in this field. It introduces the scientific basis of EEG-based emotion recognition and categorizes reviewed works into different technical routes, providing readers with a better understanding of the motivation behind these studies. The paper also discusses existing challenges and future research directions.