EEG Based Emotion Recognition: A Tutorial and Review

No Thumbnail Available
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal

Other link related to publication
Date
2022
Major/Subject
Mcode
Degree programme
Language
en
Pages
57
1–57
Series
ACM COMPUTING SURVEYS, Volume 55, issue 4
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.
Description
| openaire: EC/H2020/101016775/EU//INTERVENE
Keywords
Citation
Li , X , Zhang , Y , Tiwari , P , Song , D , Hu , B , Yang , M , Zhao , Z , Kumar , N & Marttinen , P 2022 , ' EEG Based Emotion Recognition: A Tutorial and Review ' , ACM Computing Surveys , vol. 55 , no. 4 , 79 , pp. 1–57 . https://doi.org/10.1145/3524499