Recognition of human emotions using EEG signals: A review

Md Mustafizur Rahman; Ajay Krishno Sarkar; Md Amzad Hossain; Md Selim Hossain; Md Rabiul Islam; Md Biplob Hossain; Julian M W Quinn; Mohammad Ali Moni

doi:10.1016/j.compbiomed.2021.104696

Recognition of human emotions using EEG signals: A review

Comput Biol Med. 2021 Sep:136:104696. doi: 10.1016/j.compbiomed.2021.104696. Epub 2021 Aug 3.

Authors

Md Mustafizur Rahman¹, Ajay Krishno Sarkar², Md Amzad Hossain³, Md Selim Hossain⁴, Md Rabiul Islam⁵, Md Biplob Hossain⁶, Julian M W Quinn⁷, Mohammad Ali Moni⁸

Affiliations

¹ Department of Electrical and Electronic Engineering, Jashore University of Science & Technology, Jashore, 7408, Bangladesh. Electronic address: mustafizur.170710@gmail.com.
² Department of Electrical and Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi, 6204, Bangladesh. Electronic address: sarkarajay139@gmail.com.
³ Department of Electrical and Electronic Engineering, Jashore University of Science & Technology, Jashore, 7408, Bangladesh. Electronic address: mahossain.eee@gmail.com.
⁴ Department of Electrical and Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi, 6204, Bangladesh. Electronic address: engg.selim@gmail.com.
⁵ Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh. Electronic address: rabiul.kuet.bd@gmail.com.
⁶ Department of Electrical and Electronic Engineering, Jashore University of Science & Technology, Jashore, 7408, Bangladesh. Electronic address: biplobh.eee10@gmail.com.
⁷ Healthy Ageing Theme, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia. Electronic address: j.quinn@garvan.org.au.
⁸ Healthy Ageing Theme, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia; School of Health and Rehabilitation Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland St Lucia, QLD 4072, Australia. Electronic address: m.moni@uq.edu.au.

PMID: 34388471
DOI: 10.1016/j.compbiomed.2021.104696

Abstract

Assessment of the cognitive functions and state of clinical subjects is an important aspect of e-health care delivery, and in the development of novel human-machine interfaces. A subject can display a range of emotions that significantly influence cognition, and emotion classification through the analysis of physiological signals is a key means of detecting emotion. Electroencephalography (EEG) signals have become a common focus of such development compared to other physiological signals because EEG employs simple and subject-acceptable methods for obtaining data that can be used for emotion analysis. We have therefore reviewed published studies that have used EEG signal data to identify possible interconnections between emotion and brain activity. We then describe theoretical conceptualization of basic emotions, and interpret the prevailing techniques that have been adopted for feature extraction, selection, and classification. Finally, we have compared the outcomes of these recent studies and discussed the likely future directions and main challenges for researchers developing EEG-based emotion analysis methods.

Keywords: Classification; Electroencephalography; Emotion; Recognition.

Publication types

Review

MeSH terms

Algorithms
Cognition
Electroencephalography*
Emotions*
Humans