Emotion recognition with EEG-based brain-computer interfaces: a systematic literature review

Emotion recognition with EEG-based brain-computer interfaces: a systematic literature review

Electroencephalography (EEG)-based Brain-Computer Interface (BCI) systems for emotion recognition have the potential to assist the enrichment of human–computer interaction with implicit information since they can enable understanding of the cognitive and emotional activities of humans. Therefore, th...

Full description

Saved in:
Bibliographic Details
Published in:Multimedia tools and applications Vol. 83; no. 33; pp. 79647 - 79694
Main Authors: Erat, Kübra, Şahin, Elif Bilge, Doğan, Furkan, Merdanoğlu, Nur, Akcakaya, Ahmet, Durdu, Pınar Onay
Format: Journal Article
Language:English
Published: New York Springer US 01-03-2024
Springer Nature B.V
Subjects:
Algorithms
Computer Communication Networks
Computer Science
Data processing
Data Structures and Information Theory
Electroencephalography
Emotion recognition
Emotions
Feature extraction
Human-computer interface
Literature reviews
Modules
Multimedia Information Systems
Performance evaluation
Signal processing
Special Purpose and Application-Based Systems
Systematic review
Track 3: Biometrics and HCI
Trends
Brain-computer interface
Emotion recognition
Affective computing
Emotion
Affective brain-computer interface (aBCI)
Human–computer interaction
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Electroencephalography (EEG)-based Brain-Computer Interface (BCI) systems for emotion recognition have the potential to assist the enrichment of human–computer interaction with implicit information since they can enable understanding of the cognitive and emotional activities of humans. Therefore, these systems have become an important research topic today. This study aims to present trends and gaps on this topic by performing a systematic literature review based on the 216 published scientific literature gathered from various databases including ACM, IEEE Xplore, PubMed, Science Direct, and Web of Science from 2016 to 2020. This review gives an overview of all the components of EEG based BCI system from the signal stimulus module which includes the employed device, signal stimuli, and data processing modality, to the signal processing module which includes signal acquisition, pre-processing, feature extraction, feature selection, classification algorithms, and performance evaluation. Thus, this study provides an overview of all components of an EEG-based BCI system for emotion recognition and examines the available evidence in a clear, concise, and systematic way. In addition, the findings are aimed to inform researchers about the issues on what are research trends and the gaps in this field and guide them in their research directions.
ISSN:1573-7721
1380-7501
1573-7721
DOI:10.1007/s11042-024-18259-z