Abstract
Recent developments and studies in brain-computer interface (BCI) technologies have facilitated emotion detection and classification. Many BCI studies have sought to investigate, detect, and recognize participants’ emotional affective states. The applied domains for these studies are varied, and include such fields as communication, education, entertainment, and medicine. To understand trends in electroencephalography (EEG)-based emotion recognition system research and to provide practitioners and researchers with insights into and future directions for emotion recognition systems, this study set out to review published articles on emotion detection, recognition, and classification. The study also reviews current and future trends and discusses how these trends may impact researchers and practitioners alike. We reviewed 285 articles, of which 160 were refereed journal articles that were published since the inception of affective computing research. The articles were classified based on a scheme consisting of two categories: research orientation and domains/applications. Our results show considerable growth of EEG-based emotion detection journal publications. This growth reflects an increased research interest in EEG-based emotion detection as a salient and legitimate research area. Such factors as the proliferation of wireless EEG devices, advances in computational intelligence techniques, and machine learning spurred this growth.
Highlights
A Brain Computer Interface (BCI) is a system that takes a biosignal, measured from a person, and predicts certain aspects of the person’s cognitive state [1,2]
BCIs started as assistive technological solutions for individuals with significant speech anomalies
The extensity of our search was limited, it offers a comprehensive insight into EEG-based emotion recognition system research
Summary
A Brain Computer Interface (BCI) is a system that takes a biosignal, measured from a person, and predicts (in real-time) certain aspects of the person’s cognitive state [1,2]. BCIs started as assistive technological solutions for individuals with significant speech anomalies. The research was rooted in a subject’s desire to communicate through either speech or writing or to control his or her immediate environment. BCI systems have used computer-based recreational activities to stimulate a subject’s innate ability to overcome physical disabilities. BCI-based research has been expanded to include people with and without physical disabilities. The entire system underscores how adaptive systems can enhance analytic methods and application areas. This assistive ability has created a widespread awareness among potential users and researchers alike. In the past 15 years, the increasing numbers of BCI research groups, peer-reviewed
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