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Appl. Sci. 2017, 7(12), 1239; https://doi.org/10.3390/app7121239

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

1
College of Computer and Information Sciences, Imam Muhammad bin Saud University, Riyadh 11432, Saudi Arabia
2
College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
3
Center for Complex Engineering Systems at KACST and MIT, King Abdulaziz City for Science and Technology, Riyadh 11442, Saudi Arabia
*
Author to whom correspondence should be addressed.
Received: 30 September 2017 / Revised: 26 November 2017 / Accepted: 28 November 2017 / Published: 1 December 2017
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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. View Full-Text
Keywords: brain-computer interface; electroencephalogram; emotion detection; affective computing; emotion recognition; systematic literature review brain-computer interface; electroencephalogram; emotion detection; affective computing; emotion recognition; systematic literature review
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Al-Nafjan, A.; Hosny, M.; Al-Ohali, Y.; Al-Wabil, A. Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review. Appl. Sci. 2017, 7, 1239.

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