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Deep learning-based EEG emotion recognition: Current trends and future perspectives

Automatic electroencephalogram (EEG) emotion recognition is a challenging component of human–computer interaction (HCI). Inspired by the powerful feature learning ability of recently-emerged deep learning techniques, various advanced deep learning models have been employed increasingly to learn high...

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Autores principales: Wang, Xiaohu, Ren, Yongmei, Luo, Ze, He, Wei, Hong, Jun, Huang, Yinzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009917/
https://www.ncbi.nlm.nih.gov/pubmed/36923142
http://dx.doi.org/10.3389/fpsyg.2023.1126994
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author Wang, Xiaohu
Ren, Yongmei
Luo, Ze
He, Wei
Hong, Jun
Huang, Yinzhen
author_facet Wang, Xiaohu
Ren, Yongmei
Luo, Ze
He, Wei
Hong, Jun
Huang, Yinzhen
author_sort Wang, Xiaohu
collection PubMed
description Automatic electroencephalogram (EEG) emotion recognition is a challenging component of human–computer interaction (HCI). Inspired by the powerful feature learning ability of recently-emerged deep learning techniques, various advanced deep learning models have been employed increasingly to learn high-level feature representations for EEG emotion recognition. This paper aims to provide an up-to-date and comprehensive survey of EEG emotion recognition, especially for various deep learning techniques in this area. We provide the preliminaries and basic knowledge in the literature. We review EEG emotion recognition benchmark data sets briefly. We review deep learning techniques in details, including deep belief networks, convolutional neural networks, and recurrent neural networks. We describe the state-of-the-art applications of deep learning techniques for EEG emotion recognition in detail. We analyze the challenges and opportunities in this field and point out its future directions.
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spelling pubmed-100099172023-03-14 Deep learning-based EEG emotion recognition: Current trends and future perspectives Wang, Xiaohu Ren, Yongmei Luo, Ze He, Wei Hong, Jun Huang, Yinzhen Front Psychol Psychology Automatic electroencephalogram (EEG) emotion recognition is a challenging component of human–computer interaction (HCI). Inspired by the powerful feature learning ability of recently-emerged deep learning techniques, various advanced deep learning models have been employed increasingly to learn high-level feature representations for EEG emotion recognition. This paper aims to provide an up-to-date and comprehensive survey of EEG emotion recognition, especially for various deep learning techniques in this area. We provide the preliminaries and basic knowledge in the literature. We review EEG emotion recognition benchmark data sets briefly. We review deep learning techniques in details, including deep belief networks, convolutional neural networks, and recurrent neural networks. We describe the state-of-the-art applications of deep learning techniques for EEG emotion recognition in detail. We analyze the challenges and opportunities in this field and point out its future directions. Frontiers Media S.A. 2023-02-27 /pmc/articles/PMC10009917/ /pubmed/36923142 http://dx.doi.org/10.3389/fpsyg.2023.1126994 Text en Copyright © 2023 Wang, Ren, Luo, He, Hong and Huang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Wang, Xiaohu
Ren, Yongmei
Luo, Ze
He, Wei
Hong, Jun
Huang, Yinzhen
Deep learning-based EEG emotion recognition: Current trends and future perspectives
title Deep learning-based EEG emotion recognition: Current trends and future perspectives
title_full Deep learning-based EEG emotion recognition: Current trends and future perspectives
title_fullStr Deep learning-based EEG emotion recognition: Current trends and future perspectives
title_full_unstemmed Deep learning-based EEG emotion recognition: Current trends and future perspectives
title_short Deep learning-based EEG emotion recognition: Current trends and future perspectives
title_sort deep learning-based eeg emotion recognition: current trends and future perspectives
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009917/
https://www.ncbi.nlm.nih.gov/pubmed/36923142
http://dx.doi.org/10.3389/fpsyg.2023.1126994
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