Cargando…

EEG-Based BCI Emotion Recognition: A Survey

Affecting computing is an artificial intelligence area of study that recognizes, interprets, processes, and simulates human affects. The user’s emotional states can be sensed through electroencephalography (EEG)-based Brain Computer Interfaces (BCI) devices. Research in emotion recognition using the...

Descripción completa

Detalles Bibliográficos
Autores principales: Torres, Edgar P., Torres, Edgar A., Hernández-Álvarez, Myriam, Yoo, Sang Guun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570756/
https://www.ncbi.nlm.nih.gov/pubmed/32906731
http://dx.doi.org/10.3390/s20185083
_version_ 1783597020751069184
author Torres, Edgar P.
Torres, Edgar A.
Hernández-Álvarez, Myriam
Yoo, Sang Guun
author_facet Torres, Edgar P.
Torres, Edgar A.
Hernández-Álvarez, Myriam
Yoo, Sang Guun
author_sort Torres, Edgar P.
collection PubMed
description Affecting computing is an artificial intelligence area of study that recognizes, interprets, processes, and simulates human affects. The user’s emotional states can be sensed through electroencephalography (EEG)-based Brain Computer Interfaces (BCI) devices. Research in emotion recognition using these tools is a rapidly growing field with multiple inter-disciplinary applications. This article performs a survey of the pertinent scientific literature from 2015 to 2020. It presents trends and a comparative analysis of algorithm applications in new implementations from a computer science perspective. Our survey gives an overview of datasets, emotion elicitation methods, feature extraction and selection, classification algorithms, and performance evaluation. Lastly, we provide insights for future developments.
format Online
Article
Text
id pubmed-7570756
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75707562020-10-28 EEG-Based BCI Emotion Recognition: A Survey Torres, Edgar P. Torres, Edgar A. Hernández-Álvarez, Myriam Yoo, Sang Guun Sensors (Basel) Review Affecting computing is an artificial intelligence area of study that recognizes, interprets, processes, and simulates human affects. The user’s emotional states can be sensed through electroencephalography (EEG)-based Brain Computer Interfaces (BCI) devices. Research in emotion recognition using these tools is a rapidly growing field with multiple inter-disciplinary applications. This article performs a survey of the pertinent scientific literature from 2015 to 2020. It presents trends and a comparative analysis of algorithm applications in new implementations from a computer science perspective. Our survey gives an overview of datasets, emotion elicitation methods, feature extraction and selection, classification algorithms, and performance evaluation. Lastly, we provide insights for future developments. MDPI 2020-09-07 /pmc/articles/PMC7570756/ /pubmed/32906731 http://dx.doi.org/10.3390/s20185083 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Torres, Edgar P.
Torres, Edgar A.
Hernández-Álvarez, Myriam
Yoo, Sang Guun
EEG-Based BCI Emotion Recognition: A Survey
title EEG-Based BCI Emotion Recognition: A Survey
title_full EEG-Based BCI Emotion Recognition: A Survey
title_fullStr EEG-Based BCI Emotion Recognition: A Survey
title_full_unstemmed EEG-Based BCI Emotion Recognition: A Survey
title_short EEG-Based BCI Emotion Recognition: A Survey
title_sort eeg-based bci emotion recognition: a survey
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570756/
https://www.ncbi.nlm.nih.gov/pubmed/32906731
http://dx.doi.org/10.3390/s20185083
work_keys_str_mv AT torresedgarp eegbasedbciemotionrecognitionasurvey
AT torresedgara eegbasedbciemotionrecognitionasurvey
AT hernandezalvarezmyriam eegbasedbciemotionrecognitionasurvey
AT yoosangguun eegbasedbciemotionrecognitionasurvey