A Review on EEG Signals Based Emotion Recognition

Soroush, Morteza Zangeneh; Maghooli, Keivan; Setarehdan, Seyed Kamaledin; Nasrabadi, Ali Motie

doi:10.15171/icnj.2017.01

Cited by 70 publications

(34 citation statements)

References 48 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The identification of emotion changes from EEG signals has recently achieved attention among BCI researchers in the process of developing different BCI devices. There are three excellent review articles (Al-Nafjan et al, 2017;Soroush et al, 2018;Xu T. et al, 2018) on EEG-based emotion recognition. These articles might be of help to the interested readers to further have an insight of the EEG-based emotion recognition.…”

Section: Bci Emotion Recognitionmentioning

confidence: 99%

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

et al. 2020

View full text Add to dashboard Cite

Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves. It is worth noting that the application of BCI is not limited to medical applications, and hence, the research in this field has gained due attention. Moreover, the significant number of related publications over the past two decades further indicates the consistent improvements and breakthroughs that have been made in this particular field. Nonetheless, it is also worth mentioning that with these improvements, new challenges are constantly discovered. This article provides a comprehensive review of the state-of-the-art of a complete BCI system. First, a brief overview of electroencephalogram (EEG)-based BCI systems is given. Secondly, a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics. Finally, the challenges to the recent BCI systems are discussed, and possible solutions to mitigate the issues are recommended.

show abstract

Section: Bci Emotion Recognitionmentioning

confidence: 99%

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Affective computing, which is an interdisciplinary field based on psychology, computer science, and biomedical engineering [ 629 ], will likely play an important role. Several studies have focused on identifying the cognitive-emotional state of subjects by using machine-learning algorithms and by achieving high levels of accuracy [ 630 , 631 ]. Many neuroimaging techniques have been used [ 632 ].…”

Section: Discussionmentioning

confidence: 99%

The Cognitive-Emotional Design and Study of Architectural Space: A Scoping Review of Neuroarchitecture and Its Precursor Approaches

Higuera-Trujillo

Llinares

Macagno

2021

Sensors

View full text Add to dashboard Cite

Humans respond cognitively and emotionally to the built environment. The modern possibility of recording the neural activity of subjects during exposure to environmental situations, using neuroscientific techniques and virtual reality, provides a promising framework for future design and studies of the built environment. The discipline derived is termed “neuroarchitecture”. Given neuroarchitecture’s transdisciplinary nature, it progresses needs to be reviewed in a contextualised way, together with its precursor approaches. The present article presents a scoping review, which maps out the broad areas on which the new discipline is based. The limitations, controversies, benefits, impact on the professional sectors involved, and potential of neuroarchitecture and its precursors’ approaches are critically addressed.

show abstract

“…Correlation is a term commonly used to describe whether or not there is a relationship with something else [19] [20]. In simple terms, that is precisely what understanding correlation means.…”

Section: Fast Fourier Transformmentioning

confidence: 99%

Recognizing Human Emotion patterns by applying Fast Fourier Transform based on Brainwave Features

Yudhana

Mukhopadhyay²,

Karaş

et al. 2019

2019 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

View full text Add to dashboard Cite

The natural ability of humans to receive messages from the surrounding environment can be obtained through the senses. The senses will respond to stimuli received in various conditions including emotional conditions. Psychologically, recognizing human emotions directly can be assessed from several criteria, such as facial expressions, sounds, or body movements. This research aims to analyze human emotions from the biomedical side through brainwave signals using EEG sensors. The EEG signal obtained will be extracted using Fast Fourier Transform and first-order statistical features. four emotional conditions (normal, focus, sadness and shock emotions). The results of this research are expected to help improve users in knowing their mental state accurately. The development of this kind of emotional analysis has the potential to create wide applications in the future environment. Research results have shown and compared frequency stimuli from normal emotions, sadness, focus and shock in a variety of situations. Monitoring of EEG Signals is obtained by grouping based on

show abstract

A Review on EEG Signals Based Emotion Recognition

Cited by 70 publications

References 48 publications

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

The Cognitive-Emotional Design and Study of Architectural Space: A Scoping Review of Neuroarchitecture and Its Precursor Approaches

Recognizing Human Emotion patterns by applying Fast Fourier Transform based on Brainwave Features

Contact Info

Product

Resources

About