ReviewComputational intelligence and neuroscience2020
EEG-Based Emotion Recognition: A State-of-the-Art Review of Current Trends and Opportunities.
Review in Computational intelligence and neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
70 citing papers in PubMed, 1 synthesis or guideline pooled it, 339 citations in OpenAlex.
- Datasets for Automated Affect and Emotion Recognition from Cardiovascular Signals Using Artificial Intelligence- A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Electroencephalography-Based Emotion Recognition Using Auditory Stimulation for Affective Brain-Computer Interfaces.Sensors (Basel, Switzerland) · 2026Article
- Smart Wearable EEG Devices: A Review of Lightweight, Multi-Sensor Systems for Sleep and Everyday Neurophysiology.Biosensors · 2026Review
- A 1D-CNN with advanced data augmentation for robust speech emotion recognition.Scientific reports · 2026Article
- Effect of Emotional States on EEG-Based Biometric Identification: A Comparative Study of Classifiers.Bioengineering (Basel, Switzerland) · 2026Article
- EEG-based dynamic emotion recognition using multi-scale wavelet transform with a Spatio-Temporal neural network.Scientific reports · 2026Article
- Emotion Recognition Ability in Preschoolers: Outcomes of a Socio-Emotional Intervention.Brain sciences · 2026Article
- Emerging trends and clinical challenges in AI-enhanced emotion diagnosis using physiological data.Medical & biological engineering & computing · 2026Review
- A subject-specific mechanistic model of affect links electroencephalography, cardiorespiratory feedback, and monoaminergic dynamics.Frontiers in computational neuroscience · 2026Article
- Article
- Traditional Machine Learning Outperforms EEGNet for Consumer-Grade EEG Emotion Recognition: A Comprehensive Evaluation with Cross-Dataset Validation.Sensors (Basel, Switzerland) · 2025Article
- Graph-theoretical analysis of EEG-based functional connectivity during emotional experience in virtual reality for emotion recognition.Scientific reports · 2025Article
- EEG-Based Local-Global Dimensional Emotion Recognition Using Electrode Clusters, EEG Deformer, and Temporal Convolutional Network.Bioengineering (Basel, Switzerland) · 2025Article
- MFA-CNN: An Emotion Recognition Network Integrating 1D-2D Convolutional Neural Network and Cross-Modal Causal Features.Brain sciences · 2025Article
- Facial electromyogram-based emotion recognition for virtual reality applications using machine learning classifiers trained on posed expressions.Biomedical engineering letters · 2025Article
- Acquisition Of Balinese Imagined Spelling using Electroencephalogram (BISE) Dataset.Data in brief · 2025Article
- Cross-Subject Motor Imagery Electroencephalogram Decoding with Domain Generalization.Bioengineering (Basel, Switzerland) · 2025Article
- Speech emotion recognition with light weight deep neural ensemble model using hand crafted features.Scientific reports · 2025Article
- A Comparative Study of Machine Learning and Deep Learning Models for Automatic Parkinson's Disease Detection from Electroencephalogram Signals.Diagnostics (Basel, Switzerland) · 2025Article
- An intelligent emotion prediction system using improved sand cat optimization technique based on EEG signals.Scientific reports · 2025Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing interest of the research community towards establishing some meaningful "emotional" interactions between humans and computers, the need for reliable and deployable solutions for the identification of human emotional states is required. Recent developments in using electroencephalography (EEG) for emotion recognition have garnered strong interest from the research community as the latest developments in consumer-grade wearable EEG solutions can provide a cheap, portable, and simple solution for identifying emotions. Since the last comprehensive review was conducted back from the years 2009 to 2016, this paper will update on the current progress of emotion recognition using EEG signals from 2016 to 2019. The focus on this state-of-the-art review focuses on the elements of emotion stimuli type and presentation approach, study size, EEG hardware, machine learning classifiers, and classification approach. From this state-of-the-art review, we suggest several future research opportunities including proposing a different approach in presenting the stimuli in the form of virtual reality (VR). To this end, an additional section devoted specifically to reviewing only VR studies within this research domain is presented as the motivation for this proposed new approach using VR as the stimuli presentation device. This review paper is intended to be useful for the research community working on emotion recognition using EEG signals as well as for those who are venturing into this field of research.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.