A Review of EEG-Based Emotion Recognition Methods for Emotional Intelligence Evaluation in Children

Author(s)	Ms. Manjiri Suhas Deshmukh, Ms. Rushika Deepak Kinjawadekar, Dr. Mukta Dhopeshwarkar
Country	India
Abstract	Emotional intelligence (EI) has been increasingly linked to academic performance, cognitive development, and emotional well-being in children. EEG is a good tool for evaluating emotional intelligence (EI) since it is a non-invasive method of studying how the brain processes emotions. This review examines studies on emotion recognition using EEG in children ages 5 to 18. We investigated eight public or semi-public EEG mood datasets and many research paper out that several of them lack child-specific data. Using filtered spatial pattern techniques with support vector machines (SVMs) achieved up to 97.2% accuracy on datasets tailored for children, according to our comparison of 18 distinct emotion categorization algorithms. Convolutional neural networks (CNNs) and other deep learning models have not been extensively investigated in children, despite their excellent performance on sizable adult datasets (above 98% accuracy).
Keywords	Emotional Intelligence, Cognitive Abilities, EEG, Emotion Recognition, Educational Interventions
Field	Computer > Data / Information
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-11-20
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.60495

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