Global Journal of Engineering and Technology Research (GJETR) · Research article · Open access
Conceptual Framework for AI Emotional Recognition in Children with Learning Difficulties for Paediatric Screening
Marcella Peter, Jackie Ting Tiew Wei, Khairunnisa Ibrahim
30 May 2026 · Vol. 2, Issue 5, pp. 160-163
DOI: 10.65150/EP-gjetr/V2E5/2026-05
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What is this article about?
Assessing the emotional states of children with learning difficulties (LD) is critical for effective pedagogical and clinical intervention. However, existing diagnostic methods rely on subjective observations which are prone to human bias and lack a localised Asian-centric perspective.
Article at a glance
- Published
- 30 May 2026
- Volume / issue / pages
- Vol. 2, Issue 5, pp. 160-163
- ISSN
- 3051-3782 (online) · 3051-3774 (print)
- Licence
- CC BY 4.0 — free to read and reuse with attribution
- Peer review
- Double-blind, at least two independent reviewers
- Publisher
- EP Journals Group
Abstract
Assessing the emotional states of children with learning difficulties (LD) is critical for effective pedagogical and clinical intervention. However, existing diagnostic methods rely on subjective observations which are prone to human bias and lack a localised Asian-centric perspective. This concept paper proposes an AI-based Facial Emotional Recognition (FER) initiative designed to provide objective, real-time assessment of emotional engagement in children with dyslexia during learning activities. The framework utilises a mixed-methods approach, combining a Convolutional Neural Network (CNN) pipeline for video-to-image emotion classification with clinical field validation at the SPARK Child Development Centre. The system leverages 3D depth-sensing technology via Intel RealSense to extract 468 facial landmarks. Preliminary validation of the initiative’s expert-rated dataset achieved a Cohen’s Kappa of 0.87, indicating excellent inter-rater reliability. By bridging the gap between traditional psychiatric screening and modern affective computing, this digitalisation initiative supports the SDG 4 goals, offering a scalable tool for more precise and timely support for children with learning disabilities.
Keywords: Achievement of Emotion, Affective Computing, CNN, Dyslexia, Facial Emotional Recognition, Machine Learning
Cite this article
Marcella Peter, Jackie Ting Tiew Wei, & Khairunnisa Ibrahim (2026). Conceptual Framework for AI Emotional Recognition in Children with Learning Difficulties for Paediatric Screening. Global Journal of Engineering and Technology Research, 2(5), 160-163. https://doi.org/10.65150/EP-gjetr/V2E5/2026-05
@article{Marcella2026,
title = {Conceptual Framework for AI Emotional Recognition in Children with Learning Difficulties for Paediatric Screening},
author = {Marcella Peter and Jackie Ting Tiew Wei and Khairunnisa Ibrahim},
journal = {Global Journal of Engineering and Technology Research},
year = {2026},
volume = {2},
number = {5},
pages = {160-163},
doi = {10.65150/EP-gjetr/V2E5/2026-05},
url = {https://doi.org/10.65150/EP-gjetr/V2E5/2026-05}
}Questions about this article
Who wrote this article?
Marcella Peter, Jackie Ting Tiew Wei, Khairunnisa Ibrahim.
Where and when was it published?
In Global Journal of Engineering and Technology Research, Volume 2, Issue 5, pages 160-163, published by EP Journals Group on 30 May 2026.
Is this article free to read?
Yes. It is open access under a Creative Commons Attribution 4.0 (CC BY 4.0) licence, so anyone can read, share and reuse it with attribution.
What is the DOI of this article?
10.65150/EP-gjetr/V2E5/2026-05 (https://doi.org/10.65150/EP-gjetr/V2E5/2026-05).
How do I cite this article?
APA: Marcella Peter, Jackie Ting Tiew Wei, & Khairunnisa Ibrahim (2026). Conceptual Framework for AI Emotional Recognition in Children with Learning Difficulties for Paediatric Screening. Global Journal of Engineering and Technology Research, 2(5), 160-163. https://doi.org/10.65150/EP-gjetr/V2E5/2026-05
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