ORIGINAL RESEARCH article
Front. Hum. Neurosci.
Sec. Brain-Computer Interfaces
This article is part of the Research TopicBCIs for monitoring and treating mental health conditionsView all articles
Multimodal Physiological Monitoring in Augmented Reality Teaching Environments for Children with Neurodevelopmental Disorders
Provisionally accepted
- 1Zhengzhou Shengda University, Zhengzhou, China
- 2Sehan University, Yeongam-gun, Republic of Korea
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This study investigates the integration of augmented reality (AR) teaching environments with multimodal physiological monitoring for children with neurodevelopmental disorders. We collected EEG, ECG, and eye-tracking data from 115 children (ASD n=45, ADHD n=38, SLD n=32) during AR-enhanced learning tasks. The multimodal fusion approach achieved 89.3% classification accuracy in identifying disorder-specific patterns. Key biomarkers included frontal theta power variations (p<0.001), heart rate variability indices (LF/HF ratio), and fixation duration patterns. AR environments reduced cognitive load by 27% compared to traditional settings while maintaining engagement levels. Personalized intervention based on real-time physiological feedback improved attention performance by 31.2% and social interaction scores by 24.8% over 12 months. These findings demonstrate the efficacy of combining AR technology with physiological monitoring for adaptive special education.
Keywords: augmented reality, Multimodal sensors, Neurodevelopmental disorders, Cognitive Load, personalized learning
Received: 25 Sep 2025; Accepted: 31 Oct 2025.
Copyright: © 2025 ZHANG, Cho, Fengle, Hao, QiaoYan and muqing. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
SHUYI ZHANG, 102407@shengda.edu.cn
Sukyoung Cho, sukyoung9011@sehan.ac.kr
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