Work

Managing Classroom Behavior in School-Aged Children With ADHD Using AI-Empowered Vest

Year: 2025

Type: article

Abstract: Attention deficit hyperactivity disorder (ADHD) is one of the prevalent neurodevelopmental disorders that affects school-age children. Although various treatments are currently available for ADHD, immediate and automated strategies for managing classroom behavior in children with ADHD are still limited. This study introduces an artificial intelligence (AI) empowered vest to monitor classroom activity and provide real-time vibration interventions to help manage hyperactive behavior. The vest integrates two inertial measurement units to collect behavioral data, and a neural network classifies it as typical or hyperactive. The vibration motor will be activated to remind the children to adjust their posture after detecting hyperactive behavior. A controlled experiment was conducted with 40 children aged 7-12 years to evaluate the accuracy of the vest behavior classification and the effectiveness of its vibration-based intervention. Each child attended the same lesson with three sections in the pre-test and the post-test. Vibration interventions were introduced during the post-test in the second and third sections. The teacher used a five-point scale to rate the children's performance in each section. The classification and intervention accuracy on the test set was 0.84. A significant reduction in activity level was observed after the vibration intervention, and teacher performance ratings improved significantly in sections with the intervention (p <0.05, Wilcoxon Signed-Rank Test). These findings suggest that the proposed system provides a promising real-time solution for behavioral intervention in classroom settings.

Source: IEEE Transactions on Neural Systems and Rehabilitation Engineering

DOI: 10.1109/tnsre.2025.3637761