Early Detection and Effective Treatment for ADHD using Machine Learning for Sri Lankan Children

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder that significantly impacts children's behavior, attention, and ability to learn. In Sri Lanka, there is limited awareness, resources, and accessibility to therapy services for children with ADHD. Early identification of ADHD is crucial for effective treatment, but traditional approaches in Sri Lanka have limitations in accurately identifying the disorder and providing adequate interventions. To address these challenges, this research emphasizes the development of a comprehensive mobile application utilizing game-based features, machine learning, image processing, motion detection, and speech recognition technology to enhance the early detection and treatment of ADHD in Sri Lankan children. The primary objective of this research is to accurately identify ADHD symptoms in children and offer treatments through a mobile application. The application offers interactive activities designed to address specific ADHD symptoms, supporting children's cognitive development, improving attention, concentration, memorizing, the ability to follow directions, and the ability to respond to a command. This research adopts a multidisciplinary approach, integrating principles from psychology, computer science, and machine learning. The findings inform the development of more accessible and effective interventions for children with ADHD in Sri Lanka and similar settings, ultimately improving the quality of life for affected children.