Transforming Behavioral Care for Children with Special Needs: Leveraging Artificial Intelligence for Systematic Monitoring and Support
Oluchi Uzoaru Anyom1*, Simene Baribie Sangha2, Elo-Oghene Imonifano3, Shaleye Anuoluwapo Bukola4
Abstract
The landscape of behavioral care for children with special needs is undergoing a revolutionary transformation by integrating artificial intelligence technologies. This comprehensive review examines how AI-driven systems enhance systematic monitoring and support mechanisms for children with autism spectrum disorder, attention deficit hyperactivity disorder, and other developmental conditions. This study reveals significant improvements in early detection, personalized interventions, and real-time behavioral monitoring by analyzing current research on machine learning diagnostics, wearable sensor technologies, digital therapeutics, and conversational AI systems. The evidence demonstrates that AI technologies can achieve diagnostic accuracies exceeding 90% while providing continuous, objective behavioral assessments that were previously impossible with traditional methods. However, implementation challenges, including cost barriers, privacy concerns, and the need for specialized training, remain significant obstacles to widespread adoption. This review synthesizes findings from multiple systematic reviews and empirical studies to provide a roadmap for the ethical and practical implementation of AI technologies in pediatric behavioral care settings.
Keywords:
Artificial Intelligence, Children with special needs, Machine learning, Behavioral care, Child monitoring
