Artificial Intelligence in Pediatric Rehabilitation: A New Era of Personalized Therapy

Pediatric rehabilitation is crucial for children with neuromuscular disorders, developmental delays, and injuries, aiming to restore motor and cognitive functions through therapy. However, traditional rehabilitation methods often lack personalization, relying on generalized treatment protocols that may not account for individual variability in progress and response to therapy. Recent advancements in artificial intelligence (AI) have revolutionized pediatric rehabilitation by enabling data-driven, adaptive, and patient-specific treatment strategies. AI technologies such as machine learning, computer vision, natural language processing (NLP), and robotics facilitate real-time monitoring, predictive analytics, and automated decision-making, leading to more precise and effective rehabilitation. AI-powered motion tracking enhances motor assessment, while gamified virtual reality (VR) environments improve engagement in therapy. Additionally, robotic-assisted rehabilitation, integrated with AI algorithms, optimizes therapeutic interventions for children with conditions like cerebral palsy and pediatric stroke. Despite these advancements, challenges remain, including data privacy concerns, biases in AI models, accessibility barriers, and ethical considerations regarding AI-driven decision-making in healthcare. Regulatory frameworks must evolve to ensure safe and equitable AI applications in pediatric therapy. This paper