Abstract
Cerebral Palsy (CP) is a disorder of limited functional activity and motor disorders caused by damage or developing abnormality in a prenatal or newborn child brain. Traditional methods of CP rehabilitation rely on subjective therapist assessments, lacking objective data-driven evaluations, and time efficiency. This paper reviews modern artificial intelligence (AI) based technologies that can be applied in Kazakhstan’s rehabilitation system. Nineteen peer-reviewed studies were analyzed and AI-driven technologies were grouped into three main categories: automated clinical assessment, predictive and personalized machine learning models, and real-time adaptive systems. The results showed that such innovations can maintain reliability of the treatment, increase accessibility of rehabilitation services, reduce clinician workload, and allow continuous activity monitoring. However, implementation of some innovations are limited by data quality, data quantity, additional hardware setup and ethical consideration. Overall, the integration of AI into Kazakhstan’s rehabilitation system holds great potential to make rehabilitation more objective, accessible, and personalized – eventually, improving the quality of life for people with cerebral palsy.