AI Applications for Cerebral Palsy: Focused Review on Diagnosis, Motion Analysis and Rehabilitation

Auns Al-Neami; Moneer Faraj; Lama  Bou Farah; Lina Bachache; Rasha  Massoud; Rufaida  Hussain; Saleh Massoud; Mhd Al Hinnawi; Ahmed Hussein; Samer  Alabed; Sami  Bennour

doi:10.22153/kej.2026.02.001

Authors

Auns Qusai Al-Neami Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Baghdad, Iraq https://orcid.org/0000-0001-9069-1586
Moneer K. Faraj Training and Curricula of The Arabian Board of Neurosurgery, College of Medicine, University of Baghdad, Baghdad, Iraq https://orcid.org/0000-0002-4574-5001
Lama Bou Farah Biomedical Technologies Department, Lebanese German University, Lebanon https://orcid.org/0009-0000-6737-8794
Lina Nasseer Bachache Medical Instrumentation Engineering Techniques Department, College of Technical Engineering, Mashreq University, Baghdad, Iraq
Rasha Massoud Biomedical Engineering Department, Faculty of Mechanical and Electrical Engineering, Damascus University, Syria
Rufaida Hussain Faculty of Biomedical Engineering, Al-Andalus Private University for Medical Sciences, Tartous, Syria https://orcid.org/0000-0003-2668-9769
Saleh Ibrahieem Massoud Biomedical Engineering Department, Faculty of Mechanical and Electrical Engineering, Damascus University, Damascus, Syria
Mhd Firas Al Hinnawi Biomedical Engineering Department, Faculty of Mechanical and Electrical Engineering, Damascus University, Damascus, Syria
Ahmed F. Hussein Department of Artificial Intelligence and Robotics Engineering, College of Engineering, Al-Nahrain University, Baghdad, Iraq
Samer Alabed Department of Biomedical Engineering, School of Applied Medical Sciences, German Jordanian University, Amman, Jordan https://orcid.org/0000-0002-8273-5419
Sami Bennour Mechanical Laboratory of Sousse, National School of Engineers of Sousse, University of Sousse, Tunisia https://orcid.org/0000-0002-4817-9092

DOI:

https://doi.org/10.22153/kej.2026.02.001

Keywords:

Cerebral palsy; Artificial intelligence; Machine learning; Motion analysis; Rehabilitation systems; Clinical decision support

Abstract

Early diagnosis and effective rehabilitation of cerebral palsy (CP) are essential for improving functional outcomes and reducing long-term complications. CP affects the ability to perform daily physical activities and is often associated with secondary health problems such as obesity and chronic pain. Owing to the complexity of the condition, rehabilitation typically requires continuous supervision by clinical specialists, which can be challenging in environments with limited resources. Recent advances in artificial intelligence (AI) have created new opportunities for enhancing CP healthcare. This review summarises the major applications of AI in diagnosis, clinical decision support, motion classification and rehabilitation systems. AI-based diagnostic tools—including medical-image analysis using MRI and CT—support the early detection of neural abnormalities. Motion-classification systems use physical activity data, functional motor scales and gait analysis features to detect deviations and evaluate treatment progress. In rehabilitation, AI is increasingly integrated into robotic systems, virtual reality environments, video game-based training and metaverse-based therapies, enabling adaptive and engaging therapeutic experiences. This study highlights the shift towards AI-enhanced interventions, discusses the importance of human–computer interfaces for improving interaction between patients and rehabilitation systems and outlines current limitations and challenges. Continued research is required to improve data quality, model generalisability and clinical integration of AI technologies in CP care.

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