Artificial Intelligence in Neurological Rehabilitation: Current Applications, Challenges, and Future Perspectives—A Narrative Review

Abstract

Background: Artificial intelligence (AI) is increasingly being integrated into neurological rehabilitation, offering innovative approaches to improve assessment, treatment planning, patient monitoring, and functional recovery.

Objective: To review the current applications, benefits, challenges, and prospects of AI in neurological rehabilitation.

Methods: A narrative review was conducted by searching PubMed, Scopus, Web of Science, Embase, and Google Scholar for English-language articles published between 2015 and 2026. Relevant studies on AI applications in neurological rehabilitation were included and synthesized narratively.

Key Findings: AI technologies, including machine learning, rehabilitation robotics, brain-computer interfaces, virtual reality, wearable sensors, and tele-rehabilitation, have demonstrated potential to enhance motor and cognitive recovery, enable personalised rehabilitation, improve clinical decision-making, and increase access to rehabilitation services. However, challenges related to data privacy, clinical validation, ethical issues, and implementation remain.

Conclusion: AI has the potential to transform neurological rehabilitation by enabling personalised, efficient, and patient-centred care. Further high-quality research and standardized implementation strategies are needed to facilitate its safe integration into routine clinical practice