Application of Artificial Intelligence in Physical Rehabilitation of Patients Admitted to the Intensive Care Unit: A Scoping Review

Abstract

Background and aims: Artificial intelligence (AI) has proven to be a highly useful tool in the clinical setting, especially in the Intensive Care Unit (ICU). The use of various AI-mediated instruments to guide medical treatments and even support surgical procedures has been previously described, but there is still no aggregated evidence on its usefulness in assisting the physical rehabilitation process of critically ill patients, understanding that this is extremely important to prevent the development of muscle weakness in the ICU. This review, therefore, aimed to describe the usefulness of AI in supporting the physical rehabilitation of patients admitted to the ICU. Materials and methods: This scoping review was conducted following the Joanna Briggs Institute (JBI) methodology, originally developed by Arksey and O'Malley. A structured search strategy based on a Population, Concept, and Context (PCC) framework was used to search PubMed, Web of Science, Scopus, and the Virtual Health Library (VHL) databases. Results: The initial search yielded 116 articles. After removing duplicates and applying exclusion criteria during title and abstract screening, eight studies were included in the final analysis. Identified tools included noninvasive mobility sensors, robotic assistance systems, machine learning algorithms, and software to support musculoskeletal ultrasound assessment. Conclusion: Artificial intelligence is emerging as a key tool for ICU rehabilitation, offering objective data, enhancing patient monitoring, and streamlining assessment processes. How to cite this article: Payán-Salcedo HA, Castro Aguilera AM, Salinas Batioja MF, Castillo Diaz LM. Application of Artificial Intelligence in Physical Rehabilitation of Patients Admitted to the Intensive Care Unit: A Scoping Review. Indian J Crit Care Med 2025;29(10):851-860.

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