Revista Politécnica de la Ciencia · Aug 5, 2026
Applications of artificial intelligence in geriatric physical therapy: advances, challenges, and perspectives for improving the quality of life of older adults
By Quingatuña ETL, Naula MFQ, Amancha3 LMP et al.
Demographic aging has increased the prevalence of functional limitations, falls, and musculoskeletal and neurological diseases in the older population, leading to the emergence of more precise, accessible, and personalized rehabilitation models. Artificial intelligence (IA) has positioned itself as an emerging tool capable of optimizing physical therapy assessment, treatment, and follow-up in the older population. To identify, through a literature review, the main applications of artificial intelligence in geriatric physical therapy, as well as the advances, limitations, and perspectives it may offer for improving the quality of life of older adults. A narrative literature review supported by the PRISMA guidelines was conducted, and indexed databases (PubMed, Scopus, Web of Science, ScienceDirect, and SciELO) were searched, selecting articles published between 2016 and 2026, in Spanish and English, that addressed the use of artificial intelligence in physical therapy, rehabilitation, and geriatric health. It has been observed that machine learning and deep learning algorithms, wearable sensors, robotic exoskeletons, artificial intelligence-assisted telerehabilitation, and gamified virtual reality improve fall risk prediction, diagnostic accuracy, treatment adherence, and functional outcomes in balance, gait, and mobility in the older population, although most studies have methodological limitations as well as small samples. The findings are consistent with the international literature in indicating that artificial intelligence complements, but does not replace, the physical therapist's clinical judgment, and that addressing ethical, privacy, and digital literacy barriers is essential. Artificial intelligence is shown to be a promising tool for transforming geriatric physical therapy toward a more predictive, personalized model centered on the older person, although its incorporation requires clear regulatory frameworks, continuing professional education, and rigorous clinical validation.