Precision Rehabilitation 2.0: From One-Size-Fits-All Therapy to Intelligent Personalized Care
Abstract
Rehabilitation sciences are in a transition mode where generic treatment models are more and more being replaced by personalized treatment models using technology. Since there are substantial differences in recovery potential, biomechanics, psychosocial status and lifestyle amongst patients, the interventions for rehabilitation have, to a great extent, been standardized in the past 30 years. The increasing integration of Artificial Intelligence (AI), wearable technologies, digital biomarkers, robotics, and the use of big data analytics, however, is changing rehabilitation to a more individualized and adaptive field, called precision rehabilitation.
References
Attoh-Mensah E, Boujut A, Desmons M, Perrochon A. Artificial intelligence in personalized rehabilitation: current applications and a SWOT analysis. Frontiers in Digital Health. 2025 Jul 24;7:1606088. DOI: https://doi.org/10.3389/fdgth.2025.1606088
Cotton RJ, Seamon BA, Segal RL, Davis RD, Sahu A, McLeod MM, Celnik P, Ramey SL. A causal framework for precision rehabilitation. arXiv preprint arXiv:2411.03919. 2024 Nov 6. DOI: https://doi.org/10.48550/arXiv.2411.03919
Rawashdeh SA, Reimann E, Uhl TL. Highly-Individualized physical therapy instruction beyond the clinic using wearable inertial sensors. IEEE access. 2022 Jan 14;10:14564-74. DOI: 10.1109/ACCESS.2022.3143765
Abdalla N, El Arab RA, Abdrbo A, Almari M, Ayoub MY, Alsaaideh B, Dagamseh MS, Almagharbeh WT, Abuadas F, Abu Mahfouz MS, Gaballah MK. Artificial intelligence in rehabilitation: a review of clinical effectiveness, real-world performance, safety, and equity across modalities and settings. Frontiers in Digital Health. 2026 Mar 18;8:1737957. DOI: https://doi.org/10.3389/fdgth.2026.1737957
Dai Y, Tang C, Zhang R, Yang W, Zhang Y, Wang Y, Chen J, Chen X, Xie R, Cao Y, Li Q. A data-physics hybrid generative model for patient-specific post-stroke motor rehabilitation using wearable sensor data. arXiv e-prints. 2025 Dec:arXiv-2512.
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Copyright (c) 2026 Jaza Rizvi
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