TY - JOUR
T1 - AI-Driven Rehabilitation Robotics
T2 - Advancements in and Impacts on Patient Recovery
AU - Abbas, Ghulam Husain
AU - Speksnijder, Caroline
AU - Ramnarain, Dharmanand
AU - Parmar, Chetan
AU - Parmar, Aum
AU - Ahmad, Suhaib
AU - Pouwels, Sjaak
N1 - Copyright © 2025, Abbas et al.
PY - 2025/10
Y1 - 2025/10
N2 - The integration of artificial intelligence (AI) in rehabilitation robotics (RR) can be regarded as a significant advancement in patient recovery processes. RR refers to robotic technologies that are designed to support therapy and/or healing processes by applying tailored, adaptive, and efficient machine learning algorithms. This paper is a methodological narrative review discussing the latest trends in the application of AI in RR and its effects on the recovery of patients with stroke, spinal cord injury, and musculoskeletal disorders. Technological advancements in real-time monitoring, feedback, and intelligent data analysis have enhanced the effectiveness of these systems, providing patients with personalized rehabilitation programs that are progressive in nature, based on the patients' improvement. Research evidence demonstrates that the use of AI-driven robotic systems in clinical practice significantly improves motor skills, the rate of recovery, and overall patients' well-being, in contrast to conventional rehabilitation procedures. Moreover, the review highlights the drawbacks and problems that present-day technologies have; these problems concern the costs, the absence of unified protocols, and legal requirements. Furthermore, the combination of AI with RR will likely progress even more, with ongoing research studying ways in which the system's intelligence could be upgraded, patients' involvement in the process could be increased, and the applicability of these technologies to various forms of needs could be increased as well. The present review thus highlights the importance and the role of AI-RR in enhancing the patient's recovery and opens the way for therapeutic practices. This narrative review was informed by targeted searches in PubMed, Scopus, and IEEE Xplore covering 2015-2025, with an emphasis on English-language, peer‑reviewed studies in stroke, spinal cord injury, and musculoskeletal rehabilitation; no formal meta-analytic synthesis was undertaken, consistent with a narrative approach.
AB - The integration of artificial intelligence (AI) in rehabilitation robotics (RR) can be regarded as a significant advancement in patient recovery processes. RR refers to robotic technologies that are designed to support therapy and/or healing processes by applying tailored, adaptive, and efficient machine learning algorithms. This paper is a methodological narrative review discussing the latest trends in the application of AI in RR and its effects on the recovery of patients with stroke, spinal cord injury, and musculoskeletal disorders. Technological advancements in real-time monitoring, feedback, and intelligent data analysis have enhanced the effectiveness of these systems, providing patients with personalized rehabilitation programs that are progressive in nature, based on the patients' improvement. Research evidence demonstrates that the use of AI-driven robotic systems in clinical practice significantly improves motor skills, the rate of recovery, and overall patients' well-being, in contrast to conventional rehabilitation procedures. Moreover, the review highlights the drawbacks and problems that present-day technologies have; these problems concern the costs, the absence of unified protocols, and legal requirements. Furthermore, the combination of AI with RR will likely progress even more, with ongoing research studying ways in which the system's intelligence could be upgraded, patients' involvement in the process could be increased, and the applicability of these technologies to various forms of needs could be increased as well. The present review thus highlights the importance and the role of AI-RR in enhancing the patient's recovery and opens the way for therapeutic practices. This narrative review was informed by targeted searches in PubMed, Scopus, and IEEE Xplore covering 2015-2025, with an emphasis on English-language, peer‑reviewed studies in stroke, spinal cord injury, and musculoskeletal rehabilitation; no formal meta-analytic synthesis was undertaken, consistent with a narrative approach.
U2 - 10.7759/cureus.94273
DO - 10.7759/cureus.94273
M3 - Review article
C2 - 41216066
SN - 2168-8184
VL - 17
JO - Curēus
JF - Curēus
IS - 10
M1 - e94273
ER -