{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T02:25:58Z","timestamp":1773973558931,"version":"3.50.1"},"reference-count":134,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T00:00:00Z","timestamp":1749600000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>With the continuous increase in the global aging population, stroke has become one of the major diseases affecting the health of the elderly, and the upper limb motor dysfunction it causes often requires long-term rehabilitation. To improve rehabilitation outcomes for hemiplegic patients and alleviate the shortage of rehabilitation physicians, upper limb rehabilitation robots have shown great potential in enhancing motor function and improving stroke patients\u2019 rehabilitation outcomes in clinical research. This paper first classifies rehabilitation robots based on their driving mechanisms and interaction modes, describing the application of their structural features in various scenarios. It then analyzes the optimization methods used in the trajectory planning process of rehabilitation robots at different stages. Finally, based on existing shortcomings, the paper summarizes the future development directions of upper limb rehabilitation robots, providing prospects for the development of upper limb rehabilitation robots in the areas of artificial intelligence and compliant control, multi-sensory feedback and interactive training, ergonomics and new driving technologies, modular and customizable designs, and multi-modal brain stimulation techniques.<\/jats:p>","DOI":"10.3390\/robotics14060081","type":"journal-article","created":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T06:11:49Z","timestamp":1749622309000},"page":"81","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Innovations in Upper Limb Rehabilitation Robots: A Review of Mechanisms, Optimization, and Clinical Applications"],"prefix":"10.3390","volume":"14","author":[{"given":"Yang","family":"Wang","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China"}]},{"given":"Xu","family":"Han","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China"}]},{"given":"Baiye","family":"Xin","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5775-7571","authenticated-orcid":false,"given":"Ping","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"741","DOI":"10.1016\/S1474-4422(09)70150-4","article-title":"Motor recovery after stroke: A systematic review","volume":"8","author":"Langhorne","year":"2009","journal-title":"Lancet Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/S1474-4422(18)30500-3","article-title":"Stroke in China: Advances and challenges in epidemiology, prevention, and management","volume":"18","author":"Wu","year":"2019","journal-title":"Lancet Neurol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"82","DOI":"10.2302\/kjm.2022-0002-OA","article-title":"Brain\u2013machine Interface (BMI)-based neurorehabilitation for post-stroke upper limb paralysis","volume":"71","author":"Liu","year":"2022","journal-title":"Keio J. 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