The Key Technologies and Technological Evolution Mechanisms of Robotic Systems for Fracture Reduction Surgery
Robot‐assisted fracture reduction (RAFR) systems have undergone nearly three decades of development, offering the potential to improve reduction accuracy, reduce radiation exposure, and alleviate surgeon fatigue. This review synthesizes 150 publications from 1995 to 2024 identified through structured database searches and citation tracking. Representative RAFR systems are reviewed and compared in terms of robotic architectures, bone–robot interfaces, registration and navigation, path planning, control strategies, and validation evidence. Based on the characteristics of technological evolution, the development of RAFR systems is categorized into four stages: the conceptual emergence stage, the initial development phase, the stage of rapid advancement, and the clinical validation phase. For each phase, the review outlines the evolution of core technologies such as robot structure, perception systems, control strategies, and surgical integration. Despite notable advancements, current RAFR systems still face limitations in adaptability to complex fracture types and clinical workflow integration. This review critically evaluates these challenges and outlines prospective directions that are poised to drive the next generation of intelligent, autonomous RAFR systems. These insights aim to drive the transition of RAFR systems from passive fixation tools to intelligent, autonomous surgical platforms, ultimately providing safer and more efficient treatment solutions for orthopedic patients.
Authors
- Fang Wang (ORCID: https://orcid.org/0000-0003-3827-9935)
- Shaolong Kuang (ORCID: https://orcid.org/0000-0001-5590-7943)
- Xue Zhang (ORCID: https://orcid.org/0000-0001-9639-1453)
- Xiaoyang Hu
- Jianhua Li
- Lihai Zhang (ORCID: https://orcid.org/0009-0003-5257-7397)
Institutions
- Shenzhen Institute of Information Technology (CN)
- Shenzhen University (CN)
- Chinese PLA General Hospital (CN)
- Shenzhen Technology University (CN)
Publication Details
- Journal
- Advanced Intelligent Systems
- Published
- 2026-10-14
- DOI
- https://doi.org/10.1002/aisy.70560
- Primary Topic
- Bone fractures and treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00