[Application and prospects of medical-engineering integration technology in rehabilitation following total knee arthroplasty].

康复 数据集成 适应(眼睛) 虚拟现实 康复机器人 机器人学 计算机科学 系统集成 物理医学与康复 过程管理 匹配(统计) 远程康复 客观性(哲学) 全膝关节置换术 知识管理 风险分析(工程) 远程医疗 钥匙(锁) 医学 人工智能 工作流程 可控性 梅德林 平面图(考古学)
作者
Xilin Gao,Aifeng Liu,Chao Zhang,Ping Wang,Minshan Feng,Bifeng Fu
出处
期刊:PubMed [National Institutes of Health]
卷期号:39 (1): 105-12
标识
DOI:10.12200/j.issn.1003-0034.20251009
摘要

This paper systematically reviews the relevant literature from the China National Knowledge Infrastructure (CNKI) and Web of Science databases, focusing on the three key components of rehabilitation after total knee arthroplasty (TKA):evaluation, intervention, and management. It summarizes the progress of medical-engineering integration technologies. Quantitative assessment methods, such as gait analysis, enhance the objectivity and continuity of functional evaluations but are constrained by issues like inconsistent data standards. Rehabilitation robotics offers controllability and traceability, making it promising for personalized treatment plans, though challenges related to equipment costs and scene adaptation remain. AI-assisted decision-making systems integrate multi-source information for treatment recommendations, improving decision-making efficiency and accuracy, but their effectiveness is limited by dependence on data quality. Immersive virtual reality (VR) training enhances engagement, improves proprioception, and helps manage pain, but its effectiveness is influenced by device limitations and individual tolerance. Remote rehabilitation systems significantly improve the continuity of management, yet their widespread implementation faces challenges, including low acceptance among older adults and inadequate infrastructure. Current research hotspots are mainly focused on device development, data integration and interoperability, and strengthening clinical evidence. The authors suggest that future efforts should strengthen interdisciplinary collaboration and conduct high-quality clinical research to establish a generalizable intelligent precision rehabilitation model.

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