基于视频的无标记运动捕捉在临床与康复生物力学中的应用：一项遵循PRISMA-ScR范围综述的验证架构、临床就绪度与新兴方法研究
Video-Based Markerless Motion Capture for Clinical and Rehabilitation Biomechanics: A PRISMA-ScR Scoping Review of Validated Architectures, Clinical Readiness, and Emerging Methods
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- Université Côte d'Azur（蔚蓝海岸大学）
- Centre Hospitalier Universitaire de Nice（尼斯大学附属医院）
- Institut Universitaire de France（法国大学研究院）
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中文总结 AI 辅助
该综述评估了视频无标记运动捕捉在临床生物力学中的验证现状，发现其精度未达临床标准，尤其在病理人群和平面外运动学方面，并提出了面向未来的设计指南。
中文摘要 AI 辅助
背景：基于视频的无标记运动捕捉有望在无需光电系统所带来的成本、空间和皮肤标记物限制的情况下进行运动分析，在临床和康复环境中尤其具有潜力。然而，经过验证的处理流程是否已能提供临床可接受的生物力学结果，以及它们与底层计算机视觉研究之间的关系，仍不明确。方法：我们按照范围综述的PRISMA扩展指南进行了一项范围综述，采用了注册方案，并检索了PubMed、Scopus和IEEE Xplore数据库（时间范围从2015年1月至2026年2月；计算机视觉部分的检索更新至2026年7月）。研究采用双层设计，将经过验证的生物力学研究的主要语料库与经过精选且刻意非详尽的补充性新兴计算机视觉工作语料库配对，后者用于定性分析。我们绘制了研究特征、处理流程架构、验证方法和关节角度精度。结果：我们纳入了117项研究，其中大多数发表于2024年及以后，研究对象为在实验室中行走的健康成年人。处理流程在单目和多摄像头模态下形成了五个架构家族；大多数报告了原始关节角度，而未进行生物力学优化。矢状面下肢一致性集中在5至6度左右，通常未达到临床可接受水平，而平面外运动学、动力学以及病理或老年人群的验证则很少。新兴的计算机视觉构建模块（如基础模型网格恢复、可微逆运动学、基于视频的动力学）在验证研究中几乎缺失。结论：对于临床关节运动学而言，基于视频的无标记捕捉尚不能与基于标记的系统互换使用，并且在康复最需要的领域——老年和病理人群、平面外运动学和动力学——其验证仍然不足。通过将这些证据空白与新兴的计算机视觉进展进行映射，我们提出了生成假设的设计指南（而非一种经过验证的方法），以引导下一代处理流程走向可及且具有临床意义的运动分析。
英文摘要
Background.. Video-based markerless motion capture promises movement analysis without the cost, space and skin-marker constraints of optoelectronic systems, with particular potential for clinical and rehabilitation settings. Whether validated pipelines yet deliver clinically acceptable biomechanics, and how they relate to the underlying computer-vision research, remains unclear. Methods. We conducted a scoping review following the PRISMA extension for Scoping Reviews, with a registered protocol and searches of PubMed, Scopus and IEEE Xplore (January 2015 to February 2026; the computer-vision scan was updated to July 2026). A dual-tier design paired a primary corpus of validated biomechanical studies with a complementary, curated and deliberately non-exhaustive corpus of emerging computer-vision work, used qualitatively. We charted study characteristics, pipeline architecture, validation methods and joint-angle accuracy. Results. We included 117 studies, most published from 2024 onward and conducted on healthy adults walking in a laboratory. Pipelines formed five architectural families across monocular and multi-camera modalities; most reported raw joint angles without biomechanical refinement. Sagittal lower-limb agreement clustered around 5 to 6{\textdegree}, generally short of clinical acceptability, while out-of-plane kinematics, kinetics, and pathological or older populations were rarely validated. Emerging computer-vision building blocks (foundation-model mesh recovery, differentiable inverse kinematics, video-based kinetics) were almost absent from validated studies. Conclusions. Video-based markerless capture is not yet interchangeable with marker-based systems for clinical joint kinematics, and it remains barely validated where rehabilitation needs it most: older and pathological populations, out-of-plane kinematics, and kinetics. Mapping this evidence gap onto emerging computer-vision advances, we propose hypothesis-generating design guidelines, not a validated method, to steer the next generation of pipelines toward accessible, clinically meaningful movement analysis.
