ACL损伤预防的运动分析技术：从实验室评估到场地临床筛查
简介
这篇综述系统梳理了从实验室光学系统到可穿戴惯性传感器、计算机视觉及无人机平台等运动分析技术在ACL损伤预防中的应用，并提出了一个三级临床筛查框架：从基础人体测量和单平面视频分析，逐步升级至多模态生物力学评估与实时运动反馈。文章以无人机结合智能鞋垫系统为例，展示了在真实运动场景中实现实验室级生物力学评估的可行性，为临床医生在基层开展低成本、可推广的ACL损伤风…
英文摘要
Anterior cruciate ligament (ACL) injuries remain a leading cause of morbidity in athletic populations, with 70-80% occurring through non-contact mechanisms driven by biomechanical risk factors including knee valgus (>10°), low knee flexion (<30°), tibial internal rotation (>20°), and loading asymmetry (>15°), yet implementation of evidence-based neuromuscular training (which reduces injury risk by 50-70%) remains limited due to barriers in identifying at-risk individuals through accessible field-based screening. This narrative review synthesizes motion analysis technologies spanning laboratory-based optical systems (marker-based), wearable inertial measurement units (IMUs), computer vision and marker-less pose estimation, force plate and pressure-sensitive insole systems, and integrated drone-based field assessment platforms to address this critical gap. We present a three-tier clinical screening framework that progresses from basic anthropometric and single-plane video analysis to multi-modal biomechanical assessment using real-time kinematic feedback. As an illustrative example of emerging field-deployable technology, an integrated drone-based motion capture and smart insole system combining 4K video capture, AI-driven 3D motion reconstruction, and plantar pressure mapping is described to demonstrate how laboratory-quality biomechanical assessment can be achieved in ecologically valid field settings. This evidence-based review addresses current gaps between laboratory research and practical field deployment, with emphasis on cost-effectiveness, accessibility, and clinical utility for ACL injury prevention in diverse sporting environments.