Rupture of the anterior cruciate ligament (ACL) remains extremely common, with over 250,000 injuries annually. Currently, clinical tests have poor utility to accurately screen for ACL injury risk in athletes. In this study, the position of a knee marker was tracked in 2-dimensional planes to predict biomechanical variables associated with ACL injury risk. Three-dimensional kinematics and ground reaction forces were collected during bilateral, single-leg stop-jump tasks for 44 healthy male military personnel. Knee marker position data were extracted to construct 2-dimensional 95% prediction ellipses in each anatomical plane. Knee marker variables included: ellipse areas, major/minor axes lengths, orientation of ellipse axes, absolute ranges of knee position, and medial knee collapse. These variables were then used as predictor variables in stepwise multiple linear regression analyses for 7 biomechanical variables associated with ACL injury risk. Knee flexion excursion, normalized peak vertical ground reaction forces, and knee flexion angle at initial contact were the response variables that generated the highest adjusted R² values: .71, .37, and .31, respectively. The results of this study provide initial support for the hypothesis that tracking a single marker during 2-dimensional analysis can accurately reflect the information gathered from 3-dimensional motion analysis during a task assessing knee joint stability.

前十字韧带 (ACL) 断裂仍然极为常见，每年受伤人数超过 250,000 例。目前，临床测试对于准确筛查运动员 ACL 损伤风险的实用性较差。在这项研究中，在二维平面上跟踪膝盖标记的位置，以预测与 ACL 损伤风险相关的生物力学变量。在 44 名健康男性军人的双边单腿定跳任务中收集了三维运动学和地面反作用力。提取膝盖标记位置数据以在每个解剖平面中构建二维 95% 预测椭圆。膝关节标记变量包括：椭圆面积、长轴/短轴长度、椭圆轴方向、膝关节位置的绝对范围以及膝关节内侧塌陷。然后将这些变量用作与 ACL 损伤风险相关的 7 个生物力学变量的逐步多元线性回归分析中的预测变量。膝关节屈曲偏移、归一化峰值垂直地面反作用力和初始接触时的膝关节屈曲角度是产生最高调整R ²值的响应变量：分别为 0.71、0.37 和 0.31。这项研究的结果为以下假设提供了初步支持：在评估膝关节稳定性的任务期间，在 2 维分析期间跟踪单个标记可以准确地反映从 3 维运动分析收集的信息。