Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cyncoed Campus, Cardiff CF23 6XD, UK.
Sport and Health Sciences, University of Exeter, St Luke's Campus, Exeter EX1 2LU, UK.
Sensors (Basel). 2022 Nov 29;22(23):9286. doi: 10.3390/s22239286.
Given the high rates of both primary and secondary anterior cruciate ligament (ACL) injuries in multidirectional field sports, there is a need to develop easily accessible methods for practitioners to monitor ACL injury risk. Field-based methods to assess knee variables associated with ACL injury are of particular interest to practitioners for monitoring injury risk in applied sports settings. Knee variables or proxy measures derived from wearable inertial measurement units (IMUs) may thus provide a powerful tool for efficient injury risk management. Therefore, the aim of this study was to identify whether there were correlations between laboratory-derived knee variables (knee range of motion (RoM), change in knee moment, and knee stiffness) and metrics derived from IMUs (angular velocities and accelerations) placed on the tibia and thigh, across a range of movements performed in practitioner assessments used to monitor ACL injury risk. Ground reaction forces, three-dimensional kinematics, and triaxial IMU data were recorded from nineteen healthy male participants performing bilateral and unilateral drop jumps, and a 90° cutting task. Spearman's correlations were used to examine the correlations between knee variables and IMU-derived metrics. A significant strong positive correlation was observed between knee RoM and the area under the tibia angular velocity curve in all movements. Significant strong correlations were also observed in the unilateral drop jump between knee RoM, change in knee moment, and knee stiffness, and the area under the tibia acceleration curve (r = 0.776, r = -0.712, and r = -0.765, respectively). A significant moderate correlation was observed between both knee RoM and knee stiffness, and the area under the thigh angular velocity curve (r = 0.682 and r = -0.641, respectively). The findings from this study suggest that it may be feasible to use IMU-derived angular velocities and acceleration measurements as proxy measures of knee variables in movements included in practitioner assessments used to monitor ACL injury risk.
鉴于多向性场地运动中前交叉韧带（ACL）原发和继发损伤的高发病率，有必要开发一种易于临床医生使用的方法来监测 ACL 损伤风险。评估与 ACL 损伤相关的膝关节变量的基于场地的方法对于在应用运动环境中监测损伤风险的临床医生特别感兴趣。因此，来自可穿戴惯性测量单元（IMU）的膝关节变量或代理测量值可能为高效的损伤风险管理提供强大的工具。因此，本研究的目的是确定在用于监测 ACL 损伤风险的临床医生评估中进行的一系列运动中，实验室得出的膝关节变量（膝关节活动范围（ROM）、膝关节力矩变化和膝关节刚度）与 IMU（胫骨和大腿上的角速度和加速度）得出的指标之间是否存在相关性。本研究从 19 名健康男性参与者中记录了地面反作用力、三维运动学和三轴 IMU 数据，这些参与者执行双侧和单侧跳降以及 90°变向任务。使用 Spearman 相关分析来检查膝关节变量与 IMU 衍生指标之间的相关性。在所有运动中，膝关节 ROM 与胫骨角速度曲线下面积之间存在显著强正相关。在单侧跳降中，膝关节 ROM、膝关节力矩变化和膝关节刚度与胫骨加速度曲线下面积之间也存在显著强相关性（r = 0.776、r = -0.712 和 r = -0.765）。膝关节 ROM 和膝关节刚度与大腿角速度曲线下面积之间也存在显著中度相关性（r = 0.682 和 r = -0.641）。本研究的结果表明，在用于监测 ACL 损伤风险的临床医生评估中包含的运动中，使用 IMU 衍生的角速度和加速度测量值作为膝关节变量的代理测量值可能是可行的。
