Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, NC, USA; Human Movement Science Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
J Biomech. 2024 Jun;171:112200. doi: 10.1016/j.jbiomech.2024.112200. Epub 2024 Jun 19.
Low-cost markerless motion capture systems offer the potential for 3D measurement of joint angles during human movement. This study aimed to validate a smartphone-based markerless motion capture system's (OpenCap) derived lower extremity kinematics during common return-to-sport tasks, comparing it to an established optoelectronic motion capture system. Athletes with prior anterior cruciate ligament reconstruction (12-18 months post-surgery) performed three movements: a jump-landing-rebound, single-leg hop, and lateral-vertical hop. Kinematics were recorded concurrently with two smartphones running OpenCap's software and with a 10-camera, marker-based motion capture system. Validity of lower extremity joint kinematics was assessed across 437 recorded trials using measures of agreement (coefficient of multiple correlation: CMC) and error (mean absolute error: MAE, root mean squared error: RMSE) across the time series of movement. Agreement was best in the sagittal plane for the knee and hip in all movements (CMC > 0.94), followed by the ankle (CMC = 0.84-0.93). Lower agreement was observed for frontal (CMC = 0.47-0.78) and transverse (CMC = 0.51-0.6) plane motion. OpenCap presented a grand mean error of 3.85° (MAE) and 4.34° (RMSE) across all joint angles and movements. These results were comparable to other available markerless systems. Most notably, OpenCap's user-friendly interface, free software, and small physical footprint have the potential to extend motion analysis applications beyond conventional biomechanics labs, thus enhancing the accessibility for a diverse range of users.
低成本的无标记运动捕捉系统为人体运动中关节角度的 3D 测量提供了潜力。本研究旨在验证一种基于智能手机的无标记运动捕捉系统(OpenCap)在常见的重返运动任务中得出的下肢运动学,将其与一种既定的光电运动捕捉系统进行比较。有前交叉韧带重建史的运动员(术后 12-18 个月)进行了三项运动:跳跃-着地-反弹、单腿跳跃和侧向垂直跳跃。运动学同时使用两部运行 OpenCap 软件的智能手机和一个 10 个摄像头、基于标记的运动捕捉系统进行记录。在 437 次记录的试验中,使用时间序列运动的一致性(多重相关系数:CMC)和误差(平均绝对误差:MAE、均方根误差:RMSE)评估下肢关节运动学的有效性。在所有运动中,矢状面的膝关节和髋关节的一致性最好(CMC>0.94),其次是踝关节(CMC=0.84-0.93)。在额状面(CMC=0.47-0.78)和横断(CMC=0.51-0.6)平面运动中观察到较低的一致性。OpenCap 在所有关节角度和运动中呈现出 3.85°(MAE)和 4.34°(RMSE)的平均误差。这些结果与其他可用的无标记系统相当。值得注意的是,OpenCap 用户友好的界面、免费的软件和较小的物理足迹有可能将运动分析应用扩展到传统的生物力学实验室之外,从而提高了各种用户的可及性。