Mechanical and Materials Engineering, Queen's University, Canada.
Mechanical and Materials Engineering, Queen's University, Canada.
J Biomech. 2021 Oct 11;127:110665. doi: 10.1016/j.jbiomech.2021.110665. Epub 2021 Aug 3.
Kinematic analysis is a useful and widespread tool used in research and clinical biomechanics for the quantification of human movement. Common marker-based optical motion capture systems are time intensive and require highly trained operators to obtain kinematic data. Markerless motion capture systems offer an alternative method for the measurement of kinematic data with several practical benefits. This work compared the kinematics of human gait measured using a deep learning algorithm-based markerless motion capture system to those from a standard marker-based motion capture system. Thirty healthy adult participants walked on a treadmill while data were simultaneously recorded using eight video cameras and seven infrared optical motion capture cameras, providing synchronized markerless and marker-based data for comparison. The average root mean square distance (RMSD) between corresponding joint centers was less than 2.5 cm for all joints except the hip, which was 3.6 cm. Lower limb segment angles relative to the global coordinate system indicated the global segment pose estimates from both systems were very similar, with RMSD of less than 5.5° for all segment angles except those that represent rotations about the long axis of the segment. Lower limb joint angles captured similar patterns for flexion/extension at all joints, ab/adduction at the knee and hip, and toe-in/toe-out at the ankle. These findings indicate that the markerless system would be a suitable alternative technology in cases where the practical benefits of markerless data collection are preferred.
运动学分析是一种在人体运动的研究和临床生物力学中广泛应用的、用于量化人体运动的有用工具。常见的基于标记的光学运动捕捉系统需要大量的时间，并且需要经过高度训练的操作人员来获取运动学数据。无标记运动捕捉系统提供了一种替代方法来测量运动学数据，具有几个实际的好处。本工作比较了基于深度学习算法的无标记运动捕捉系统测量的人体步态运动学与基于标记的标准运动捕捉系统的运动学。三十名健康成年人在跑步机上行走，同时使用八台摄像机和七台红外光学运动捕捉摄像机同步记录数据，为比较提供了无标记和基于标记的同步数据。除了髋关节为 3.6 厘米之外，所有关节的对应关节中心的平均均方根距离（RMSD）均小于 2.5 厘米。相对于全局坐标系的下肢节段角度表明，两个系统的全局节段姿态估计非常相似，除了代表节段长轴旋转的那些角度外，所有节段角度的 RMSD 都小于 5.5°。下肢关节角度在所有关节的屈伸、膝关节和髋关节的内收/外展以及踝关节的内翻/外翻都呈现出相似的模式。这些发现表明，在无标记数据采集的实际好处更受青睐的情况下，无标记系统将是一种合适的替代技术。
