Chèze L, Fregly B J, Dimnet J
Centre de Mécanique, Université Claude Bernard Lyon I, Villeurbanne, France.
J Biomech. 1995 Jul;28(7):879-84. doi: 10.1016/0021-9290(95)95278-d.
When video-based motion analysis systems are used to measure segmental kinematics, the major source of error is the displacement of skin-fixed markers relative to the underlying skeletal structure. Such displacements cause the marker representation of the segment to deform, thereby decreasing the accuracy of subsequent three-dimensional kinematic calculations. We have developed a two-step solidification procedure to address this problem. First, the mean rigid shape is computed which best represents the time-varying marker configuration of each segment. Second, a least-squares minimization is used to replace the measured marker coordinates with those corresponding to the best-fit mean rigid shape. Rigid body theory can then be applied unambiguously to perform kinematic analyses. To evaluate this approach, we defined an unperturbed three-dimensional reference movement using kinematic data from the swing phase of gait. After perturbing the marker coordinates with artificial noise, the rotation matrix and translation vector (absolute and relative movement) between each pair of successive images were computed using (1) reference frames fixed directly to the perturbed marker coordinates, (2) a least-squares minimization procedure found in the literature, and (3) the proposed solidification procedure. The least-squares and solidification procedures produced extremely similar results which, relative to the direct calculation, reduced kinematic errors on average by 20-25% when the maximum distance between markers was small (e.g. < 15 cm). The solidification methodology therefore combines the numerical benefits of the least-squares method with the conceptual benefits of a rigid body method.
当使用基于视频的运动分析系统来测量节段运动学时,误差的主要来源是皮肤固定标记相对于其下方骨骼结构的位移。这种位移会导致节段的标记表示变形,从而降低后续三维运动学计算的准确性。我们开发了一种两步凝固程序来解决这个问题。首先,计算平均刚体形状,它能最好地表示每个节段随时间变化的标记配置。其次,使用最小二乘法最小化,用与最佳拟合平均刚体形状对应的坐标替换测量的标记坐标。然后可以明确应用刚体理论来进行运动学分析。为了评估这种方法,我们使用步态摆动期的运动学数据定义了一个无扰动的三维参考运动。在用人工噪声干扰标记坐标后,使用以下方法计算每对连续图像之间的旋转矩阵和平移向量(绝对和相对运动):(1) 直接固定在受干扰标记坐标上的参考系;(2) 文献中找到的最小二乘法最小化程序;(3) 提出的凝固程序。最小二乘法和凝固程序产生了极其相似的结果,相对于直接计算,当标记之间的最大距离较小时(例如 < 15 cm),运动学误差平均降低了20 - 25%。因此,凝固方法将最小二乘法的数值优势与刚体方法的概念优势结合了起来。