Suzuki Yasuyuki, Inoue Takuya, Nomura Taishin
Division of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan.
Front Bioeng Biotechnol. 2018 Oct 18;6:141. doi: 10.3389/fbioe.2018.00141. eCollection 2018.
Human movement analysis is often performed with a model of multi-rigid-body system, whereby reflective-marker-based motion capture data are assimilated into the model for characterizing kinematics and kinetics of the movements quantitatively. Accuracy of such analysis is limited, due to motions of the markers on the skin relative to the underlying skeletal system, referred to as the soft tissue artifact (STA). Here we propose a simple algorithm for assimilating motion capture data during periodic human movements, such as bipedal walking, into models of multi-rigid-body systems in a way that the assimilated motions are not affected by STA. The proposed algorithm assumes that STA time-profiles during periodic movements are also periodic. We then express unknown STA profiles using Fourier series, and show that the Fourier coefficients can be determined optimally based solely on the periodicity assumption for the STA and kinematic constraints requiring that any two adjacent rigid-links are connected by a rotary joint, leading to the STA-free assimilated motion that is consistent with the multi-rigid-link model. To assess the efficiency of the algorithm, we performed a numerical experiment using a dynamic model of human gait composed of seven rigid links, on which we placed STA-affected markers, and showed that the algorithm can estimate the STA accurately and retrieve the non-STA-affected true motion of the model. We also confirmed that our STA-removal processing improves accuracy of the inverse dynamics analysis, suggesting the usability of the proposed algorithm for gait analysis.
人体运动分析通常使用多刚体系统模型来进行，通过该模型将基于反光标记的运动捕捉数据同化，以定量表征运动的运动学和动力学。由于皮肤上的标记相对于其下方骨骼系统的运动，即所谓的软组织伪影（STA），这种分析的准确性受到限制。在此，我们提出一种简单算法，用于在诸如双足行走等周期性人体运动过程中将运动捕捉数据同化到多刚体系统模型中，使得同化后的运动不受STA影响。所提出的算法假设周期性运动期间的STA时间剖面也是周期性的。然后，我们使用傅里叶级数来表示未知的STA剖面，并表明仅基于STA的周期性假设以及要求任意两个相邻刚体通过旋转关节连接的运动学约束，就可以最优地确定傅里叶系数，从而得到与多刚体模型一致的无STA同化运动。为了评估该算法的效率，我们使用由七个刚体组成的人体步态动力学模型进行了数值实验，在该模型上放置了受STA影响的标记，并表明该算法能够准确估计STA并恢复模型不受STA影响的真实运动。我们还证实，我们的STA去除处理提高了逆动力学分析的准确性，这表明所提出的算法可用于步态分析。
