Barré Arnaud, Jolles Brigitte M, Theumann Nicolas, Aminian Kamiar
Laboratory of Movement Analysis and Measurement (LMAM), EPFL, Lausanne, Switzerland.
Department of Orthopaedic Surgery and Traumatology, CHUV and University of Lausanne, Lausanne, Switzerland.
J Biomech. 2015 Jul 16;48(10):1965-71. doi: 10.1016/j.jbiomech.2015.04.007. Epub 2015 Apr 17.
Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9 mm and 15.3 mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0 mm to 16.2 mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.
从皮肤标记估计的节段姿势和关节运动学受到软组织伪影（STA）及其刚性运动成分（STARM）的高度影响。虽然四个标记簇可以减少步态活动期间的STA非刚性运动，但其他数据，如标记位置或STARM模式，对于临床步态分析中补偿STA至关重要。本研究提出：1）设计一个综合平均图，说明跑步机步态期间下肢STA的空间分布；2）从分配到从空间分布中提取的区域的四个标记簇分析STARM。所有实验均使用立体摄影测量系统跟踪皮肤标记，并使用双平面荧光透视系统跟踪膝关节假体。使用贴在下肢的80个标记对19名受试者进行STA空间分布的计算。从大腿分布图中提取了三个不同区域。大腿近端区域和小腿近端区域的标记位移分别最大达到24.9 mm和1�.3 mm。大腿上的STARM比小腿上的大，簇方向的均方根误差在1.2°至8.1°之间。平移均方根误差也很大（3.0 mm至1６.2 mm）。没有标记簇能正确补偿STARM。然而，多元相关系数在皮肤和骨骼运动学之间以及受试者之间的STARM方面表现出优异的分数。这些相关性突出了STARM与运动学成分之间的依赖性。本研究为步态活动的STARM建模提供了新的见解。
