Solav Dana, Camomilla Valentina, Cereatti Andrea, Barré Arnaud, Aminian Kamiar, Wolf Alon
Department of Mechanical Engineering, Technion Israel Institute of Technology, 32000 Haifa, Israel.
Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", 00135 Rome, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal system, University of Rome "Foro Italico", 00135 Rome, Italy.
J Biomech. 2017 Sep 6;62:110-116. doi: 10.1016/j.jbiomech.2017.01.026. Epub 2017 Feb 1.
The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8deg for orientation, 1.5/4.2mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3deg, 5.8/12.3mm), was compared with RBLS (4.3/6.6deg, 6.9/16.6mm) and HDLS (4.6/7.6deg, 6.7/12.5mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy.
本研究的目的是分析基于以三角形柯塞尔点元素（TCPEs）为特征的三个皮肤标记子簇的骨位姿估计的准确性，并评估四种可在体内无创测量的瞬时物理参数识别最准确TCPEs的能力。此外，使用刚体（RBLS）和均匀变形（HDLS）假设，将TCPE位姿估计与应用于所有标记簇的两种最小二乘最小化方法的估计进行了比较。对先前收集的体内跑步机步态数据进行了分析，该数据由双平面荧光透视跟踪受试者膝关节假体的金标准骨位姿以及跟踪受软组织伪影影响的皮肤标记的立体摄影测量系统的同步测量组成。使用多达35个标记的簇，为18名受试者计算了从皮肤标记簇估计的股骨方向和位置误差。基于金标准数据的结果表明，存在TCPEs的瞬时子集，其以合理的准确性估计股骨位姿（站立/摆动期间的中值均方根误差：方向为1.4/2.8度，位置为1.5/4.2毫米）。将用于位姿估计的选择准确TCPEs的无创且瞬时标准（4.8/7.3度，5.8/12.3毫米）与RBLS（4.3/6.6度，6.9/16.6毫米）和HDLS（4.6/7.6度，6.7/12.5毫米）进行了比较。考虑均匀变形，使用HDLS或选定的TCPEs产生的位置估计比RBLS方法更准确，相反，RBLS方法产生的方向估计更准确。需要进一步研究以设计有效的簇选择标准，这可能会显著提高骨位姿估计的准确性。
