De Momi Elena, Lopomo Nicola, Cerveri Pietro, Zaffagnini Stefano, Safran Marc R, Ferrigno Giancarlo
NearLab, Dipartimento di Bioingegneria, Politecnico di Milano, Italy.
J Biomech. 2009 May 29;42(8):989-95. doi: 10.1016/j.jbiomech.2009.02.031. Epub 2009 Apr 24.
Hip joint centre (HJC) localization is used in several biomedical applications, such as movement analysis and computer-assisted orthopaedic surgery. The purpose of this study was to validate in vitro a new algorithm (MC-pivoting) for HJC computation and to compare its performances with the state-of-the-art (least square approach-LSA). The MC-pivoting algorithm iteratively searches for the 3D coordinates of the point belonging to the femoral bone that, during the circumduction of the femur around the hip joint (pivoting), runs the minimum length trajectory. The algorithm was initialized with a point distribution that can be considered close to a Monte Carlo simulation sampling all around the LSA estimate. The performances of the MC-pivoting algorithm, compared with LSA, were evaluated with tests on cadavers. Dynamic reference frames were applied on both the femur and the pelvis and were tracked by an optical localizer. Results proved the algorithm accuracy (1.7mm+/-1.6, 2.3-median value+/-quartiles), reliability (smaller upper quartiles of the errors distribution with respect to LSA) and robustness (reduction of the errors also in case of large pelvis displacements).
髋关节中心(HJC)定位在多个生物医学应用中有所使用,比如运动分析和计算机辅助骨科手术。本研究的目的是在体外验证一种用于HJC计算的新算法(MC旋转法),并将其性能与现有技术(最小二乘法-LSA)进行比较。MC旋转法算法会迭代搜索属于股骨的点的三维坐标,在股骨围绕髋关节旋转(旋转)过程中,该点运行的轨迹长度最短。算法初始化时使用的点分布可被视为接近围绕LSA估计值进行全面蒙特卡洛模拟采样的结果。通过对尸体进行测试,评估了MC旋转法算法与LSA相比的性能。在股骨和骨盆上均应用了动态参考系,并通过光学定位器进行跟踪。结果证明了该算法的准确性(1.7毫米±1.6,中位数为2.3±四分位数)、可靠性(相对于LSA,误差分布的上四分位数更小)以及稳健性(在骨盆大幅位移的情况下误差也会减小)。