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Evaluation of functional methods of joint centre determination for quasi-planar movement

机译:准平面运动关节中心确定功能方法的评价

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摘要

Functional methods identify joint centres as the centre of rotation (CoR) of two adjacent movements during an ad-hoc movement. The methods have been used for functionally determining hip joint centre in gait analysis and have revealed advantages compared to predictive regression techniques. However, the current implementation of functional methods hinders its application in clinical use when subjects have difficulties performing multi-plane movements over the required range. In this study, we systematically investigated whether functional methods can be used to localise the CoR during a quasi-planar movement. The effects of the following factors were analysed: the algorithms, the range and speed of the movement, marker cluster location, marker cluster size and distance to the joint centre. A mechanical linkage was used in our study to isolate the factors of interest and give insight to variation in implementation of functional methods. Our results showed the algorithms and cluster locations significantly affected the estimate results. For all algorithms, a significantly positive relationship between CoR errors and the distance of proximal cluster coordinate location to the joint centre along the medial-lateral direction was observed while the distal marker clusters were best located as close as possible to the joint centre. By optimising the analytical and experimental factors, the transformation algorithms achieved a root mean square error (RMSE) of 5.3 mm while the sphere fitting methods yielded the best estimation with an RMSE of 2.6 mm. The transformation algorithms performed better in presence of random noise and simulated soft tissue artefacts.
机译:功能方法将关节中心确定为临时运动期间两个相邻运动的旋转中心(CoR)。该方法已用于步态分析中功能性确定髋关节中心的方法,与预测性回归技术相比,已显示出优势。但是,当受试者难以在所需范围内执行多平面运动时,功能性方法的当前实施会阻碍其在临床中的应用。在这项研究中,我们系统地研究了在准平面运动期间是否可以使用功能性方法来定位CoR。分析了以下因素的影响:算法,运动的范围和速度,标记簇的位置,标记簇的大小以及到关节中心的距离。在我们的研究中使用机械联动来分离感兴趣的因素,并洞察功能方法的实施变化。我们的结果表明算法和聚类位置显着影响估计结果。对于所有算法,观察到CoR误差和近端簇坐标沿内侧-外侧方向到关节中心的距离之间的显着正相关,而远端标记簇最好尽可能靠近关节中心。通过优化分析和实验因素,变换算法实现了5.3 mm的均方根误差(RMSE),而球面拟合方法则以2.6 mm的RMSE产生了最佳估计。在存在随机噪声和模拟的软组织伪像的情况下,转换算法的性能更好。

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