Dijkstra Erik J, Gutierrez-Farewik Elena M
KTH Engineering Sciences, Mechanics, Royal Institute of Technology, Stockholm, Sweden; KTH BioMEx Center, Stockholm, Sweden.
KTH Engineering Sciences, Mechanics, Royal Institute of Technology, Stockholm, Sweden; KTH BioMEx Center, Stockholm, Sweden; Department of Women׳s & Children׳s Health, Karolinska Institutet, Stockholm, Sweden.
J Biomech. 2015 Nov 5;48(14):3776-81. doi: 10.1016/j.jbiomech.2015.08.027. Epub 2015 Oct 3.
Motion analysis is a common clinical assessment and research tool that uses a camera system or motion sensors and force plates to collect kinematic and kinetic information of a subject performing an activity of interest. The use of force plates can be challenging and sometimes even impossible. Over the past decade, several computational methods have been developed that aim to preclude the use of force plates. Useful in particular for predictive simulations, where a new motion or change in control strategy inherently means different external contact loads. These methods, however, often depend on prior knowledge of common observed ground reaction force (GRF) patterns, are computationally expensive, or difficult to implement. In this study, we evaluated the use of the Zero Moment Point as a computationally inexpensive tool to obtain the GRFs for normal human gait. The method was applied on ten healthy subjects walking in a motion analysis laboratory and predicted GRFs are evaluated against the simultaneously measured force plate data. Apart from the antero-posterior forces, GRFs are well-predicted and errors fall within the error ranges from other published methods. Joint extension moments were underestimated at the ankle and hip but overestimated at the knee, attributable to the observed discrepancy in the predicted application points of the GRFs. The computationally inexpensive method evaluated in this study can reasonably well predict the GRFs for normal human gait without using prior knowledge of common gait kinetics.
运动分析是一种常见的临床评估和研究工具,它使用摄像系统或运动传感器以及测力板来收集受试者进行感兴趣活动时的运动学和动力学信息。使用测力板可能具有挑战性,有时甚至是不可能的。在过去十年中,已经开发了几种计算方法,旨在避免使用测力板。这对于预测模拟特别有用,在预测模拟中,新的运动或控制策略的变化本质上意味着不同的外部接触载荷。然而,这些方法通常依赖于常见观察到的地面反作用力(GRF)模式的先验知识,计算成本高昂,或者难以实施。在本研究中,我们评估了使用零力矩点作为一种计算成本低廉的工具来获取正常人类步态的GRF。该方法应用于在运动分析实验室中行走的十名健康受试者,并将预测的GRF与同时测量的测力板数据进行比较评估。除了前后力外,GRF得到了很好的预测,误差落在其他已发表方法的误差范围内。踝关节和髋关节处的关节伸展力矩被低估,但膝关节处被高估,这归因于预测的GRF应用点中观察到的差异。本研究中评估的计算成本低廉的方法可以在不使用常见步态动力学先验知识的情况下,相当准确地预测正常人类步态的GRF。