Hnat Sandra K, van Basten Ben J H, van den Bogert Antonie J
Cleveland State University, Department of Mechanical Engineering, Cleveland, OH 44115, USA.
Motekforce Link, Hogehilweg 18-C, 1101 CD Amsterdam, The Netherlands.
J Biomech. 2018 Jun 25;75:96-101. doi: 10.1016/j.jbiomech.2018.05.009. Epub 2018 May 19.
Force plates for human movement analysis provide accurate measurements when mounted rigidly on an inertial reference frame. Large measurement errors occur, however, when the force plate is accelerated, or tilted relative to gravity. This prohibits the use of force plates in human perturbation studies with controlled surface movements, or in conditions where the foundation is moving or not sufficiently rigid. Here we present a linear model to predict the inertial and gravitational artifacts using accelerometer signals. The model is first calibrated with data collected from random movements of the unloaded system and then used to compensate for the errors in another trial. The method was tested experimentally on an instrumented force treadmill capable of dynamic mediolateral translation and sagittal pitch. The compensation was evaluated in five experimental conditions, including platform motions induced by actuators, by motor vibration, and by human ground reaction forces. In the test that included all sources of platform motion, the root-mean-square (RMS) errors were 39.0 N and 15.3 N m in force and moment, before compensation, and 1.6 N and 1.1 N m, after compensation. A sensitivity analysis was performed to determine the effect on estimating joint moments during human gait. Joint moment errors in hip, knee, and ankle were initially 53.80 N m, 32.69 N m, and 19.10 N m, and reduced to 1.67 N m, 1.37 N m, and 1.13 N m with our method. It was concluded that the compensation method can reduce the inertial and gravitational artifacts to an acceptable level for human gait analysis.
用于人体运动分析的测力板在牢固安装于惯性参考系时可提供准确测量值。然而,当测力板加速或相对于重力倾斜时,会出现较大的测量误差。这使得测力板无法用于具有可控表面运动的人体扰动研究,或在基础移动或刚性不足的情况下使用。在此,我们提出一种线性模型,利用加速度计信号预测惯性和重力伪影。该模型首先用从卸载系统的随机运动中收集的数据进行校准,然后用于补偿另一试验中的误差。该方法在一台能够进行动态内外侧平移和矢状面俯仰的测力跑步机上进行了实验测试。在包括由致动器、电机振动和人体地面反作用力引起的平台运动的五个实验条件下评估了补偿效果。在包含平台运动所有来源的测试中,补偿前力和力矩的均方根(RMS)误差分别为39.0 N和15.3 N·m,补偿后分别为1.6 N和1.1 N·m。进行了敏感性分析,以确定对人体步态期间关节力矩估计的影响。髋、膝和踝关节的关节力矩误差最初分别为53.80 N·m、32.69 N·m和19.10 N·m,采用我们的方法后分别降至1.67 N·m、1.37 N·m和1.13 N·m。得出的结论是,该补偿方法可将惯性和重力伪影降低到人体步态分析可接受的水平。