Collins Steven H, Adamczyk Peter G, Ferris Daniel P, Kuo Arthur D
Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA.
Gait Posture. 2009 Jan;29(1):59-64. doi: 10.1016/j.gaitpost.2008.06.010. Epub 2008 Aug 27.
We propose a new method for calibrating force plates to reduce errors in center of pressure locations, forces, and moments. These errors may be caused by imperfect mounting of force plates to the ground or by installation of a treadmill atop a force plate, which may introduce distorting loads. The method, termed the Post-Installation Least-Squares (PILS) calibration, combines features of several previous methods into a simple procedure. It requires a motion capture system and an instrumented pole for applying reference loads. Reference loads may be manually applied to the force plate in arbitrary locations and directions. The instrumented pole measures applied load magnitudes through a single-axis load cell, and load directions through motion capture markers. Reference data and imperfect force plate signals are then combined to form a linear calibration matrix that simultaneously minimizes mean square errors in all forces and moments. We applied the procedure to standard laboratory force plates, as well as a custom-built, split-belt force treadmill. We also collected an independent set of verification data for testing. The proposed calibration procedure was found to reduce force errors by over 20%, and moment errors by over 60%. Center of pressure errors were also reduced by 63% for standard force plates and 91% for the force treadmill. The instrumented pole is advantageous because it allows for fast and arbitrary load application without needing a precise fixture for aligning loads. The linear calibration matrix is simpler than nonlinear correction equations and more compatible with standard data acquisition software, yet it yields error reductions comparable to more complex methods.
我们提出了一种用于校准测力板的新方法,以减少压力中心位置、力和力矩的误差。这些误差可能是由于测力板安装在地面上不完善,或者在测力板上安装跑步机而引入的扭曲载荷所致。该方法称为安装后最小二乘法(PILS)校准,它将几种先前方法的特点结合到一个简单的过程中。它需要一个运动捕捉系统和一根用于施加参考载荷的仪器化杆。参考载荷可以手动施加到测力板的任意位置和方向。仪器化杆通过单轴测力传感器测量施加的载荷大小,并通过运动捕捉标记测量载荷方向。然后将参考数据和不完善的测力板信号组合起来,形成一个线性校准矩阵,该矩阵同时最小化所有力和力矩的均方误差。我们将该过程应用于标准实验室测力板以及定制的分体带测力跑步机。我们还收集了一组独立的验证数据用于测试。结果发现,所提出的校准过程可将力误差降低20%以上,力矩误差降低60%以上。标准测力板的压力中心误差也降低了63%,测力跑步机的压力中心误差降低了91%。仪器化杆的优势在于它允许快速且任意地施加载荷,而无需精确的夹具来对准载荷。线性校准矩阵比非线性校正方程更简单,并且与标准数据采集软件更兼容,但它产生的误差降低效果与更复杂的方法相当。