Department of Environmental Health, Harvard School of Public Health, Boston, MA 02139, USA.
J Biomech. 2012 Apr 30;45(7):1332-8. doi: 10.1016/j.jbiomech.2012.01.024. Epub 2012 Mar 23.
This study describes a novel calibration method for six-degrees-of-freedom force/torque sensors (FTsensors) using a pre-calibrated force plate (FP) as a reference measuring device. In this calibration method, the FTsensor is rigidly connected to a FP and force/torque data are synchronously recorded while a dynamic functional loading procedure is applied by the researcher. Based on these data an accurate calibration matrix for the FTsensor can easily be obtained via least-squares optimization. Using this calibration method, this study further investigated what loading methods are appropriate for the calibration of FTsensors intended for ambulatory measurement of ground reaction forces (GRFs). Seven different loading methods were compared (e.g., walking, pushing while standing on the FTsensor). Calibration matrices were calculated based on the raw data from the seven loading methods individually and all loading methods combined. Performance of these calibration matrices was subsequently compared in an in situ trial. During the in situ trial, five common work tasks (e.g., walking, manual lifting, pushing) were performed by an experimenter, while standing on the FP wearing a "ForceShoe" with two calibrated FTsensors attached to its sole. Root-mean-square differences (RMSDs) between the FTsensor and FP outcomes were calculated over all tasks. Using the calibration matrices based on all loading methods combined resulted in small RMSDs (GRF: <8 N, center of pressure: <2 mm). Using the calibration matrices based on "pushing against manual resistance" resulted in similar RMSDs, proving it to be the best single loading method.
本研究描述了一种使用经过预校准的力板（FP）作为参考测量设备的六自由度力/扭矩传感器（FT 传感器）的新型校准方法。在这种校准方法中，FT 传感器被刚性地连接到 FP，并且在研究人员施加动态功能加载程序的同时同步记录力/扭矩数据。基于这些数据，可以通过最小二乘优化轻松获得 FT 传感器的精确校准矩阵。使用这种校准方法，本研究进一步研究了哪些加载方法适用于用于测量地面反作用力（GRF）的可穿戴 FT 传感器的校准。比较了七种不同的加载方法（例如，行走，在 FT 传感器上站立时推动）。根据来自七种加载方法的原始数据单独计算校准矩阵，并将所有加载方法组合在一起。随后在原位试验中比较这些校准矩阵的性能。在原位试验中，实验者穿着带有两个校准 FT 传感器的“ForceShoe”站在 FP 上，执行五个常见的工作任务（例如，行走，手动提升，推动）。计算了所有任务中 FT 传感器和 FP 结果之间的均方根差（RMSD）。使用基于所有加载方法组合的校准矩阵导致 RMSD 较小（GRF：<8 N，压力中心：<2 mm）。使用基于“抵抗手动阻力的推动”的校准矩阵产生了相似的 RMSD，证明它是最好的单个加载方法。
