Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratory of Movement Analysis and Measurement, Lausanne, Switzerland.
Gait Posture. 2010 Jul;32(3):311-6. doi: 10.1016/j.gaitpost.2010.05.014. Epub 2010 Jun 23.
This study aimed to use the plantar pressure insole for estimating the three-dimensional ground reaction force (GRF) as well as the frictional torque (T(F)) during walking. Eleven subjects, six healthy and five patients with ankle disease participated in the study while wearing pressure insoles during several walking trials on a force-plate. The plantar pressure distribution was analyzed and 10 principal components of 24 regional pressure values with the stance time percentage (STP) were considered for GRF and T(F) estimation. Both linear and non-linear approximators were used for estimating the GRF and T(F) based on two learning strategies using intra-subject and inter-subjects data. The RMS error and the correlation coefficient between the approximators and the actual patterns obtained from force-plate were calculated. Our results showed better performance for non-linear approximation especially when the STP was considered as input. The least errors were observed for vertical force (4%) and anterior-posterior force (7.3%), while the medial-lateral force (11.3%) and frictional torque (14.7%) had higher errors. The result obtained for the patients showed higher error; nevertheless, when the data of the same patient were used for learning, the results were improved and in general slight differences with healthy subjects were observed. In conclusion, this study showed that ambulatory pressure insole with data normalization, an optimal choice of inputs and a well-trained nonlinear mapping function can estimate efficiently the three-dimensional ground reaction force and frictional torque in consecutive gait cycle without requiring a force-plate.
本研究旨在使用足底压力鞋垫来估计三维地面反作用力(GRF)和行走时的摩擦扭矩(T(F))。11 名受试者,6 名健康受试者和 5 名踝关节疾病患者,在测力板上进行多次行走试验时穿着压力鞋垫参与了研究。分析了足底压力分布,并考虑了 10 个主要成分和 24 个区域压力值的支撑时间百分比(STP),用于 GRF 和 T(F)估计。基于内个体和个体间数据的两种学习策略,使用线性和非线性逼近器来估计 GRF 和 T(F)。计算了逼近器与力板实际模式之间的均方根误差和相关系数。我们的结果表明,特别是当 STP 被视为输入时,非线性逼近具有更好的性能。垂直力(4%)和前后力(7.3%)的误差最小,而横向力(11.3%)和摩擦扭矩(14.7%)的误差较大。对于患者获得的结果显示出更高的误差;然而,当使用同一患者的数据进行学习时,结果得到了改善,并且通常与健康受试者观察到轻微差异。总之,本研究表明,具有数据归一化、最佳输入选择和训练良好的非线性映射功能的可穿戴压力鞋垫可以在无需测力板的情况下,高效地估计连续步态周期中的三维地面反作用力和摩擦扭矩。