A Novel Flexible Multidimensional Force Platform for Assessing Regional Plantar Pressure and Shear Stress Under the Foot During Gait

The multidimensional force platform with a flexible interface for simultaneous assessment of plantar pressure and shear stresses has become highly anticipated for early diagnostics of diabetic foot ulcer (DFU). Robust detection of such multidimensional forces remains challenging; meanwhile, an intrinsically flexible sensor interface is deemed required to improve detection accuracy by adapting to plantar foot structure and its surface characteristics. This study proposes a novel silicone rubber-based vision sensor design for multidimensional force assessment under the foot. We employ the finite element method (FEM) to determine the optimal range of the platform for plantar force detection relevant to gait, offering a comprehensive yet efficient design scheme. After fabrication, a force decoupling model was established by training the convolutional neural network of U-Net with 15400 datasets with multidimensional force-optical flow data as collected by the customized calibration system. Following calibration, the platform can achieve simultaneous measurement of multidimensional plantar stresses in real time with an accuracy of 0.09 N for pressure with a range up to 25 N/cm2 and 0.06 N for shear stress with a range up to 10 N/cm2. The platform proposed in this work is the first neural network-informed force platform with a flexible interactive interface, multidimensional force detection capability, and low manufacturing cost. In the future, it is expected to become an efficient tool for further research into the biomechanical etiology of the DFU in both research and clinical settings.