School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Xiaolingwei Street 200#, Nanjing 210094, China.
Sensors (Basel). 2020 Dec 18;20(24):7286. doi: 10.3390/s20247286.
Bionic electronic skin can accurately sense and locate surface pressure, which is widely demanded in many fields. Traditional electronic skin design usually relies on grid-architecture sensor arrays, requiring complex grid and interconnection arrangements as well as high cost. Grid-less planar sensors can solve the problem by using electrodes only at the edges, but they usually require the use of mapping software such as electrical impedance tomography to achieve high precision. In this work, a design method of high-precision grid-less planar pressure sensors based on the back-propagation (BP) neural network is proposed. The measurement precision of this method is demonstrated to be over two orders of magnitude higher than that of a grid-structure sensor array with the same electrode distribution density. Moreover, this method can be used for irregularly-shaped and non-uniform sensors, which further reduces the manufacturing difficulty and increases the application flexibility.
仿生电子皮肤可以准确感知和定位表面压力，这在许多领域都有广泛的需求。传统的电子皮肤设计通常依赖于网格架构传感器阵列，需要复杂的网格和互连布置，成本也很高。无网格平面传感器可以通过仅在边缘使用电极来解决这个问题，但它们通常需要使用像电阻抗断层成像术这样的映射软件来实现高精度。在这项工作中，提出了一种基于反向传播（BP）神经网络的高精度无网格平面压力传感器设计方法。该方法的测量精度被证明比具有相同电极分布密度的网格结构传感器阵列高出两个数量级以上。此外，这种方法还可以用于不规则形状和不均匀的传感器，进一步降低了制造难度，增加了应用灵活性。
