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A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network

School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350116, China
Author to whom correspondence should be addressed.
Sensors 2019, 19(1), 27;
Received: 6 November 2018 / Revised: 15 December 2018 / Accepted: 17 December 2018 / Published: 21 December 2018
(This article belongs to the Special Issue Smart Textiles and Wearable Sensors)
PDF [7002 KB, uploaded 21 December 2018]


Electronic skin is an important means through which robots can obtain external information. A novel flexible tactile sensor capable of simultaneously detecting the contact position and force was proposed in this paper. The tactile sensor had a three-layer structure. The upper layer was a specially designed conductive film based on indium-tin oxide polyethylene terephthalate (ITO-PET), which could be used for detecting contact position. The intermediate layer was a piezoresistive film used as the force-sensitive element. The lower layer was made of fully conductive material such as aluminum foil and was used only for signal output. In order to solve the inconsistencies and nonlinearity of the piezoresistive properties for large areas, a Radial Basis Function (RBF) neural network was used. This includes input, hidden, and output layers. The input layer has three nodes representing position coordinates, X, Y, and resistor, R. The output layer has one node representing force, F. A sensor sample was fabricated and experiments of contact position and force detection were performed on the sample. The results showed that the principal function of the tactile sensor was feasible. The sensor sample exhibited good consistency and linearity. The tactile sensor has only five lead wires and can provide the information support necessary for safe human—computer interactions. View Full-Text
Keywords: electronic skin; contact position detection; contact force detection; RBF neural network electronic skin; contact position detection; contact force detection; RBF neural network

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Zhang, Y.; Ye, J.; Lin, Z.; Huang, S.; Wang, H.; Wu, H. A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network. Sensors 2019, 19, 27.

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