Touch Localization with a Resistive Position Sensor-Gated Oxide Neuromorphic Transistor

Abstract The ability to localize external mechanical stimuli is fundamental to human tactile perception, making its hardware implementation of significant interest for advanced human–machine interaction. Here, a resistive position sensor (RPS) is proposed for touch location recognition, exhibiting a high sensitivity of ∼55 kΩ/cm and excellent stability. A tactile perceptual system (TPS) is proposed by integrating the RPS with a chitosan-gated oxide ionotronic neuromorphic transistor. Benefiting from the strong proton relaxation effects of the chitosan-based electrolyte, the neuromorphic transistor can effectively process electrical signals generated from the RPS. The TPS can emulate various synaptic behaviors under mechanical stimuli. As a proof of concept, it demonstrates Braille code recognition. Furthermore, the TPS enables touch intention recognition through machine learning, demonstrating a high recognition accuracy of ∼99.2%. The results demonstrate great promise in human−machine interaction.