The Polymer Society of Korea

Abstract

For human–machine interfaces (HMIs), pressure sensor systems require large sensing areas, mechanical conformability, with high spatial resolution. However, conventional pixelated architectures impose excessive wiring and interconnect complexity, limiting scalability and system integration. Here, we present a pixelation-free, monolithic iontronic pressure sensing (PF-MPS) platform that simultaneously resolves pressure magnitude and spatial position. The device comprises a single ionogel layer interfaced with four peripheral electrodes, eliminating discrete pixelation. Under AC bias, pressure-induced ionic redistribution generates spatially varying impedance responses, enabling extraction of both pressure and positional information while maintaining stable signal under static pressure. Machine learning algorithms are employed to decouple the pressure–position signals. Real-time demonstrations validate the potential of this architecture for large-area HMI applications.