Wirelessly Detecting of Spatiotemporal Mechanical Stimuli by a Bio-Inspired Neural Sensor Via Temperature Signals

Traditional artificial sensory systems, inspired by biological sensory nervous systems, require the integration of distributed units and wired connections to realize the perception of external mechanical stimuli, which brings disadvantages such as complex connections, complicated structures, and interference between signals. Herein, we propose a bio-inspired artificial neural sensor with a highlighted ability of wirelessly detecting spatiotemporal mechanical stimuli, which is fabricated by carbon nanotube and polymer composites. Because the resistance of the sensor varies in respond to external mechanical stimuli, the consequential temperature changes caused by Joule heating effect can be wirelessly detected, realizing the recognition of different mechanical stimuli and multi-positional sensing. The great durability (>1400 cycles) allow the sensor to withstand long-lasting mechanical stimuli. In addition, the artificial neural sensor enables programmable design in device shapes and functions, and it needs no energy consumption without stimulus. We demonstrate a series of touch-interaction applications based on the neural sensor, such as human–computer interaction, encrypted information transmission, and remote control. We hope that this artificial neural sensor will facilitate the development of complex bionic sensing systems, virtual reality, and metaverse.