Multifunctional biomimetic neural tactile sensing system for human-machine interaction

The human tactile sensing system involves perceiving stimuli by combining pressure and touch signals through different cutaneous receptors. A biomimetic tactile sensor system facilitates the development of human-machine interaction, which is vital for bioinspired robotic systems, virtual reality, and artificial receptors. However, building sensing systems with capabilities similar to those of humans presents a significant challenge. Here, we report a multifunctional biomimetic neural tactile sensing system that emulates the human tactile sensing process using a biomimetic all-in-one interactive tactile sensor and a signal-converting system. The sensors exhibit high regional differentiation in touch response, similar to the spatiotemporal characteristics of biological neural networks in human skin, and generate output signals akin to those of sensory neurons. In human-machine interaction applications, we have verified that output signals can be transmitted through a signal transmission system without distortion, thereby effectively driving human-machine interaction. Furthermore, experiments with various structural designs have shown that signals can support efficient human-machine interaction across different sensor configurations. By integrating biomimetic sensing systems with spatiotemporal resolution capabilities, we aim to advance complex neural repair research and further develop the field of intelligent interactive perception using biomimetic interactive sensors.