High‐Sensitivity Self‐Sensing Hydrogels With Reconfigurable Island–Bridge Networks for Human–Machine Interaction and Intelligent Bioinspired Recognition

ABSTRACT Intelligent hydrogel actuators with self‐sensing capabilities have shown broad prospects in flexible electronics, bioinspired robotics, and human–machine interaction. However, most reported self‐sensing hydrogel actuators still suffer from insufficient sensing sensitivity and low efficiency in structural‐response coupling, which restrict their application in highly integrated self‐sensing systems. Here, we develop a high‐sensitivity self‐sensing actuating hydrogel through embedding micro‐nano collaborative island‐bridge conductive network of liquid metal (LM) and carbon nanotube (CNT) within thermal‐responsive poly(N‐isopropylacrylamide) (PNIPAM) matrix, allowing external strain and photothermal actuation to be translated into amplified electrical signals through reversible fracture and reconstruction of conductive pathways. The as‐prepared hydrogel exhibits ultrahigh strain sensitivity (Gauge Factor = 38.9) and precise actuation self‐sensing capability ( ΔR/R 0 > 200%). Benefiting from the excellent sensing performance, the proposed LM/CNT‐PNIPAM (LCP) self‐sensing hydrogel not only enables high‐fidelity monitoring of human motion and physiological signals in wearable electronics, but also exhibits potential as gesture‐controlled remote navigation of intelligent vehicle by integrating with machine‐learning algorithm. Moreover, through combining with IoT communication technique, a bioinspired self‐sensing tentacle with high‐accuracy recognition capacity was developed based on the excellent self‐sensing feature of the LCP hydrogel. This study lays a material foundation for developing intelligent soft systems with accurate feedback regulation and further human–machine interaction capacity.