Surfactant‐Enhanced Anti‐Swelling Hydrogel Flexible Sensor for Machine Learning‐Assisted Underwater Gesture Recognition
Xin Jiao, Dengke Song, Junjie Ding, Jiayu Li, Kexin Ding, Fanlun Meng, Hui Zheng, Wenlong Xu
Abstract
Hydrogels hold great promise as flexible sensors. However, the development of hydrogel sensors with exceptional anti-swelling properties and stable performance remains a significant challenge. This study introduced a novel design strategy based on surfactant-assisted hydrophobic associative hydrogels. Through free-radical copolymerization in the presence of the surfactant cetyltrimethylammonium bromide, hydrogels with outstanding mechanical properties, excellent anti-swelling capabilities, and superior sensing performance are successfully fabricated. The resulting hydrogel demonstrated remarkable anti-swelling behavior (swelling ratio: -2.3%), exceptional mechanical strength (breaking strain: 3594.5%), and sustained fatigue resistance during repeated underwater loading-unloading cycles (1000 cycles). Integrating the hydrogel sensor with machine learning, precise and stable underwater gesture recognition and motion monitoring are achieved with an accuracy of 98.3%. This study provides a new perspective for advancing flexible underwater sensor technologies and underscores their broad potential in smart wearable devices, health monitoring, and underwater exploration.