3D‐Printed Ion‐Conductive Hydrogels with Tunable Mechanical–Electrical Properties for Multimodal Sign Language Recognition

ABSTRACT Sign language recognition technology holds significant importance for eliminating communication barriers faced by the hearing‐impaired population. To address the limitations of current wearable sensors‒such as complex fabrication or materials incompatibility within an integrated system, this study designed a 3D printed ion‐conductive hydrogel with tunable electromechanical performances for versatile wearable sensing. The hydrogel is primarily based on a polyampholyte network interpenetrated with a polyacrylamide (PAAM) framework and synergistically integrated with LiCl and a covalent organic framework (COF) to enhance its electromechanical performance. It exhibits low hysteresis (90.25% recovery ratio) with high elongation (550%) and large compressive strain tolerance (90%) for strain/pressure sensing, while its low modulus (0.09 MPa) and high conductivity (0.23 S m ^{− 1} ) enabled high‐fidelity surface electromyography (sEMG) sensing. Leveraging these multifunctional hydrogels, we developed a multimodal sign language recognition system consisting of a pair of digital gloves, each embedded with 12 strain sensors and 5 pressure sensors, together with a flexible armband integrated with a 10‐channel differential sEMG electrode array. Coupled with a bidirectional long short‐term memory (Bi‐LSTM) multimodal fusion model, the system achieved a classification accuracy of 99.65% across 24 Chinese sign language gestures.