Long‐Term Stability, Rapid Response, and Low‐Hysteretic Conductive Composite Hydrogels for Real‐Time Sign Language Translation

ABSTRACT Sign language recognition is a vital communication aid for the hearing‐impaired. Existing wearable sign language recognition systems suffer from poor real‐time performance and recognition accuracy due to limitations in multimodal sensing capabilities and sensor performance. As the core sensing material, traditional hydrogels are prone to mechanical hysteresis and residual strain under cyclic loading, leading to signal drift and distortion. Additionally, they are susceptible to dehydration and failure, which severely compromise the system's long‐term stable operation. To address these bottlenecks, we developed a composite hydrogel with outstanding water retention (73.4% water content after 60 days at 25°C), low hysteresis, ultra‐fast response (64 ms), and recovery (66 ms). It enables highly sensitive, durable bidirectional tensile/pressure sensing for real‐time multimodal mechanical monitoring. Integrated with an IMU, this hydrogel was applied to a lightweight wearable glove to reliably acquire multichannel signals and accelerations. When combined with a dual‐branch LSTM model, the glove achieved 98.90% accuracy in sign language classification, demonstrating strong potential for home rehabilitation and daily communication assistance. This integrated multimodal sensing platform enables diverse wireless intelligent interactions across complex applications such as sign language recognition, robotic control, and assisted rehabilitation, delivering outstanding accuracy, real‐time responsiveness, portability, and scalability.