Ultrasensitive and Breathable Hydrogel Fiber‐Based Strain Sensors Enabled by Customized Crack Design for Wireless Sign Language Recognition

Abstract

Abstract Wearable strain sensors, capable of continuously detecting human movements, hold great application prospects in sign language gesture recognition to alleviate the daily communication barriers of the deaf and mute community. However, the unsatisfactory strain sensing performance (such as low sensitivity, narrow detection range, etc.) and wearing discomfort severely hinder their practical application. Here, high‐performance breathable hydrogel strain sensors are proposed by introducing an adjustable localized crack in a closed‐loop connected hydrogel fiber encapsulated by porous elastomer films. Upon loading/unloading of external strain, the dynamic opening/closing of the pre‐cut crack causes a rapid switching in the hydrogel conductive path, resulting in sharp changes in resistance and a high sensitivity. Consequently, the hydrogel‐based crack‐effect strain sensor exhibits a superb sensitivity (GF up to 3930), a broad detection range (from 0.02% to 80%), fast response/recovery time (78/52 ms), repeatability, and structural stability. Based on the capability to accurately detect various strains across the full range of human movements, a wireless sign language recognition system is developed to achieve a high recognition accuracy of 98.1% by encoding and decoding various sign language gestures with the assistance of machine learning, providing a robust platform for efficient sign language intelligibility and barrier‐free communication.