Abstract
Language barrier is the main cause of disagreement.Sign language,which is a common language in all the worldwide language families,is difficult to be entirely popularized due to the high cost of learning as well as the technical barrier in real-time translation.To solve these problems,here,we constructed a wearable organohydrogel-based electronic skin(e-skin)with fast self-healing,strong adhesion,extraor-dinary anti-freezing and moisturizing properties for sign language recognition under complex environ-ments.The e-skin was obtained by using an acrylic network as the main body,aluminum(Ⅲ)and bay-berry tannin as the crosslinking agent,water/ethylene glycol as the solvent system,and a polyvinyl al-cohol network to optimize the network performance.Using this e-skin,a smart glove was further built,which could carry out the large-scale data collection of common gestures and sign languages.With the help of the deep learning method,specific recognition and translation for various gestures and sign lan-guages could be achieved.The accuracy was 93.5％,showing the ultra-high classification accuracy of a sign language interpreter.In short,by integrating multiple characteristics and combining deep learning technology with hydrogel materials,the e-skin achieved an important breakthrough in human-computer interaction and artificial intelligence,and provided a feasible strategy for solving the dilemma of mutual exclusion between flexible electronic devices and human bodies.
NETL
NSTL
万方数据