Affiliation:
1. Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electric Engineering Soochow University Suzhou 215123 China
2. School of Future Science and Engineering Soochow University Suzhou 215299 China
Abstract
Wearable smart glove of gesture language provides a novel strategy for the hearing‐impaired people to commutate with the world. Current commercialized solutions of gesture language are limited by the full extent of human interaction beyond operation dexterity, sensory feedback, and the huge cost of fabrication. Herein, a low‐cost, high‐efficient gesture‐language‐recognition feedback system combined with the strain‐sensor arrays and machine‐learning technology is proposed. The strain‐sensor arrays integrated with 3D‐printed glove can extract both spatial and temporal information about the finger's movement. The smart glove achieves gesture‐language recognition using machine learning with an accuracy of over 99%. Integrating with multidimensional manipulation, visual feedback and artificial intelligence (AI)‐based gesture‐language recognition, the smart system can accurately recognize complex gestures and provide real‐time feedback to users. The smart glove system can not only provide an efficient way for hearing‐impaired persons to communicate with the outside world, but also benefit industries in multiple fields such as entertainment, home healthcare, sports training, and the medical industry.
Funder
National Natural Science Foundation of China
Cited by
3 articles.
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