Highly durable machine-learned waterproof electronic glove based on low-cost thermal transfer printing for amphibious wearable applications  

作　　者：Shengshun Duan Jiayi Wang Yong Lin Jianlong Hong Yucheng Lin Yier Xia Yinghui Li Di Zhu Wei Lei Wenming Su Baoping Wang Zheng Cui Wei Yuan Jun Wu 

机构地区：[1]Joint International Research Laboratory of Information Display and Visualization,School of Electronic Science and Engineering,Southeast University,Nanjing 210096,China [2]Printable Electronics Research Centre,Suzhou Institute of Nano-Tech and Nano-Bionics,Chinese Academy of Sciences,Suzhou 215123,China

出　　处：《Nano Research》2023年第4期5480-5489,共10页纳米研究（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.62075040 and 51603227);the National Key R&D Program of China(No.2017YFE0112000);Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_0230).

摘　　要：Gesture recording,modeling,and understanding based on a robust electronic glove(E-glove)are of great significance for efficient human-machine cooperation in harsh environments.However,such robust edge-intelligence interfaces remain challenging as existing E-gloves are limited in terms of integration,waterproofness,scalability,and interface stability between different components.Here,we report on the design,manufacturing,and application scenarios for a waterproof E-glove,which is of low cost,lightweight,and scalable for mass production,as well as environmental robustness,waterproofness,and washability.An improved neural network architecture is proposed to implement environment-adaptive learning and inference for hand gestures,which achieves an amphibious recognition accuracy of 100%in 26 categories by analyzing 2,600 hand gesture patterns.We demonstrate that the E-glove can be used for amphibious remote vehicle navigation via hand gestures,potentially opening the way for efficient human-human and human-machine cooperation in harsh environments.

关 键 词：data glove transfer printing human-machine interfaces strain sensor amphibious control 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]