Sawtooth-enhanced bend sensor for gesture recognition  

作　　者：BAI YanRu ZHANG ZiHang WANG HaoYu GUO Rui LI XiSheng 

机构地区：[1]School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing,100083,China [2]School of Advanced Engineering,University of Science and Technology Beijing,Beijing,100083,China [3]School of Precision Instrument and Opto-Electronics Engineering,Tianjin University,Tianjin,300072,China [4]School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing,100083,China

出　　处：《Science China(Technological Sciences)》2024年第6期1727-1736,共10页中国科学（技术科学英文版）

基　　金：supported by the National Key R&D Program of China(Grant No.2022YFC2403703)。

摘　　要：Gesture recognition has diverse application prospects in the field of human-computer interaction.Recently,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have considerable advantages due to their high tensile strength and conductivity.To improve the detection sensitivity of liquid metal strain sensors,a sawtooth-enhanced bending sensor is proposed in this study.Compared with the results from previous studies,the bending sensor shows enhanced resistance variation.In addition,combined with machine learning algorithms,a gesture recognition glove based on the sawtooth-enhanced bending sensor is also fabricated in this study,and various gestures are accurately identified.In the fields of human-computer interaction,wearable sensing,and medical health,the sawtooth-enhanced bending sensor shows great potential and can have wide application prospects.

关 键 词：liquid metal bending sensor gesture recognition machine learning 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP212[自动化与计算机技术—计算机科学与技术] TP18