材料科学
解耦(概率)
人体运动
像素
拉伤
振动器
弯曲
应变计
结构健康监测
灵敏度(控制系统)
运动(物理)
声学
人工智能
电子工程
计算机科学
控制工程
工程类
复合材料
振动
医学
物理
内科学
作者
Xiuzhu Lin,Hua Xue,Fan Li,Yan Wang,Juan Li,Hongran Zhao,Tong Zhang
出处
期刊:Nano Energy
[Elsevier]
日期:2024-02-01
卷期号:123: 109350-109350
被引量:3
标识
DOI:10.1016/j.nanoen.2024.109350
摘要
Flexible strain sensors have excellent prospects in the fields of medical health monitoring and intelligent human-machine interaction. Considerable research effort is dedicated to continuously optimizing their sensitivity performance to meet application requirements. However, the ability to distinguish and decouple different forms of strain is crucial in determining the accuracy and effectiveness of information extraction from complex strain patterns, which is also one of the challenges presently restricting the practical application of strain sensors. Here, a simple strategy for constructing a paper-based bending strain sensor is introduced, achieved by a commercially available inkjet printer and original ink cartridges to print on coated paper. The strain sensor exhibits high resolution in measuring strain degrees and decoupling strain in different directions. More importantly, a scheme for measuring the horizontal angle of the strain axis is proposed for the first time, which is achieved through a strain sensor array consisting of three sensing units distributed at different horizontal angles. This further promotes the accurate recognition of strain information in multidimensional strain patterns. Combining machine learning algorithms, the strain sensor array demonstrates exceptional accuracy in distinguishing various human upper limb activities. This work provides the necessary research value to advance flexible strain sensors towards practical applications.
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