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受嵌入肌肉的骨骼启发的柔性宽量程多维力传感器。

Flexible wide-range multidimensional force sensors inspired by bones embedded in muscle.

作者信息

Zhang Jie, Hou Xiaojuan, Qian Shuo, Huo Jiabing, Yuan Mengjiao, Duan Zhigang, Song Xiaoguang, Wu Hui, Shi Shuzheng, Geng Wenping, Mu Jiliang, He Jian, Chou Xiujian

机构信息

Science and Technology on Electronic Test and Measurement Laboratory, North University of China, Taiyuan, 030051 China.

School of Software, North University of China, Taiyuan, 030051 China.

出版信息

Microsyst Nanoeng. 2024 May 22;10:64. doi: 10.1038/s41378-024-00711-7. eCollection 2024.

Abstract

Flexible sensors have been widely studied for use in motion monitoring, human‒machine interactions (HMIs), personalized medicine, and soft intelligent robots. However, their practical application is limited by their low output performance, narrow measuring range, and unidirectional force detection. Here, to achieve flexibility and high performance simultaneously, we developed a flexible wide-range multidimensional force sensor (FWMFS) similar to bones embedded in muscle structures. The adjustable magnetic field endows the FWMFS with multidimensional perception for detecting forces in different directions. The multilayer stacked coils significantly improved the output from the μV to the mV level while ensuring FWMFS miniaturization. The optimized FWMFS exhibited a high voltage sensitivity of 0.227 mV/N (0.5-8.4 N) and 0.047 mV/N (8.4-60 N) in response to normal forces ranging from 0.5 N to 60 N and could detect lateral forces ranging from 0.2-1.1 N and voltage sensitivities of 1.039 mV/N (0.2-0.5 N) and 0.194 mV/N (0.5-1.1 N). In terms of normal force measurements, the FWMFS can monitor finger pressure and sliding trajectories in response to finger taps, as well as measure plantar pressure for assessing human movement. The plantar pressure signals of five human movements collected by the FWMFS were analyzed using the k-nearest neighbors classification algorithm, which achieved a recognition accuracy of 92%. Additionally, an artificial intelligence biometric authentication system is being developed that classifies and recognizes user passwords. Based on the lateral force measurement ability of the FWMFS, the direction of ball movement can be distinguished, and communication systems such as Morse Code can be expanded. This research has significant potential in intelligent sensing and personalized spatial recognition.

摘要

柔性传感器在运动监测、人机交互(HMI)、个性化医疗和软智能机器人等领域已得到广泛研究。然而,其实际应用受到低输出性能、窄测量范围和单向力检测的限制。在此,为了同时实现灵活性和高性能,我们开发了一种类似于嵌入肌肉结构中的骨骼的柔性宽范围多维力传感器(FWMFS)。可调磁场赋予FWMFS多维感知能力,以检测不同方向的力。多层堆叠线圈在确保FWMFS小型化的同时,将输出从μV显著提高到mV水平。优化后的FWMFS在0.5 N至60 N的法向力范围内表现出0.227 mV/N(0.5 - 8.4 N)和0.047 mV/N(8.4 - 60 N)的高电压灵敏度,并且能够检测0.2 - 1.1 N的侧向力,电压灵敏度分别为1.039 mV/N(0.2 - 0.5 N)和0.194 mV/N(0.5 - 1.1 N)。在法向力测量方面,FWMFS可以监测手指轻敲时的手指压力和滑动轨迹,还可以测量足底压力以评估人体运动。利用k近邻分类算法对FWMFS采集的五种人体运动的足底压力信号进行分析,识别准确率达到92%。此外,正在开发一种人工智能生物特征认证系统,用于对用户密码进行分类和识别。基于FWMFS的侧向力测量能力,可以区分球的运动方向,并扩展诸如摩尔斯电码之类的通信系统。这项研究在智能传感和个性化空间识别方面具有巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56cb/11111798/c67edce88fcf/41378_2024_711_Fig1_HTML.jpg

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