{"title":"Flexible wide-range multidimensional force sensors inspired by bones embedded in muscle.","authors":"Jie Zhang, Xiaojuan Hou, Shuo Qian, Jiabing Huo, Mengjiao Yuan, Zhigang Duan, Xiaoguang Song, Hui Wu, Shuzheng Shi, Wenping Geng, Jiliang Mu, Jian He, Xiujian Chou","doi":"10.1038/s41378-024-00711-7","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18560,"journal":{"name":"Microsystems & Nanoengineering","volume":"10 ","pages":"64"},"PeriodicalIF":7.3000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11111798/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microsystems & Nanoengineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1038/s41378-024-00711-7","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Microsystems & Nanoengineering is a comprehensive online journal that focuses on the field of Micro and Nano Electro Mechanical Systems (MEMS and NEMS). It provides a platform for researchers to share their original research findings and review articles in this area. The journal covers a wide range of topics, from fundamental research to practical applications. Published by Springer Nature, in collaboration with the Aerospace Information Research Institute, Chinese Academy of Sciences, and with the support of the State Key Laboratory of Transducer Technology, it is an esteemed publication in the field. As an open access journal, it offers free access to its content, allowing readers from around the world to benefit from the latest developments in MEMS and NEMS.