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DC Field | Value | Language |
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dc.citation.number | 1 | - |
dc.citation.startPage | 139 | - |
dc.citation.title | NANO-MICRO LETTERS | - |
dc.citation.volume | 14 | - |
dc.contributor.author | Wu, Ronghui | - |
dc.contributor.author | Seo, Sangjin | - |
dc.contributor.author | Ma, Liyun | - |
dc.contributor.author | Bae, Juyeol | - |
dc.contributor.author | Kim, Taesung | - |
dc.date.accessioned | 2023-12-21T13:16:53Z | - |
dc.date.available | 2023-12-21T13:16:53Z | - |
dc.date.created | 2022-07-19 | - |
dc.date.issued | 2022-12 | - |
dc.description.abstract | Yarn sensors have shown promising application prospects in wearable electronics owing to their shape adaptability, good flexibility, and weavability. However, it is still a critical challenge to develop simultaneously structure stable, fast response, body conformal, mechanical robust yarn sensor using full microfibers in an industrial-scalable manner. Herein, a full-fiber auxetic-interlaced yarn sensor (AIYS) with negative Poisson's ratio is designed and fabricated using a continuous, mass-producible, structure-programmable, and low-cost spinning technology. Based on the unique microfiber interlaced architecture, AIYS simultaneously achieves a Poisson's ratio of-1.5, a robust mechanical property (0.6 cN/dtex), and a fast train-resistance responsiveness (0.025 s), which enhances conformality with the human body and quickly transduce human joint bending and/or stretching into electrical signals. Moreover, AIYS shows good flexibility, washability, weavability, and high repeatability. Furtherly, with the AIYS array, an ultrafast full-letter sign-language translation glove is developed using artificial neural network. The sign-language translation glove achieves an accuracy of 99.8% for all letters of the English alphabet within a short time of 0.25 s. Furthermore, owing to excellent full letter-recognition ability, real-time translation of daily dialogues and complex sentences is also demonstrated. The smart glove exhibits a remarkable potential in eliminating the communication barriers between signers and non-signers. | - |
dc.identifier.bibliographicCitation | NANO-MICRO LETTERS, v.14, no.1, pp.139 | - |
dc.identifier.doi | 10.1007/s40820-022-00887-5 | - |
dc.identifier.issn | 2311-6706 | - |
dc.identifier.scopusid | 2-s2.0-85133243459 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/59026 | - |
dc.identifier.wosid | 000819802100001 | - |
dc.language | 영어 | - |
dc.publisher | SHANGHAI JIAO TONG UNIV PRESS | - |
dc.title | Full-Fiber Auxetic-Interlaced Yarn Sensor for Sign-Language Translation Glove Assisted by Artificial Neural Network | - |
dc.type | Article | - |
dc.description.isOpenAccess | TRUE | - |
dc.relation.journalWebOfScienceCategory | Nanoscience & Nanotechnology; Materials Science, Multidisciplinary; Physics, Applied | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics; Materials Science; Physics | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Negative Poisson&apos | - |
dc.subject.keywordAuthor | s ratio yarns | - |
dc.subject.keywordAuthor | Interlaced yarn sensors | - |
dc.subject.keywordAuthor | Smart glove | - |
dc.subject.keywordAuthor | Deep learning | - |
dc.subject.keywordAuthor | Sign-language translation | - |
dc.subject.keywordPlus | STRAIN SENSOR | - |
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