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dc.contributor.author Kim, Kyungsoo -
dc.contributor.author Sim, Minkyung -
dc.contributor.author Lim, Sung‐Ho -
dc.contributor.author Kim, Dongsu -
dc.contributor.author Lee, Doyoung -
dc.contributor.author Shin, Kwonsik -
dc.contributor.author Moon, Cheil -
dc.contributor.author Choi, Ji-Woong -
dc.contributor.author Jang, Jae Eun -
dc.date.accessioned 2021-03-10T02:41:02Z -
dc.date.available 2021-03-10T02:41:02Z -
dc.date.created 2021-03-02 -
dc.date.issued 2021-04 -
dc.identifier.issn 2198-3844 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12981 -
dc.description.abstract As a surrogate for human tactile cognition, an artificial tactile perception and cognition system are proposed to produce smooth/soft and rough tactile sensations by its user's tactile feeling; and named this system as “tactile avatar”. A piezoelectric tactile sensor is developed to record dynamically various physical information such as pressure, temperature, hardness, sliding velocity, and surface topography. For artificial tactile cognition, the tactile feeling of humans to various tactile materials ranging from smooth/soft to rough are assessed and found variation among participants. Because tactile responses vary among humans, a deep learning structure is designed to allow personalization through training based on individualized histograms of human tactile cognition and recording physical tactile information. The decision error in each avatar system is less than 2% when 42 materials are used to measure the tactile data with 100 trials for each material under 1.2N of contact force with 4cm s−1 of sliding velocity. As a tactile avatar, the machine categorizes newly experienced materials based on the tactile knowledge obtained from training data. The tactile sensation showed a high correlation with the specific user's tendency. This approach can be applied to electronic devices with tactile emotional exchange capabilities, as well as advanced digital experiences. © 2021 The Authors. Advanced Science published by Wiley-VCH GmbH -
dc.language English -
dc.publisher John Wiley and Sons Inc -
dc.title Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition -
dc.type Article -
dc.identifier.doi 10.1002/advs.202002362 -
dc.identifier.wosid 000615812000001 -
dc.identifier.scopusid 2-s2.0-85100619795 -
dc.identifier.bibliographicCitation Kim, Kyungsoo. (2021-04). Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition. Advanced Science, 8(7), 2002362. doi: 10.1002/advs.202002362 -
dc.description.isOpenAccess TRUE -
dc.subject.keywordAuthor machine learning -
dc.subject.keywordAuthor P(VDF-TrFE) -
dc.subject.keywordAuthor piezoelectric effect -
dc.subject.keywordAuthor tactile avatars -
dc.subject.keywordPlus Digital devices -
dc.subject.keywordPlus Topography -
dc.subject.keywordPlus Electronic device -
dc.subject.keywordPlus Learning structure -
dc.subject.keywordPlus Physical information -
dc.subject.keywordPlus Sliding velocities -
dc.subject.keywordPlus Tactile information -
dc.subject.keywordPlus Tactile perception -
dc.subject.keywordPlus Tactile sensation -
dc.subject.keywordPlus Tactile sensing system -
dc.subject.keywordPlus Deep learning -
dc.citation.number 7 -
dc.citation.startPage 2002362 -
dc.citation.title Advanced Science -
dc.citation.volume 8 -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Chemistry; Science & Technology - Other Topics; Materials Science -
dc.relation.journalWebOfScienceCategory Chemistry, Multidisciplinary; Nanoscience & Nanotechnology; Materials Science, Multidisciplinary -
dc.type.docType Article -
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