FingMag: Finger Identification Method for Smartwatch

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dc.contributor.authorPARK, KEUNWOOko
dc.contributor.authorLee, Geehyukko
dc.date.accessioned2019-07-18T05:41:56Z-
dc.date.available2019-07-18T05:41:56Z-
dc.date.created2019-06-19-
dc.date.created2019-06-19-
dc.date.created2019-06-19-
dc.date.created2019-06-19-
dc.date.issued2019-05-08-
dc.identifier.citation2019 CHI Conference on Human Factors in Computing Systems, CHI 2019, pp.1 - 6-
dc.identifier.urihttp://hdl.handle.net/10203/263440-
dc.description.abstractInteracting with a smartwatch is difficult owing to its small touchscreen. A general strategy to overcome the limitations of the small screen is to increase the input vocabulary. A popular approach to do this is to distinguish fingers and assign different functions to them. As a finger identification method for a smartwatch, we propose FingMag, a machine-learning-based method that identifies the finger on the screen with the help of a ring. For this identification, the finger's touch position and the magnetic field from a magnet embedded in the ring are used. In an offline evaluation using data collected from 12 participants, we show that FingMag can identify the finger with an accuracy of 96.21% in stationary geomagnetic conditions.-
dc.languageEnglish-
dc.publisherACM Special Interest Group on Computer-Human Interaction (SIGCHI)-
dc.titleFingMag: Finger Identification Method for Smartwatch-
dc.typeConference-
dc.identifier.wosid000482042102090-
dc.identifier.scopusid2-s2.0-85067298556-
dc.type.rimsCONF-
dc.citation.beginningpage1-
dc.citation.endingpage6-
dc.citation.publicationname2019 CHI Conference on Human Factors in Computing Systems, CHI 2019-
dc.identifier.conferencecountryUK-
dc.identifier.conferencelocationGlasgow, Scotland Uk-
dc.identifier.doi10.1145/3290607.3312982-
dc.contributor.localauthorLee, Geehyuk-
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CS-Conference Papers(학술회의논문)
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