Analysis of Gender Differences in Online Handwriting Signals for Enhancing e-Health and e-Security Applications

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dc.contributor.authorFaúndez Zanuy, Marcoscs
dc.contributor.authorMekyska, Jiřícs
dc.coverage.issue1cs
dc.coverage.volume15cs
dc.date.issued2023-01-21cs
dc.description.abstractHandwriting is a complex perceptual–motor skill that is mastered around the age of 8. Although its computerized analysis has been utilized in many biometric and digital health applications, the possible effect of gender is frequently neglected. The aim of this paper is to analyze different online handwritten tasks performed by intact subjects and explore gender differences in commonly used temporal, kinematic, and dynamic features. The differences were explored in the BIOSECUR-ID database. We have identified a significant gender difference in on-surface/in-air time of genuine and skilled forgery signatures, on-surface time in cursive letters and numbers, and pressure, speed, and acceleration in text written in capital letters. Our findings accent the need to consider gender as an important confounding factor in studies dealing with online handwriting signal processing.en
dc.formattextcs
dc.format.extent1-12cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationCognitive Computation. 2023, vol. 15, issue 1, p. 1-12.en
dc.identifier.doi10.1007/s12559-023-10116-9cs
dc.identifier.issn1866-9956cs
dc.identifier.orcid0000-0002-6195-193Xcs
dc.identifier.other182508cs
dc.identifier.researcheridK-4001-2015cs
dc.identifier.scopus35746344400cs
dc.identifier.urihttp://hdl.handle.net/11012/209230
dc.language.isoencs
dc.publisherSpringercs
dc.relation.ispartofCognitive Computationcs
dc.relation.urihttps://link.springer.com/article/10.1007/s12559-023-10116-9cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1866-9956/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectonline handwritingen
dc.subjectgender differencesen
dc.subjecttexten
dc.subjectsignatureen
dc.titleAnalysis of Gender Differences in Online Handwriting Signals for Enhancing e-Health and e-Security Applicationsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-182508en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:42:30en
sync.item.modts2025.01.17 18:49:01en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
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