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Real-time blink detection as an indicator of computer vision syndrome in real-life settings: an exploratory study

dc.contributor.authorLapa, Inês
dc.contributor.authorFerreira, Simão
dc.contributor.authorMateus, Catarina
dc.contributor.authorRocha, Nuno
dc.contributor.authorRodrigues, Matilde
dc.date.accessioned2023-12-11T16:09:00Z
dc.date.available2023-12-11T16:09:00Z
dc.date.issued2023-11-04
dc.description.abstractWith the increase in the number of people using digital devices, complaints about eye and vision problems have been increasing, making the problem of computer vision syndrome (CVS) more serious. Accompanying the increase in CVS in occupational settings, new and unobstructive solutions to assess the risk of this syndrome are of paramount importance. This study aims, through an exploratory approach, to determine if blinking data, collected using a computer webcam, can be used as a reliable indicator for predicting CVS on a real-time basis, considering real-life settings. A total of 13 students participated in the data collection. A software that collected and recorded users’ physiological data through the computer’s camera was installed on the participants’ computers. The CVS-Q was applied to determine the subjects with CVS and its severity. The results showed a decrease in the blinking rate to about 9 to 17 per minute, and for each additional blink the CVS score lowered by 1.26. These data suggest that the decrease in blinking rate was directly associated with CVS. These results are important for allowing the development of a CVS real-time detection algorithm and a related recommendation system that provides interventions to promote health, well-being, and improved performance.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationLapa, I., Ferreira, S., Mateus, C., Rocha, N., & Rodrigues, M. A. (2023). Real-Time Blink Detection as an Indicator of Computer Vision Syndrome in Real-Life Settings: An Exploratory Study. International Journal of Environmental Research and Public Health, 20(5), 4569. https://doi.org/10.3390/ijerph20054569pt_PT
dc.identifier.doi10.3390/ijerph20054569pt_PT
dc.identifier.eissn1660-4601
dc.identifier.urihttp://hdl.handle.net/10400.22/24133
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationThis research was funded by ITEA3 and Compete 2020—POCI-01-0247-FEDER-046168| Lisboa-01-0247-FEDER-046168.pt_PT
dc.relation.publisherversionhttps://www.mdpi.com/1660-4601/20/5/4569pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectComputer vision syndromept_PT
dc.subjectEye blinkpt_PT
dc.subjectBlinking ratept_PT
dc.subjectEye-blink detectionpt_PT
dc.titleReal-time blink detection as an indicator of computer vision syndrome in real-life settings: an exploratory studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage11pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleInternational Journal of Environmental Research and Public Healthpt_PT
oaire.citation.volume20 (5)pt_PT
person.familyNameFerreira
person.familyNameMateus
person.familyNameRocha
person.familyNameRodrigues
person.givenNameSimão
person.givenNameCatarina
person.givenNameNuno
person.givenNameMatilde
person.identifier2680796
person.identifier.ciencia-idB11E-1BD3-5F34
person.identifier.ciencia-id2511-2C7F-6252
person.identifier.ciencia-id5110-3A70-C3F3
person.identifier.orcid0000-0001-8233-2217
person.identifier.orcid0000-0003-4472-5049
person.identifier.orcid0000-0002-8472-2603
person.identifier.orcid0000-0001-6175-6934
person.identifier.ridN-7022-2015
person.identifier.scopus-author-id57359736400
person.identifier.scopus-author-id55485977900
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication0bd5b0fc-6849-4f36-b751-87e7f4c81eff
relation.isAuthorOfPublication7433c2c9-3ce3-4ad8-b268-7255233bda5b
relation.isAuthorOfPublication7809ef89-8994-4ef1-a1e4-92fe46b0da89
relation.isAuthorOfPublication8ddb200d-027c-40ca-8ca4-7e3a5981bcb1
relation.isAuthorOfPublication.latestForDiscovery0bd5b0fc-6849-4f36-b751-87e7f4c81eff

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