Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/41641
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dc.contributor.authorMatos, Tomáspt_PT
dc.contributor.authorVornicoglo, Danielpt_PT
dc.contributor.authorCoelho, Paulo Jorgept_PT
dc.contributor.authorZdravevski, Eftimpt_PT
dc.contributor.authorAlbuquerque, Carlospt_PT
dc.contributor.authorPires, Ivan Miguelpt_PT
dc.date.accessioned2024-04-19T16:45:51Z-
dc.date.available2024-04-19T16:45:51Z-
dc.date.issued2024-02-
dc.identifier.urihttp://hdl.handle.net/10773/41641-
dc.description.abstractThere is growing interest in the automated measurement of physical fitness tests, such as the Arm Curl Test, to enable more objective and accurate assessments. This review aimed to systematically analyze the types of sensors and technological methods used for automated Arm Curl Test measurement and their benefits for different populations. The search consisted of the search related to the possibilities to measure the Arm Curl Test results with sensors in scientific databases, including PubMed Central, IEEE Explore, Elsevier, Springer, MDPI, ACM, and PMC, published from January 2010 to October 2022. The analysis included 30 studies from 15 nations with diverse populations analyzed. According to data extraction, the most prevalent sensors were chronometers, accelerometers, stadiometers, and dynamometers. In the investigations, statistical analysis predominated. The study shows how automated sensor technologies can objectively measure the Arm Curl Test. The detected sensors combined with statistical analysis techniques can enhance assessments. Applications for the Arm Curl Test may be improved even more with more research on cutting-edge sensors and algorithms. This evaluation offers insightful information about utilizing sensor-based automation to enhance Arm Curl Testing.pt_PT
dc.language.isoengpt_PT
dc.publisherSpringerpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PTpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00308%2F2020/PTpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00742%2F2020/PTpt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectArm Curl Testpt_PT
dc.subjectIoTpt_PT
dc.subjectSystematic reviewpt_PT
dc.subjectMobile devicespt_PT
dc.subjectTelemedicinept_PT
dc.subjectSensorspt_PT
dc.titleCan sensors be used to measure the Arm Curl Test results? a systematic reviewpt_PT
dc.typearticlept_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
degois.publication.issue2pt_PT
degois.publication.titleDiscover Applied Sciencespt_PT
degois.publication.volume6pt_PT
dc.identifier.doi10.1007/s42452-024-05643-5pt_PT
dc.identifier.essn3004-9261pt_PT
dc.identifier.articlenumber48pt_PT
Appears in Collections:ESTGA - Artigos
IT - Artigos

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