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Handgrip strength time profile and frailty: an exploratory study

2021-05-31Journal article Open access
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dc.contributor.authorUrbano, Diana
dc.contributor.authorRestivo, Maria Teresa
dc.contributor.authorBarbosa, Manuel Romano
dc.contributor.authorFernandes, Ângela
dc.contributor.authorAbreu, Paulo
dc.contributor.authorChousal, Maria de Fátima
dc.contributor.authorCoelho, Tiago
dc.date.accessioned2021-07-23T09:46:31Z
dc.date.available2021-07-23T09:46:31Z
dc.date.issued2021-05-31
dc.description.abstractThis study aims to explore the use of force vs. time data obtained from an isometric handgrip test to match a frailty state based on the TFI score. BodyGrip, a novel prototype system, is used for handgrip strength over 10 s time interval tests. A cross-sectional study with a non-probabilistic sample of community-dwelling elderly women was conducted. The force/time data collected from the dominant handgrip strength test, together with the Tilburg Frailty Indicator (TFI) test results, were used to train artificial neural networks. Different models were tested, and the frailty matching of TFI scores reached a minimum accuracy of 75%. Despite the small sample size, the BodyGrip system appears to be a promising tool for exploring new frailty-related features. The adopted strategy foresees ultimately configuring the system to be used as an expedite mode for identifying individuals at risk, allowing an easy, quick, and frequent person-centered care approach. Additionally, it is suitable for following up of the elderly in particular, and it may assume a relevant role in the mitigation of the increase in frailty evolution during and after the imposed isolation of the COVID-19 pandemic. Further use of the system will improve the robustness of the artificial neural network algorithm.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationUrbano, D., Restivo, M. T., Barbosa, M. R., Fernandes, Â., Abreu, P., Chousal, M. D., & Coelho, T. (2021). Handgrip Strength Time Profile and Frailty: An Exploratory Study. Applied Sciences, 11(11). https://doi.org/10.3390/app11115134pt_PT
dc.identifier.doi10.3390/app11115134pt_PT
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10400.22/18155
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relation.publisherversionhttps://www.mdpi.com/2076-3417/11/11/5134/htmpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectArtificial neural networkspt_PT
dc.subjectFrailtypt_PT
dc.subjectHandgrip strength time profilept_PT
dc.subjectOccupational healthpt_PT
dc.subjectSmart systemspt_PT
dc.titleHandgrip strength time profile and frailty: an exploratory studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage14pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleApplied Sciencespt_PT
oaire.citation.volume11pt_PT
person.familyNameFernandes
person.familyNameCoelho
person.givenNameÂngela
person.givenNameTiago
person.identifier188655
person.identifier.ciencia-idB417-8E58-EF75
person.identifier.orcid0000-0002-3882-4908
person.identifier.orcid0000-0001-7847-2401
person.identifier.ridJJC-7415-2023
person.identifier.scopus-author-id56583916600
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication82911dfb-0180-4fe0-8266-9a272bfa6858
relation.isAuthorOfPublication7c814c96-7746-4d89-ab01-ed2e4af5ab92
relation.isAuthorOfPublication.latestForDiscovery7c814c96-7746-4d89-ab01-ed2e4af5ab92

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