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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/42575
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dc.creatorJanaíne Cunha Polesept_BR
dc.creatorGiselle Silva e Fariapt_BR
dc.creatorGiane Amorim Ribeiro Samorapt_BR
dc.creatorLorena Pereira Limapt_BR
dc.creatorChristina Danielli Coelho de Morais Fariapt_BR
dc.creatorAline Alvim Sciannipt_BR
dc.creatorLuci Fuscaldi Teixeira-Salmelapt_BR
dc.date.accessioned2022-06-21T15:29:44Z-
dc.date.available2022-06-21T15:29:44Z-
dc.date.issued2019-07-
dc.citation.volume23pt_BR
dc.citation.issue3pt_BR
dc.citation.spage461pt_BR
dc.citation.epage465pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.jbmt.2019.01.011pt_BR
dc.identifier.issn1360-8592pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/42575-
dc.description.resumoObjective: To examine the validity of the GT3X® ActiGraph accelerometer and the Google Fit® smartphone application in estimating stepping activity in people with chronic stroke. Methods: Thirty-seven stroke survivors walked along a straight, 10 metre hallway over 5 min at their fastest speeds, wearing the GT3X® ActiGraph accelerometer and a smartphone on their paretic lower limb. The criterion-standard measurement made was the actual number of steps, counted by a trained examiner. Results: The mean estimated steps measured by the GT3X® ActiGraph and Google Fit® respectively were 276.7 ± 97.6 and 481.0 ± 119.8; that calculated from the examiner's measurements was 472.0 ± 93.9. Statistically significant associations were found between the actual steps and those estimated by the GT3X® ActiGraph (r = 0.56; p < 0.001) and Google Fit® (r = 0.89; p < 0.001). The Google Fit® application demonstrated the highest reliability coefficient (ICC[2,1] = 0.93; p < 0.001; p = 0.37), compared to that of the GT3X® ActiGraph (ICC[2,1] = 0.32; p < 0.001; p < 0.001). Conclusions: The GT3X® ActiGraph underestimated the data and may not be the most appropriate device to estimate the stepping activity of stroke patients. The findings support the validity of a smartphone application in estimating the stepping activity of individuals with stroke, when worn on the paretic side.pt_BR
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológicopt_BR
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Geraispt_BR
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentEEF - DEPARTAMENTO DE FISIOTERAPIApt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofJournal of Bodywork and Movement Therapiespt_BR
dc.rightsAcesso Restritopt_BR
dc.subjectHemiplegiapt_BR
dc.subjectValidationpt_BR
dc.subjectCell phonept_BR
dc.subjectAccelerometrypt_BR
dc.subject.otherHemiplegiapt_BR
dc.subject.otherValidação de programas de computadorpt_BR
dc.subject.otherSmartphonept_BR
dc.subject.otherAcelerometriapt_BR
dc.subject.otherAcidente vascular cerebralpt_BR
dc.subject.otherCaminhadapt_BR
dc.titleGoogle fit smartphone application or Gt3X Actigraph: which is better for detecting the stepping activity of individuals with stroke?: a validity studypt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://www.sciencedirect.com/science/article/pii/S1360859219300658?via%3Dihub#!pt_BR
dc.identifier.orcidhttps://orcid.org/ 0000-0003-3366-1545pt_BR
dc.identifier.orcidhttps://orcid.org/ 0000-0001-5102-369Xpt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-9784-9729pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-5968-2195pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-8358-8636pt_BR
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