Publication:
Balance Measurement Using Microsoft Kinect v2: Towards Remote Evaluation of Patient with the Functional Reach Test

dc.contributor.authorAyed, Ines
dc.contributor.authorJaume-i-Capo, Antoni
dc.contributor.authorMartínez-Bueso, Pau
dc.contributor.authorMir, Arnau
dc.contributor.authorMoya-Alcover, Gabriel
dc.date.accessioned2024-09-18T06:43:35Z
dc.date.available2024-09-18T06:43:35Z
dc.date.issued2021-07
dc.description.abstractTo prevent falls, it is important to measure periodically the balance ability of an individual using reliable clinical tests. As Red Green Blue Depth (RGBD) devices have been increasingly used for balance rehabilitation at home, they may also be used to assess objectively the balance ability and determine the effectiveness of a therapy. For this, we developed a system based on the Microsoft Kinect v2 for measuring the Functional Reach Test (FRT); one of the most used balance clinical tools to predict falls. Two experiments were conducted to compare the FRT measures computed by our system using the Microsoft Kinect v2 with those obtained by the standard method, i.e., manually. In terms of validity, we found a very strong correlation between the two methods (r = 0.97 and r = 0.99 (p < 0.05), for experiments 1 and 2, respectively). However, we needed to correct the measurements using a linear model to fit the data obtained by the Kinect system. Consequently, a linear regression model has been applied and examining the regression assumptions showed that the model works well for the data. Applying the paired t-test to the data after correction indicated that there is no statistically significant difference between the measurements obtained by both methods. As for the reliability of the test, we obtained good to excellent within repeatability of the FRT measurements tracked by Kinect (ICC = 0.86 and ICC = 0.99, for experiments 1 and 2, respectively). These results suggested that the Microsoft Kinect v2 device is reliable and adequate to calculate the standard FRT.en
dc.description.sponsorshipThis work was funded by project EXPLainable Artificial INtelligence systems for health and well-beING (EXPLAINING) (PID2019-104829RA-I00/AEI/10.13039/501100011033), and project TIN2016-81143-R (MINECO/AEI/ERDF, EU). InesAyed benefited from the fellowship FPI/2039/2017 from the Vicepresidencia i Conselleria d'Innovacio, Recerca i Turisme del Govern de les Illes Balears.es_ES
dc.format.number13es_ES
dc.format.page6073es_ES
dc.format.volume11es_ES
dc.identifier.citationAyed I, Jaume-i-Capo A, Martinez-Bueso P, Mir A, Moya-Alcover G. Balance Measurement Using Microsoft Kinect v2: Towards Remote Evaluation of Patient with the Functional Reach Test. Appl Sci-Basel. 2021 Jul;11(13):6073.en
dc.identifier.doi10.3390/app11136073
dc.identifier.e-issn2076-3417es_ES
dc.identifier.journalApplied Sciences-Baseles_ES
dc.identifier.otherhttps://hdl.handle.net/20.500.13003/19460
dc.identifier.scopus2-s2.0-85109972459
dc.identifier.urihttps://hdl.handle.net/20.500.12105/23248
dc.identifier.wos670699300001
dc.language.isoengen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.relation.publisherversionhttps://dx.doi.org/10.3390/app11136073en
dc.rights.accessRightsopen accessen
dc.rights.licenseAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectMicrosoft Kinect v2
dc.subjectDepth sensor
dc.subjectRGBD
dc.subjectHealth care
dc.subjectBalance
dc.subjectFunctional reach test
dc.titleBalance Measurement Using Microsoft Kinect v2: Towards Remote Evaluation of Patient with the Functional Reach Testen
dc.typeresearch articleen
dspace.entity.typePublication
relation.isPublisherOfPublication30293a55-0e53-431f-ae8c-14ab01127be9
relation.isPublisherOfPublication.latestForDiscovery30293a55-0e53-431f-ae8c-14ab01127be9

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