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Azure Kinect body tracking under review for the specific case of upper limb exercises

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Azure Kinect body tracking under review for the specific case of upper limb exercises

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dc.contributor.author Ivorra, Eugenio es_ES
dc.contributor.author Ortega Pérez, Mario es_ES
dc.contributor.author Alcañiz Raya, Mariano Luis es_ES
dc.date.accessioned 2022-02-14T19:02:50Z
dc.date.available 2022-02-14T19:02:50Z
dc.date.issued 2021-06 es_ES
dc.identifier.uri http://hdl.handle.net/10251/180803
dc.description.abstract [EN] A tool for human pose estimation and quantification using consumer-level equipment is a long-pursued objective. Many studies have employed the Microsoft Kinect v2 depth camera but with recent release of the new Kinect Azure a revision is required. This work researches the specific case of estimating the range of motion in five upper limb exercises using four different pose estimation methods. These exercises were recorded with the Kinect Azure camera and assessed with the OptiTrack motion tracking system as baseline. The statistical analysis consisted of evaluation of intra-rater reliability with intra-class correlation, the Pearson correlation coefficient and Bland-Altman statistical procedure. The modified version of the OpenPose algorithm with the post-processing algorithm PoseFix had excellent reliability with most intra-class correlations being over 0.75. The Azure body tracking algorithm had intermediate results. The results obtained justify clinicians employing these methods, as quick and low-cost simple tools, to assess upper limb angles es_ES
dc.description.sponsorship THE OPTITRACK 3D CAPTURE MOVEMENT SYSTEM WAS FUNDED BY THE EUROPEAN UNION THROUGH THE ERDF (EUROPEAN REGIONAL DEVELOPMENT FUND) PROGRAM OF THE VALENCIAN COMMUNITY 2014-2020 (IDIFEDER/2018/029) es_ES
dc.language Inglés es_ES
dc.publisher MM Publishing es_ES
dc.relation.ispartof MM Science Journal (Online) es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Human pose estimation es_ES
dc.subject Microsoft Azure Kinect es_ES
dc.subject Upper limb exercises es_ES
dc.subject OptiTrack system es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Azure Kinect body tracking under review for the specific case of upper limb exercises es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.17973/MMSJ.2021_6_2021012 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EDUC.INVEST.CULT.DEP//IDIFEDER%2F2018%2F029//LENI INFRAESTRUCTURAS GVA/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Ivorra, E.; Ortega Pérez, M.; Alcañiz Raya, ML. (2021). Azure Kinect body tracking under review for the specific case of upper limb exercises. MM Science Journal (Online). 2021:4333-4341. https://doi.org/10.17973/MMSJ.2021_6_2021012 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.17973/MMSJ.2021_6_2021012 es_ES
dc.description.upvformatpinicio 4333 es_ES
dc.description.upvformatpfin 4341 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 2021 es_ES
dc.identifier.eissn 1805-0476 es_ES
dc.relation.pasarela S\440124 es_ES
dc.contributor.funder GENERALITAT VALENCIANA es_ES
upv.costeAPC 568,7 es_ES


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