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ReBase: a framework for acquiring and managing body tracking data

dc.contributor.authorTrotta, Tiago
dc.contributor.authorRodrigues, Luis [UNESP]
dc.contributor.authorBrega, José Remo [UNESP]
dc.contributor.authorGuimarães, Marcelo
dc.contributor.authorRocha, Leonardo
dc.contributor.authorBrandão, Alexandre
dc.contributor.authorDias, Diego
dc.contributor.institutionUniversidade Federal de São João del-Rei
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionCentro Universitário Campo Limpo Paulista (Unifaccamp)
dc.contributor.institutionPontifícia Universidade Católica de Campinas
dc.contributor.institutionUniversidade Federal do Espírito Santo (UFES)
dc.date.accessioned2025-04-29T20:03:08Z
dc.date.issued2024-09-30
dc.description.abstractThere is a great deal of interest in developing virtual reality and augmented reality applications that require data storage, with which developers can interact and create intelligent systems for various purposes, such as applications for neuromotor rehabilitation. These applications provide the benefits of traditional rehabilitation without becoming overwhelming, as they allow the user to be immersed in various scenarios and situations. In addition, the way these applications interact makes it possible to retrieve and analyze the data generated by users’ movements during treatment. However, it is tough to find datasets of body movements, and those that do exist do not include movements specific to the rehabilitation context. This paper, therefore, presents ReBase, a framework that provides a standardized storage system for body movement data. ReBase was designed to allow the collection of data generated by any application, regardless of the form of body tracking used. This paper presents an open API that can be used to communicate with the ReBase database, a package for the Unity game engine, and a library for the Python programming language, which facilitates the integration of new applications into the system. In addition, two applications are shown as case studies within and outside the health area, developed using the tool.en
dc.description.affiliationUniversidade Federal de São João del-Rei
dc.description.affiliationUniversidade Estadual Paulista
dc.description.affiliationCentro Universitário Campo Limpo Paulista (Unifaccamp)
dc.description.affiliationPontifícia Universidade Católica de Campinas
dc.description.affiliationUniversidade Federal do Espírito Santo
dc.description.affiliationUnespUniversidade Estadual Paulista
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipLembaga Pengelola Dana Pendidikan
dc.description.sponsorshipIdCAPES: 001
dc.description.sponsorshipIdLembaga Pengelola Dana Pendidikan: 129/2021
dc.description.sponsorshipIdLembaga Pengelola Dana Pendidikan: P: 2021-GL60J
dc.format.extent152-160
dc.identifierhttp://dx.doi.org/10.1145/3691573.3691578
dc.identifier.citationACM International Conference Proceeding Series, p. 152-160.
dc.identifier.doi10.1145/3691573.3691578
dc.identifier.scopus2-s2.0-85206563379
dc.identifier.urihttps://hdl.handle.net/11449/305446
dc.language.isoeng
dc.relation.ispartofACM International Conference Proceeding Series
dc.sourceScopus
dc.subjectAugmented reality
dc.subjectDatabase
dc.subjectFramework
dc.subjectMachine learning
dc.subjectNeurorehabilitation
dc.subjectVirtual reality
dc.titleReBase: a framework for acquiring and managing body tracking dataen
dc.typeTrabalho apresentado em eventopt
dspace.entity.typePublication
unesp.author.orcid0000-0003-4501-7810[1]
unesp.author.orcid0000-0001-8729-116X[2]
unesp.author.orcid0000-0002-2275-4722[3]
unesp.author.orcid0000-0001-5026-1581[4]
unesp.author.orcid0000-0002-4913-4902[5]
unesp.author.orcid0000-0003-3978-8862[6]
unesp.author.orcid0000-0001-9619-2171[7]

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