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Automating senior fitness testing through gesture detection with depth sensors

2015Book part Open access
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dc.contributor.authorGonçalves, A. R.
dc.contributor.authorCameirão, M. S.
dc.contributor.authorBermúdez i Badia, S.
dc.contributor.authorGouveia, E. R.
dc.date.accessioned2022-09-12T13:37:42Z
dc.date.available2022-09-12T13:37:42Z
dc.date.issued2015
dc.description.abstractSedentarism has a negative impact on health, life expectancy and quality of life, especially in older adults. The assessment of functional fitness helps evaluating the effects of ageing and sedentarism, and this assessment is typically done through validated battery tests such as the Senior Fitness Test (SFT). In this paper we present a computer-based system for assisting and automating SFT administration and scoring in the elderly population. Our system assesses lower body strength, agility and dynamic balance, and aerobic endurance making use of a depth sensor for body tracking and multiple gesture detectors for the evaluation of movement execution. The system was developed and trained with optimal data collected in laboratory conditions and its performance was evaluated in a real environment with 22 elderly end-users, and compared to traditional SFT administered by an expert. Results show a high accuracy of our system in identifying movement patterns (>95%) and consistency with the traditional fitness assessment method. Our results suggest that this technology is a viable low cost option to assist in the fitness assessment of elderly that could be deployed for at home use in the context of fitness programs.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationGonçalves, A. R., Gouveia, E. R., Cameirão, M. S., & Bermúdez i Badia, S. (2015, November). Automating senior fitness testing through gesture detection with depth sensors. In IET International Conference on Technologies for Active and Assisted Living (TechAAL) (pp. 1-6). IET.pt_PT
dc.identifier.doi10.1049/ic.2015.0132pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/4599
dc.language.isoengpt_PT
dc.publisherIETpt_PT
dc.relationLaboratory for Robotics and Engineering Systems
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectSenior fitness testpt_PT
dc.subjectOlder adultspt_PT
dc.subjectAssistive technologypt_PT
dc.subjectGesture detectionpt_PT
dc.subjectKinectpt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleAutomating senior fitness testing through gesture detection with depth sensorspt_PT
dc.typebook part
dspace.entity.typePublication
oaire.awardTitleLaboratory for Robotics and Engineering Systems
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F50009%2F2013/PT
oaire.citation.endPage6 .pt_PT
oaire.citation.startPage6 .pt_PT
oaire.citation.titleIET International Conference on Technologies for Active and Assisted Living (TechAAL)pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameGonçalves
person.familyNameCameirão
person.familyNameBermúdez i Badia
person.familyNameGouveia
person.givenNameAfonso
person.givenNameMónica
person.givenNameSergi
person.givenNameÉlvio Rúbio
person.identifier239789
person.identifier.ciencia-id0A12-4F21-0CC2
person.identifier.ciencia-idCA17-5E88-2B37
person.identifier.ciencia-id3B10-8BDF-0D67
person.identifier.orcid0000-0003-3196-2678
person.identifier.orcid0000-0002-5352-0128
person.identifier.orcid0000-0003-4452-0414
person.identifier.orcid0000-0003-0927-692X
person.identifier.ridC-8675-2018
person.identifier.ridC-8681-2018
person.identifier.scopus-author-id21740694600
person.identifier.scopus-author-id6506360007
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typebookPartpt_PT
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