Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/79708
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dc.creatorManuel R. Barbosa
dc.creatorTeresa Amaral
dc.creatorMaria de Fátima Chousal
dc.creatorMaria Teresa Restivo
dc.date.accessioned2019-01-31T18:21:47Z-
dc.date.available2019-01-31T18:21:47Z-
dc.date.issued2010
dc.identifier.othersigarra:103261
dc.identifier.urihttps://repositorio-aberto.up.pt/handle/10216/79708-
dc.description.abstractAbstract: The amount of fat in human body composition relative to total body weight(%BF) is considered a determinant factor to a healthier and longer life. In this paper aneural network approach, that overcomes some of the current limitations of assessing%BF through skinfold thickness measurement with calliper devices, is presented. Neuralnetworks recognised capabilities in modelling nonlinear problems can provide a valuabletool to deal with the inherent nonlinear behaviour of body tissues. The approach wastested on a sample of elder individuals, men and women, showing better performancewhen compared with two available alternative methodologies.
dc.language.isoeng
dc.relation.ispartofCONTROLO2010
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectCiências Tecnológicas, Ciências da Saúde, Engenharia electrotécnica, electrónica e informática
dc.subjectTechnological sciences, Health sciences, Electrical engineering, Electronic engineering, Information engineering
dc.titleNeural networks based approach to estimate body fat (%BF)
dc.typeArtigo em Livro de Atas de Conferência Nacional
dc.contributor.uportoFaculdade de Ciências da Nutrição e Alimentação
dc.contributor.uportoFaculdade de Engenharia
dc.subject.fosCiências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
dc.subject.fosEngineering and technology::Electrical engineering, Electronic engineering, Information engineering
Appears in Collections:FCNAUP - Artigo em Livro de Atas de Conferência Nacional
FEUP - Artigo em Livro de Atas de Conferência Nacional

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