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Assessing the female figure identification technique's reliability as a body shape classification system.
Parker, Christopher J; Hayes, Steven George; Brownbridge, Kathryn; Gill, Simeon.
Afiliação
  • Parker CJ; School of Design and Creative Arts, Loughborough University, Loughborough, UK.
  • Hayes SG; School of Materials, The University of Manchester, Manchester, UK.
  • Brownbridge K; Manchester Fashion Institute (MFI), Manchester Metropolitan University, Manchester, UK.
  • Gill S; School of Materials, The University of Manchester, Manchester, UK.
Ergonomics ; 64(8): 1035-1051, 2021 Aug.
Article em En | MEDLINE | ID: mdl-33719914
ABSTRACT
This paper demonstrates the effects of slight differences in measurement definitions on resultant body shape classification. Ergonomic researchers consider the Female Figure Identification Technique (FFIT) a 'gold standard' body shape classification system to describe variation in a population's 3 D profile. Nevertheless, researchers use FFIT without a scientific basis or considering their ergonomic suitability. This paper rigorously evaluates FFIT, focussing on ergonomics, garment construction, and scientific research applications. Through analysing 1,679 3 D Body Scans, we assess the level of agreement between the FFIT's body shape classification when measurements placed following FFIT's or SizeUK's guidance. We establish how different interpretations of FFIT's measurement placement cause the same body to be categorised into different shapes - in up to 40% of cases. FFIT omits shoulder measurements that have little relationship to body shape yet are vital in garment construction. Using FFIT with different datasets and definitions, therefore, leads to inconsistent conclusions about shape differences.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Somatotipos / Ergonomia Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans Idioma: En Revista: Ergonomics Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Somatotipos / Ergonomia Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans Idioma: En Revista: Ergonomics Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido