TY - JOUR
T1 - Assessing the female figure identification technique’s reliability as a body shape classification system
AU - Parker, Christopher J.
AU - Hayes, Steven George
AU - Brownbridge, Kathryn
AU - Gill, Simeon
N1 - Funding Information:
The authors thank Manchester Metropolitan University’s technical team for providing support during body scanning, Dr. Abu Sadat Muhammad Sayem for conceiving that shoulders may relate to body shape and the participants for participating in this study and for consenting to their data’s academic use.
Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - 3D body scanning
KW - Body shape
KW - anthropometrics
KW - clothing fit
KW - measurement
UR - http://www.scopus.com/inward/record.url?scp=85104324298&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/c0b4bd76-769b-37fd-8356-b58454d214d1/
U2 - 10.1080/00140139.2021.1902572
DO - 10.1080/00140139.2021.1902572
M3 - Article
SN - 0014-0139
VL - 64
SP - 1035
EP - 1051
JO - Ergonomics
JF - Ergonomics
IS - 8
ER -