Predicting pelvis geometry using a morphometric model with overall anthropometric variables
Journal article, 2021

Pelvic fractures have been identified as the second most common AIS2+ injury in motor vehicle crashes, with the highest early mortality rate compared to other orthopaedic injuries. Further, the risk is associated with occupant sex, age, stature and body mass index (BMI). In this study, clinical pelvic CT scans from 132 adults (75 females, 57 males) were extracted from a patient database. The population shape variance in pelvis bone geometry was studied by Sparse Principal Component Analysis (SPCA) and a morphometric model was developed by multi- variate linear regression using overall anthropometric variables (sex, age, stature, BMI). In the analysis, SPCA identified 15 principal components (PCs) describing 83.6% of the shape variations. Eight of these were signifi- cantly captured (α < 0.05) by the morphometric model, which predicted 29% of the total variance in pelvis geometry. The overall anthropometric variables were significantly related to geometrical features primarily in the inferior-anterior regions while being unable to significantly capture local sacrum features, shape and position of ASIS and lateral tilt of the iliac wings. In conclusion, a new detailed morphometric model of the pelvis bone demonstrated that overall anthropometric variables account for only 29% of the variance in pelvis geometry. Furthermore, variations in the superior-anterior region of the pelvis, with which the lap belt is intended to interact, were not captured. Depending on the scenario, shape variations not captured by overall anthropometry could have important implications for injury prediction in traffic safety analysis.

Sparse Principal Component Analysis (SPCA)

Multivariate linear regression

Pelvis geometry

Shape variance

Morphometric model


Erik Brynskog

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Johan Iraeus

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Matthew P. Reed

University of Michigan

Johan Davidsson

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Journal of Biomechanics

0021-9290 (ISSN) 18732380 (eISSN)

Vol. 126 110633

Höft- och ryggskadepredikteringsmodeller för kvinnor och män i varierande sittställningar i framtida fordon

VINNOVA (2018-04998), 2019-04-01 -- 2022-03-31.

Pelvis and spine injury predicting models for women and men in a variety of sitting postures in future autonomous cars

FFI - Strategic Vehicle Research and Innovation (2018-04998), 2019-04-01 -- 2022-03-31.

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