TY - GEN
T1 - Pelvic injury survival analysis for a finite element human body model using multiple data sets
AU - Weaver, Caitlin M.
AU - Miller, Anna N.
AU - Stitzel, Joel D.
N1 - Funding Information:
The authors would like to acknowledge the Soldier Protection Sciences Branch of the US Army Research Laboratory, Elemance, LLC, and the Science Mathematics And Research for Transformation (SMART) Scholarship for Service Program for their support and collaboration.
Publisher Copyright:
© 2018 ASME.
PY - 2018
Y1 - 2018
N2 - Finite element (FE) computational human body models (HBMs) have gained popularity over the past several decades as human surrogates for use in blunt injury research. FE HBMs are critical for the analysis of local injury mechanisms. These metrics are challenging to measure experimentally and demonstrate an important advantage of HBMs. The objective of this study is to evaluate the injury risk predictive power of localized metrics to predict the risk of pelvic fracture in a FE HBM. The Global Human Body Models Consortium (GHBMC) 50th percentile detailed male model (v4.3) was used for this study. Crosssectional and cortical bone surface instrumentation was implemented in the GHBMC pelvis. Lateral impact FE simulations were performed using input data from tests performed on post mortem human subjects (PMHS). Predictive power of the FE force and strain outputs on localized fracture risk was evaluated using the receiver operator characteristic (ROC) curve analysis. The ROC curve analysis showed moderate predictive power for the superior pubic ramus and sacrum. Additionally, cross-sectional force was compared to a range of percentile outputs of maximum principal, minimum principal, and effective cortical element strains. From this analysis it was determined that cross-sectional force was the best predictor of localized pelvic fracture.
AB - Finite element (FE) computational human body models (HBMs) have gained popularity over the past several decades as human surrogates for use in blunt injury research. FE HBMs are critical for the analysis of local injury mechanisms. These metrics are challenging to measure experimentally and demonstrate an important advantage of HBMs. The objective of this study is to evaluate the injury risk predictive power of localized metrics to predict the risk of pelvic fracture in a FE HBM. The Global Human Body Models Consortium (GHBMC) 50th percentile detailed male model (v4.3) was used for this study. Crosssectional and cortical bone surface instrumentation was implemented in the GHBMC pelvis. Lateral impact FE simulations were performed using input data from tests performed on post mortem human subjects (PMHS). Predictive power of the FE force and strain outputs on localized fracture risk was evaluated using the receiver operator characteristic (ROC) curve analysis. The ROC curve analysis showed moderate predictive power for the superior pubic ramus and sacrum. Additionally, cross-sectional force was compared to a range of percentile outputs of maximum principal, minimum principal, and effective cortical element strains. From this analysis it was determined that cross-sectional force was the best predictor of localized pelvic fracture.
UR - http://www.scopus.com/inward/record.url?scp=85060385897&partnerID=8YFLogxK
U2 - 10.1115/IMECE201888447
DO - 10.1115/IMECE201888447
M3 - Conference contribution
AN - SCOPUS:85060385897
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Biomedical and Biotechnology Engineering
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2018 International Mechanical Engineering Congress and Exposition, IMECE 2018
Y2 - 9 November 2018 through 15 November 2018
ER -