PMID- 37659277
OWN - NLM
STAT- MEDLINE
DCOM- 20230919
LR  - 20230919
IS  - 1879-2057 (Electronic)
IS  - 0001-4575 (Linking)
VI  - 192
DP  - 2023 Nov
TI  - Assessment of finite element human body and ATD models in estimating injury risk 
      in far-side impacts using field-based injury risk.
PG  - 107274
LID - S0001-4575(23)00321-4 [pii]
LID - 10.1016/j.aap.2023.107274 [doi]
AB  - The objective of this study was to assess the ability of finite element human 
      body models (FEHBMs) and Anthropometric Test Device (ATD) models to estimate 
      occupant injury risk by comparing it with field-based injury risk in far-side 
      impacts. The study used the Global Human Body Models Consortium midsize male 
      (M50-OS+B) and small female (F05-OS+B) simplified occupant models with a modular 
      detailed brain, and the ES-2Re and SID-IIs ATD models in the simulated far-side 
      crashes. A design of experiments (DOE) with a total of 252 simulations was 
      conducted by varying lateral DeltaV (10-50kph; 5kph increments), the principal 
      direction of force (PDOF 50 degrees , 60 degrees , 65 degrees , 70 degrees , 75 degrees , 80 degrees , 90 degrees ), and occupant models. 
      Models were gravity-settled and belted into a simplified vehicle model (SVM) 
      modified for far-side impact simulations. Acceleration pulses and vehicle 
      intrusion profiles used for the DOE were generated by impacting a 2012 Camry 
      vehicle model with a mobile deformable barrier model across the 7 PDOFs and 9 
      lateral DeltaV's in the DOE for a total of 63 additional simulations. Injury risks 
      were estimated for the head, chest, lower extremity, pelvis (AIS 2+; AIS 3+), and 
      abdomen (AIS 3+) using logistic regression models. Combined AIS 3+ injury risk 
      for each occupant was calculated using AIS 3+ injury risk estimations for the 
      head, chest, abdomen, and lower extremities. The injury risk calculated using 
      computational models was compared with field-based injury risk derived from 
      NASS-CDS by calculating their correlation coefficient. The field-based injury 
      risk was calculated using risk curves that were created based on real-world crash 
      data in a previous study (Hostetler et al., 2020). Occupant age (40 years), 
      seatbelt use (belted occupant), collision deformation classification, lateral DeltaV, 
      and PDOF of the crash event were used in these curves to estimate field injury 
      risk. Large differences in the kinematics were observed between HBM and ATD 
      models. ATD models tended to overestimate risk in almost every case whereas HBMs 
      yielded better risk estimates overall. Chest and lower extremity risks were the 
      least correlated with field injury risk estimates. The overall risk of AIS 
      3+ injury risk was the strongest comparison to the field data-based risk curves. 
      The HBMs were still not able to capture all the variance but future studies can 
      be carried out that are focused on investigating their shortfalls and improving 
      them to estimate injury risk closer to field injury risk in far-side crashes.
CI  - Copyright (c) 2023 Elsevier Ltd. All rights reserved.
FAU - Devane, Karan
AU  - Devane K
AD  - Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, 
      NC, USA. Electronic address: kdevane@wakehealth.edu.
FAU - Hsu, Fang-Chi
AU  - Hsu FC
AD  - Department of Biostatistics and Data Science, Division of Public Health Sciences, 
      Wake Forest University School of Medicine, Winston-Salem, NC, USA.
FAU - Koya, Bharath
AU  - Koya B
AD  - Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, 
      NC, USA.
FAU - Davis, Matthew
AU  - Davis M
AD  - Elemance, LLC., Winston-Salem, NC, USA.
FAU - Weaver, Ashley A
AU  - Weaver AA
AD  - Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, 
      NC, USA.
FAU - Scott Gayzik, F
AU  - Scott Gayzik F
AD  - Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, 
      NC, USA.
FAU - Guleyupoglu, Berkan
AU  - Guleyupoglu B
AD  - Elemance, LLC., Winston-Salem, NC, USA.
LA  - eng
PT  - Journal Article
DEP - 20230831
PL  - England
TA  - Accid Anal Prev
JT  - Accident; analysis and prevention
JID - 1254476
SB  - IM
MH  - Humans
MH  - Female
MH  - Male
MH  - Adult
MH  - *Human Body
MH  - Finite Element Analysis
MH  - *Accidents, Traffic
MH  - Acceleration
MH  - Anthropometry
OTO - NOTNLM
OT  - ATD model
OT  - Far-side impact
OT  - GHBMC
OT  - Human body model
OT  - Injury risk
COIS- Declaration of Competing Interest The authors declare the following financial 
      interests/personal relationships which may be considered as potential competing 
      interests: F. Scott Gayzik and Matthew Davis are members and Ashley A. Weaver is 
      a consultant of Elemance, LLC, which distributes academic and commercial licenses 
      for the use of GHBMC-owned computational human body models.
EDAT- 2023/09/03 00:41
MHDA- 2023/09/19 06:43
CRDT- 2023/09/02 18:08
PHST- 2023/03/01 00:00 [received]
PHST- 2023/08/11 00:00 [revised]
PHST- 2023/08/26 00:00 [accepted]
PHST- 2023/09/19 06:43 [medline]
PHST- 2023/09/03 00:41 [pubmed]
PHST- 2023/09/02 18:08 [entrez]
AID - S0001-4575(23)00321-4 [pii]
AID - 10.1016/j.aap.2023.107274 [doi]
PST - ppublish
SO  - Accid Anal Prev. 2023 Nov;192:107274. doi: 10.1016/j.aap.2023.107274. Epub 2023 
      Aug 31.