Injury Risk Curves for the WorldSID 50<sup>th</sup> Male Dummy

Petitjean, Audrey; Trosseille, Xavier; Praxl, Norbert; Hynd, David; Irwin, Annette L.

doi:10.4271/2012-22-0008

Cited by 19 publications

(12 citation statements)

References 19 publications

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“…The methodology was At the outset it should be acknowledged that the ISO working group was tasked to recommend a process for determining injury criteria in the form of probability curves for automotive applications, and the consensus-driven approach was a result of a multi-year collaborative work from an international team of researchers (including the first author of this paper). The recommendation of the working group (WG6 referred in the introduction section) has been used to derive risk curves from side-impact sled tests and foot-ankle-leg PMHS experiments (Petitjean et al, 2012;Yoganandan et al, 2015,a-b). While applying to other body regions and loading environments, it was deemed necessary to re-examine this approach and ensure that the methodology is clear, more general and robust.…”

Section: Discussionmentioning

confidence: 99%

“…Steps in the ISO approach are: (1) collecting data, (2) assigning censor status, (3) checking for multiple injury mechanisms, (4) separating samples by injury mechanism, (5) estimating distribution parameters, (6) identifying overly influential observations, (7) checking the distribution assumption, (8) choosing the distribution, (9) checking the validity of predictions against existing results, (10) calculating 95% confidence intervals, (11) assessing the quality index, and (12) recommending one curve per body region (Petitjean et al, 2012). The suggested approach has been applied to derive risk curves for thoracic and abdominal injuries in nearside-impacts (Petitjean et al, 2012). In addition, survival analysis-based probability curves for foot-ankle-leg injuries resulting from the axial loading mechanism differed from simple logistic regression-based risk curves (Yoganandan et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Deriving injury risk curves using survival analysis from biomechanical experiments

Yoganandan

Banerjee

Hsu

et al. 2016

Journal of Biomechanics

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Injury risk curves from biomechanical experimental data analysis are used in automotive studies to improve crashworthiness and advance occupant safety. Metrics such as acceleration and deflection coupled with outcomes such as fractures and anatomical disruptions from impact tests are used in simple binary regression models. As an improvement, the International Standards Organization suggested a different approach. It was based on survival analysis. While probability curves for side-impact-induced thorax and abdominal injuries and frontal impact-induced foot-ankle-leg injuries are developed using this approach, deficiencies are apparent. The objective of this study is to present an improved, robust and generalizable methodology in an attempt to resolve these issues. It includes: (a) statistical identification of the most appropriate independent variable (metric) from a pool of candidate metrics, measured and or derived during experimentation and analysis processes, based on the highest area under the receiver operator curve, (b) quantitative determination of the most optimal probability distribution based on the lowest Akaike information criterion, (c) supplementing the qualitative/visual inspection method for comparing the selected distribution with a non-parametric distribution with objective measures, (d) identification of overly influential observations using different methods, and (e) estimation of confidence intervals using techniques more appropriate to the underlying survival statistical model. These clear and quantified details can be easily implemented with commercial/open source packages. They can be used in retrospective analysis and prospective design of experiments, and in applications to different loading scenarios such as underbody blast events. The feasibility of the methodology is demonstrated using post mortem human subject experiments and 24 metrics associated with thoracic/abdominal injuries in side-impacts.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deriving injury risk curves using survival analysis from biomechanical experiments

Yoganandan

Banerjee

Hsu

et al. 2016

Journal of Biomechanics

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“…It should be noted that the biofidelity rate of the ES-2re is lower than the WorldSID. [23][24][25] However, in this study, the FE model of the ES-2re was selected because it had extensive injury criteria and associated injury risk curves for the thorax. Figure 20 in Appendix 1 shows the injury criteria and corresponding AIS 3+ curves that were used to assess the risk of serious injuries for different body regions.…”

Section: Fe Modelsmentioning

confidence: 99%

Numerical assessment of occupant responses during the bus rollover test: A finite element parametric study

Seyedi

Jung

2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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Rollover crashes of buses are usually associated with multiple impacts that can result in complex interactions between passengers and a bus superstructure. Although there have been a few field data studies that provide some insights into occupant injuries (e.g. severity and distribution of injuries) during the real-world bus rollover crash, because they had used post-crash data, the occupant kinematics and injury mechanisms were not completely detailed in their results. Based on a literature review, available numerical and experimental studies on a bus rollover safety have mainly focused on structural integrity rather than considering occupant responses in their assessment. In addition, their results about occupant responses in bus rollover crashes show some discrepancies in terms of the estimated injury distribution, severity, and causes. Therefore, the main objective of this study was to provide a more detailed understanding of the occupant kinematics and associated injury risk during the ECE R66 tilt table bus rollover test using validated finite element (FE) models. The ECE R66 tilt table rollover was simulated using a full finite element model of the bus. A 50th percentile male Hybrid III Anthropomorphic test device (ATD) and EuroSID-2re FE models were selected to simulate the occupant’s motion. Each ATD was seated adjacent to the impacted side wall and restrained with a 2-point seatbelt. Simulation parameters included two impact surface friction values and different side window conditions. The results indicated that both ATD estimated the highest injury risk when the partial ejection occurred. They predicted a similar injury risk for the head and thorax. The ES-2re estimated a very low risk of neck injury in all simulations, whereas the Hybrid III estimated the high risk of a neck injury. Finally, recommendations to potentially reduce the injuries were provided and possible future works were suggested.

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“… Shoulder contact force . (A) Comparison of THOR shoulder contact force related to the BDRC DR y , (B) Comparison of WorldSID and THOR shoulder contact force data reported by Pintar et al ( 2007 ), (C) WorldSID injury risk function reported by Petitjean et al ( 2012 ), and (D) developed THOR shoulder force injury risk functions. …”

Section: Literature Review and Standards Framework Developmentmentioning

confidence: 99%

Investigation of the THOR Anthropomorphic Test Device for Predicting Occupant Injuries during Spacecraft Launch Aborts and Landing

Somers

Newby

Lawrence

et al. 2014

Front. Bioeng. Biotechnol.

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The objective of this study was to investigate new methods for predicting injury from expected spaceflight dynamic loads by leveraging a broader range of available information in injury biomechanics. Although all spacecraft designs were considered, the primary focus was the National Aeronautics and Space Administration Orion capsule, as the authors have the most knowledge and experience related to this design. The team defined a list of critical injuries and selected the THOR anthropomorphic test device as the basis for new standards and requirements. In addition, the team down-selected the list of available injury metrics to the following: head injury criteria 15, kinematic brain rotational injury criteria, neck axial tension and compression force, maximum chest deflection, lateral shoulder force and displacement, acetabular lateral force, thoracic spine axial compression force, ankle moments, and average distal forearm speed limits. The team felt that these metrics capture all of the injuries that might be expected by a seated crewmember during vehicle aborts and landings. Using previously determined injury risk levels for nominal and off-nominal landings, appropriate injury assessment reference values (IARVs) were defined for each metric. Musculoskeletal deconditioning due to exposure to reduced gravity over time can affect injury risk during landing; therefore a deconditioning factor was applied to all IARVs. Although there are appropriate injury data for each anatomical region of interest, additional research is needed for several metrics to improve the confidence score.

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Injury Risk Curves for the WorldSID 50^th Male Dummy

Cited by 19 publications

References 19 publications

Deriving injury risk curves using survival analysis from biomechanical experiments

Deriving injury risk curves using survival analysis from biomechanical experiments

Numerical assessment of occupant responses during the bus rollover test: A finite element parametric study

Investigation of the THOR Anthropomorphic Test Device for Predicting Occupant Injuries during Spacecraft Launch Aborts and Landing

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Injury Risk Curves for the WorldSID 50th Male Dummy

Cited by 19 publications

References 19 publications

Deriving injury risk curves using survival analysis from biomechanical experiments

Deriving injury risk curves using survival analysis from biomechanical experiments

Numerical assessment of occupant responses during the bus rollover test: A finite element parametric study

Investigation of the THOR Anthropomorphic Test Device for Predicting Occupant Injuries during Spacecraft Launch Aborts and Landing

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Injury Risk Curves for the WorldSID 50^th Male Dummy