Data Censoring and Parametric Distribution Assignment in the Development of Injury Risk Functions from Biochemical Data

2004 ◽  
Author(s):  
Richard W. Kent ◽  
James R. Funk
Keyword(s):  
Injury Risk ◽  
Biochemical Data ◽  
Risk Functions ◽  
Data Censoring

Injury risk functions for frontal oblique collisions

2018 ◽  
Vol 19 (5) ◽  
pp. 518-522 ◽  
Author(s):  
Nino Andricevic ◽  
Mirko Junge ◽  
Jonas Krampe
Keyword(s):  
Injury Risk ◽  
Risk Functions

scholarly journals Statistical Considerations in the Development of Injury Risk Functions

2014 ◽  
Vol 16 (6) ◽  
pp. 618-626 ◽  
Author(s):  
Timothy L. McMurry ◽  
Gerald S. Poplin
Keyword(s):  
Injury Risk ◽  
Risk Functions

Evaluation of the Field Relevance of Several Injury Risk Functions

2010 ◽  
Author(s):  
Priya Prasad ◽  
Harold J. Mertz ◽  
Dainius J. Dalmotas ◽  
Jeffrey S. Augenstein ◽  
Kennerly Digges
Keyword(s):  
Injury Risk ◽  
Risk Functions

Wavelet-based Non-parametric Estimation of Injury Risk Functions

2007 ◽  
Author(s):  
Zhiqing Cheng ◽  
Annette L. Rizer ◽  
Joseph A. Pellettiere
Keyword(s):  
Injury Risk ◽  
Parametric Estimation ◽  
Risk Functions ◽  
Non Parametric Estimation ◽  
Non Parametric

Development of thoracic injury risk functions for the THOR ATD

2017 ◽  
Vol 106 ◽  
pp. 122-130 ◽  
Author(s):  
Gerald S. Poplin ◽  
Timothy L. McMurry ◽  
Jason L. Forman ◽  
Joseph Ash ◽  
Daniel P. Parent ◽  
...  
Keyword(s):  
Injury Risk ◽  
Thoracic Injury ◽  
Risk Functions

An Injury Risk Function for the Leg, Foot, and Ankle Exposed to Axial Impact Loading Using Force and Impulse

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Ann M. Bailey ◽  
Timothy L. McMurry ◽  
Robert S. Salzar ◽  
Jeff R. Crandall
Keyword(s):  
Injury Risk ◽  
Risk Function ◽  
Axial Loading ◽  
Survival Model ◽  
Natural Period ◽  
Axial Impact ◽  
Injury Prediction ◽  
Leg Injuries ◽  
Risk Functions ◽  
The Military

Most injury risk functions (IRFs) for dynamic axial loading of the leg have been targeted toward automotive applications such as predicting injury caused by intrusion into the occupant compartment from frontal collisions. Recent focus on leg injuries in the military has led to questions about the applicability of these IRFs shorter duration, higher amplitude loading associated with underbody blast (UBB). To investigate these questions, data were collected from seven separate test series that subjected post-mortem human legs to axial impact. A force and impulse-based Weibull survival model was developed from these studies to estimate fracture risk. Specimen age was included as a covariate to reduce variance and improve survival model fit. The injury criterion estimated 50% risk of injury for a leg exposed to 13 N s of impulse at peak force and 8.07 kN of force for force durations less than and greater than half the natural period of the leg, respectively. A supplemental statistical analysis estimated that the proposed IRF improves injury prediction accuracy by more than 9% compared to the predictions from automobile-based risk functions developed for automotive intrusion. The proposed leg IRF not only improves injury prediction for higher rate conditions but also provides a single injury prediction tool for an expanded range of load durations ranging from 5 to 90 ms, which spans both automotive and military loading environments.

Injury risk functions based on population-based finite element model responses: Application to femurs under dynamic three-point bending

2018 ◽  
Vol 19 (sup1) ◽  
pp. S59-S64
Author(s):  
Gwansik Park ◽  
Jason Forman ◽  
Taewung Kim ◽  
Matthew B. Panzer ◽  
Jeff R. Crandall
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Injury Risk ◽  
Element Model ◽  
Population Based ◽  
Three Point Bending ◽  
Risk Functions
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