Abstract
Injury criteria and risk curves are needed for anthropomorphic test devices (dummies) to assess injuries for improving human safety. The present state of knowledge is based on using injury outcomes and biomechanical metrics from post-mortem human subject (PMHS) and mechanical records from dummy tests. Data from these models are combined to develop dummy injury assessment risk curves (IARCs)/dummy injury assessment risk values (IARVs). This simple substitution approach involves duplicating dummy metrics for PMHS tested under similar conditions and pairing with PMHS injury outcomes. It does not directly account for the age of each specimen tested in the PMHS group. Current substitution methods for injury risk assessments use age as a covariate and dummy metrics (e.g., accelerations) are not modified so that age can be directly included in the model. The age-infusion methodology presented in this perspective article accommodates for an annual rate factor that modifies the dummy injury risk assessment responses to account for the age of the PMHS that the injury data were based on. The annual rate factor is determined using human injury risk curves. The dummy metrics are modulated based on individual PMHS age and rate factor, thus “infusing” age into the dummy data. Using PMHS injuries and accelerations from side-impact experiments, matched-pair dummy tests, and logistic regression techniques, the methodology demonstrates the process of age-infusion to derive the IARCs and IARVs.
Highlights
Specialty section: This article was submitted to Biomechanics, a section of the journal Frontiers in Bioengineering and Biotechnology
The present state of knowledge is based on using injury outcomes and biomechanical metrics from post-mortem human subject (PMHS) and mechanical records from dummy tests
Using PMHS injuries and accelerations from sideimpact experiments, matched-pair dummy tests, and logistic regression techniques, the methodology demonstrates the process of age-infusion to derive the injury assessment risk curves (IARCs) and injury assessment risk values (IARVs)
Summary
Extra-cranial accelerations from drop tests of isolated PMHS heads and intact PMHS combined with skull fracture pathologies were used in the promulgation of the head injury criterion (HIC) (Evans et al, 1958; Lissner et al, 1960) This index continues to be used for different impact modes. An acceleration-based criterion is much more dependent on the attached mass because the head mass of the Hybrid III device is the same as the mass of the human head by design; HIC applies to both surrogates Other factors, such as age and gender, do not influence this parameter. Data from the two surrogates are used in the substitution method to derive dummy-specific injury criteria In this method, the anatomical/structural outcome from the biological surrogate is matched with measured dummy metrics to derive dummy-specific injury assessment risk curves (IARCs) from which injury assessment risk values (IARVs) are extracted. Biomechanical studies have used this substitution approach for developing dummy-based IARCs and IARVs (Kuppa et al, 2003; Cavanaugh and Yoganandan, 2015)
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