Hierarchical process using Brier Score Metrics for lower leg injury risk curves in vertical impact

Introduction Parametric survival models are used to develop injury risk curves (IRCs) from impact tests using postmortem human surrogates (PMHS). Through the consideration of different output variables, input parameters and censoring, different IRCs could be created. The purpose of this study was to demonstrate the feasibility of the Brier Score Metric (BSM) to determine the optimal IRCs and derive them from lower leg impact tests. Methods Two series of tests of axial impacts to PMHS foot-ankle complex were used in the study. The first series used the metrics of force, time and rate, and covariates of age, posture, stature, device and presence of a boot. Also demonstrated were different censoring schemes: right and exact/uncensored (RC-UC) or right and uncensored/left (RC-UC-LC). The second series involved only one metric, force, and covariates age, sex and weight. It contained interval censored (IC) data demonstrating different censoring schemes: RC-IC-UC, RC-IC-LC and RC-IC-UC-LC. Results For each test set combination, optimal IRCs were chosen based on metric-covariate combination that had the lowest BSM value. These optimal IRCs are shown along with 95% CIs and other measures of interval quality. Forces were greater for UC than LC data sets, at the same risk levels (10% used in North Atlantic Treaty Organisation (NATO)). All data and IRCs are presented. Conclusions This study demonstrates a novel approach to examining which metrics and covariates create the best parametric survival analysis-based IRCs to describe human tolerance, the first step in describing lower leg injury criteria under axial loading to the plantar surface of the foot.