Login / Signup

Load-Based Lower Neck Injury Criteria for Females from Rear Impact from Cadaver Experiments.

Narayan YoganandanFrank A PintarAnjishnu Banerjee
Published in: Annals of biomedical engineering (2017)
The objectives of this study were to derive lower neck injury metrics/criteria and injury risk curves for the force, moment, and interaction criterion in rear impacts for females. Biomechanical data were obtained from previous intact and isolated post mortem human subjects and head-neck complexes subjected to posteroanterior accelerative loading. Censored data were used in the survival analysis model. The primary shear force, sagittal bending moment, and interaction (lower neck injury criterion, LNic) metrics were significant predictors of injury. The most optimal distribution was selected (Weibulll, log normal, or log logistic) using the Akaike information criterion according to the latest ISO recommendations for deriving risk curves. The Kolmogorov-Smirnov test was used to quantify robustness of the assumed parametric model. The intercepts for the interaction index were extracted from the primary risk curves. Normalized confidence interval sizes (NCIS) were reported at discrete probability levels, along with the risk curves and 95% confidence intervals. The mean force of 214 N, moment of 54 Nm, and 0.89 LNic were associated with a five percent probability of injury. The NCIS for these metrics were 0.90, 0.95, and 0.85. These preliminary results can be used as a first step in the definition of lower neck injury criteria for women under posteroanterior accelerative loading in crashworthiness evaluations.
Keyphrases
  • endothelial cells
  • electronic health record
  • machine learning
  • pregnant women
  • big data
  • social media
  • adipose tissue
  • artificial intelligence
  • pluripotent stem cells