From Impact to Insight: Finite Element Modeling of Real-World Head Trauma

QC 2025-04-25

Abstract

Traumatic head injuries represent a major global health burden, affecting up to 70 million people annually world-wide. To study head injury mechanisms and evaluate preventive measures, virtual, anatomically-detailed human surrogates, referred to as Human Body Models (HBMs), can be created using Finite Element (FE) modeling techniques. Such FE models can be used to computationally recreate real-world head traumas to study human response to impact and reveal injury mechanisms. However, since FE is an inherently heavy computational task, there are numerous modeling challenges associated with using FE analysis for this purpose: constitutive models need to be appointed to complex biological tissues, models need to be properly validated, the chosen approach should be feasible in terms of time, and so forth. This doctoral thesis aims to address a few of these difficulties.

This thesis is composed of four comprehensive studies, each related to the overall objective of developing new methodologies and models, and further developing existing ones, for in-depth FE reconstructions of real-world head trauma. To emphasize their applicability in head injury research, the four studies also feature in-depth reconstructions of real-world injurious events. In the first study, a male and female pedestrian HBM was developed based on an existing occupant HBM, along with an efficient framework for anthropometric personalization. In the second study, a framework for reconstructing head traumas of pedestrians and cyclists in real-world road traffic accidents was developed, validated and exemplified by reconstructing 20 real-world cases. In the third study, a material model for cranial bone was developed and validated, and used for predicting skull fractures in five fall accidents. Lastly, in the fourth study, the material model was applied to a subject-specific head model, used to conduct an in-depth reconstruction of a workplace fatality to assess the protective effect of construction helmets.

Together, these four studies highlight how in-depth FE reconstructions, involving geometrically personalized models of the human body, can provide head injury predictions with striking resemblance to real-world data. When conducted with care, such reconstructions can offer valuable insights into the complex dynamics of head trauma. They can be indispensable tools for evaluating injury prevention strategies, and can potentially be useful within the field of forensic medicine, as they may help open up for objectification of forensic evaluations.

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