Traumatic Brain Injuries (TBIs) are a pressing global public health issue,
impacting tens of millions of individuals annually. Vulnerable road users
(VRUs), such as pedestrians, are vastly overrepresented in the worldwide TBI
statistics. To evaluate the effectiveness of injury prevention measures,
researchers often employ Finite Element (FE) models of the human body to
virtually simulate the human response to impact in real-world road traffic
accident scenarios. Cependant, VRU accidents occur in a highly uncontrolled
environment and, in consequence, there is a large amount of variables
(covariates), e.g. the vehicle impact speed and VRU body posture, that together
dictate the injurious outcome of the collision. At the same time, since FE
analysis is a computationally heavy task, researchers often need to apply
extensive simplifications to FE models when attempting to predict real-world
VRU head trauma. To help researchers make informed decisions when conducting FE
accident reconstructions, this literature review aims to create an overarching
summary of covariates that have been reported influential in literature. The
review provides researchers with an overview of variables proven to have an
influence on head injury predictions. The material could potentially be useful
as a basis for choosing parameters to include when performing sensitivity
analyses of car-to-pedestrian impact simulations.

Cet article explore les excursions dans le temps et leurs implications.

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