A Surrogate Model Based on a Finite Element Model of Abdomen for Real-Time Visualisation of Tissue Stress during Physical Examination Training.

Robotic patients show great potential for helping to improve medical palpation training, as they can provide feedback that cannot be obtained in a real patient. They provide information about internal organ deformation that can significantly enhance palpation training by giving medical trainees visual insight based on the pressure they apply for palpation. This can be achieved by using computational models of abdomen mechanics.

Development of detailed finite element models for in silico analyses of brain impact dynamics.

Background And Objective: In the last few decades, several studies have been performed to investigate traumatic brain injuries (TBIs) and to understand the biomechanical response of brain tissues, by using experimental and computational approaches. As part of computational approaches, human head finite element (FE) models show to be important tools in the analysis of TBIs, making it possible to estimate local mechanical effects on brain tissue for different accident scenarios. The present study aims to contribute to the computational approach by means of the development of three advanced FE head models for accurately describing the head tissue dynamics, the first step to predict TBIs.

Multiscale modelling of cerebrovascular injury reveals the role of vascular anatomy and parenchymal shear stresses.

Neurovascular injury is often observed in traumatic brain injury (TBI). However, the relationship between mechanical forces and vascular injury is still unclear. A key question is whether the complex anatomy of vasculature plays a role in increasing forces in cerebral vessels and producing damage.