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Brain strain secondary to head impact or inertial loading is closely associated with pathologic observations in the brain. The only experimental brain strain dataset under loadings close to traumatic levels was calculated by imposing the experimentally measured motion of markers embedded in the brain to an auxiliary model formed by triad elements (Hardy et al., 2007). However, fidelity of the calculated strain as well as the suitability of using triad elements for three-dimensional (3D) strain estimation remains to be verified. Therefore, this study proposes to use tetrahedron elements as a new approach to estimate the brain strain. Fidelity of this newly-proposed approach along with the previous triad-based approach is evaluated with the aid of three independently-developed finite element (FE) head models by numerically replicating the experimental impacts and strain estimation procedures.

Relative motion between the brain and skull and brain deformation are biomechanics aspects associated with many types of traumatic brain injury (TBI). Thus far, there is only one experimental endeavor (Hardy et al., 2007) reported brain strain under loading conditions commensurate with levels that were capable of producing injury. Most of the existing finite element (FE) head models are validated against brain-skull relative motion and then used for TBI prediction based on strain metrics. However, the suitability of using a model validated against brain-skull relative motion for strain prediction remains to be determined. To partially address the deficiency of experimental brain deformation data, this study revisits the only existing dynamic experimental brain strain data and updates the original calculations, which reflect incremental strain changes. The brain strain is recomputed by imposing the measured motion of neutral density target (NDT) to the NDT triad model.

This study describes a method to identify laboratory test procedures and impact response requirements suitable for assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of the experimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility and relevance of the available experimental data. A weighted averaging procedure was chosen in order to consider different contributions from the various test conditions and target measurements based on experimental error. According to the quality criteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of response curves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time history response to the measured data.

Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided.

Pedestrians are one of the least protected groups in urban traffic and frequently suffer fatal head injuries. An important boundary condition for the head is the cervical spine, and it has previously been demonstrated that neck muscle activation is important for head kinematics during inertial loading. It has also been shown in a recent numerical study that a tensed neck musculature also has some influence on head kinematics during a pedestrian impact situation. The aim of this study was to analyze the influence on head kinematics and injury metrics during the isolated time of head impact by comparing a pedestrian with relaxed neck and a pedestrian with increased tonus. The human body Finite Element model THUMS Version 1.4 was connected to head and neck models developed at KTH and used in pedestrian-to-vehicle impact simulations with a generalized hood, so that the head would impact a surface with an identical impact response in all simulations.

The aim of this study is to evaluate all the 58 available NFL cases and compare various predictors for mild traumatic brain injuries using a detailed and extensively validated finite element model of the human head. Global injury measures such as magnitude in angular and translational acceleration, change in angular velocity, head impact power (HIP) and HIC were also investigated with regard to their ability to predict the intracranial pressure and strains associated with injury. The brain material properties were modeled using a hyperelastic and viscoelastic constitutive law. Also, three different stiffness parameters, encompassing a range of published brain tissue properties, were tested. 8 tissue injury predictors were evaluated for 6 different regions, covering the entire cerebrum, as well as for the whole brain. In addition, 10 head kinematics based predictors were evaluated both for correlation with injury as well as with strain and pressure.

A parameterized, or scalable, finite element (FE) model of the human head was developed and validated against the available cadaver experiment data for three impact directions (frontal, occipital and lateral). The brain material properties were modeled using a hyperelastic and viscoelastic constitutive law. The interface between the skull and the brain was modeled in three different ways ranging from purely tied (no-slip) to sliding (free-slip). Two sliding contact definitions were compared with the tied condition. Also, three different stiffness parameters, encompassing the range of published brain tissue properties, were tested. The model using the tied contact definition correlated well with the experimental results for the coup and contrecoup pressures in a frontal impact while the sliding interface models did not. Relative motion between the skull and the brain in low-severity impacts appears to be relatively insensitive to the contact definitions.