# Influence of Chinstrap Stiffness on Cerebrospinal Fluid Dynamics and Brain Stress in Helmet Impacts
## 2 Materials and Methods
### Helmet Design Processing  
In order to run the simulation, a three-dimensional (3D) design of the helmet and a head model with the physiologic structures of interest must be created. The Autodesk Netfabb design software serves this role as it allows for the accurate development of 3D models while also being able to optimize the shape, rigidity, weight, and allowable force load of products, which ensures its realistic capabilities [26]. Additionally, studies have shown that when compared to human physiologic structures, such as the mandible, the accuracy of the designed 3D mandible model via the Netfabb software was comparable to many other advanced 3D printing models [27]. A total of 13 structures were analyzed with the software. The following structures were used for the representation of the head model: the brainstem, cerebellum, cerebrum, pituitary, skull, jaw, and the filling that surrounds the brain contents, as depicted in Figure 1. These structures were based off of the DICOM images online database. Several structures were left out of the model, such as the skin, meninges, and arachnoid mater. While the primary focus of this study is on the helmet and its direct interaction with the skull and brain, it is important to acknowledge that the exclusion of these anatomical layers constitutes a simplification. The skin and meningeal layers, particularly the dura mater, possess viscoelastic properties that can contribute to energy absorption and redistribution during impact. Their omission may result in an overestimation of stress transmission to intracranial structures, as the model does not account for the damping and shear resistance these tissues provide. This limitation is further discussed in the Discussion Section. The baseball helmet used in the study consisted of a padded inner lining with a hard-shell cover on the exterior. A chinstrap cup was also used for the base of the straps in order to attach and connect to the sides of the helmet. To create the proper sizing of the model, the design program utilizes triangular geometric shapes. These shapes, or nodes, delineate the three contact points that form the 3D shape. By removing nodes, one is able to modify the structure in order to simulate forces impacting the design. This results in an accurate and predictable database that can be used to further make interpretations on how these forces interact throughout and within the structures. Furthermore, the accurate physiologic sizing between the skull, brain, and helmet is achieved by giving each structure its conventional material properties [25]. To ensure the accuracy and reliability of our computational approach, we used the same model (i.e., with patient-specific geometries representing the brain, skull, and surrounding CSF) as previously validated against cadaveric head impact data from [28]. This validation, as reported in [29], demonstrated that the model accurately reproduces brain dynamics observed in experimental conditions. A 3D mesh design was then created for analysis via the Gmsh software program. Gmsh is a 3D finite element grid generator that allows for advanced geometrical elements and visualization [30]. Developing the volume meshes of each part is completed so that the \(x\), \(y\), and \(z\) coordinates of each node in space from the overall model are gathered and further used in the investigation of how each node is affected on impact. The model was then optimized as it enhances the tetrahedral mesh quality and ultimately produces a better mesh for more complex models [30]. Once the overall design is established, it is ready for the overall simulation. The choice of brain constitutive model and the specific location of impact loading are known to influence the predicted biomechanical response in computational head models [31]. Previous studies allowed for the realistic material properties of the human brain and its interaction with its adjacent structures through the proper modeling of each component [32; 33; 34; 35; 36].