## 4 Discussion and Limitations  
The research results show that elder people have a greater predisposition to the formation of subdural haematomas. The main cause of this phenomenon is brain atrophy,  
Figure 11: The deviation analysis of the young adult’s (reference) and senior’s brains: left—the quantitative comparison analysis in [mm]. The results distribution graph is also visible next to the scale. Figure 10: Axonometric views of the two different brain models: orange—young adult, and yellow—senior brain models. which leads to increased movement of the cerebral cortex. Therefore, it is crucial to recognise the limitations inherent in the selection of geometric models, the uniqueness of individual bridging vein layouts, and the relatively new nature of the smoothed-particle hydrodynamics (SPH) approach in finite element analysis. One of the primary limitations of this study is the reliance on geometrical models obtained from different individuals. While these models were carefully selected based on statistical analysis using craniometry data, it is essential to acknowledge that the inherent variability in anatomical structures among individuals may introduce biases or limitations to our findings. The diversity in cranial shapes and sizes among the selected models may not fully capture the anatomical diversity of the entire population. Another noteworthy limitation is the individual variability in bridging vein layout [16]. Due to their uniqueness, we compare these layouts to fingerprints, yet this individuality can pose challenges when attempting to establish universal patterns or guidelines. The study findings are based on a specific group of individuals. While they provide valuable insights, extrapolating these results to broader populations or clinical applications should be given attention. Moreover, using SPH within the finite element framework represents a novel approach in this study. This study, based on the FE-SPH approach, endeavours to improve the biofidelity of the head better than the other numerical algorithms, such as the multi-body approach, by offering a more comprehensive and accurate representation of highly deformable tissues, particularly brain tissue. Through systematic manual segmentation and collaboration between engineers and medical doctors, the models developed in this study capture intricate anatomical details with greater fidelity. Additionally, including pathology-free patient data from diverse sources ensures broader demographic representation and enhances the validity of the models. The detailed description and validation of the developed numerical models further distinguish this study, providing a robust foundation for understanding vascular haemorrhage pathmechanisms. However, it is crucial to acknowledge that this technique is still relatively new in the context of biomedical modelling and simulation. As such, there may be inherent limitations associated with SPH, including the need for further investigation to fully understand its accuracy and applicability in modelling cranial biomechanics [43; 44]. The results presented in this study should be considered as an original exploration of this approach, and further research should aim to validate and refine its use for more robust and accurate predictions. By recognising and addressing these limitations, we aim to facilitate future actions that can build upon our work and further advance the field of head biomechanics. The insights from the paper can inform preventive measures and interventions to reduce the occurrence and severity of subdural haematomas. Some possible strategies based on the research findings may include improving head protection devices, enhancing diagnostic techniques for early detection, and implementing lifestyle modifications or preventive measures tailored to individuals at higher risk [45; 46]. Overall, this research contributes to advancing knowledge in the field of head injury biomechanics and has the potential to improve patient outcomes and reduce the burden of subdural haematomas.