# A Review of Validation Methods for the Intracranial Response of FEHM to Blunt Impacts
## 5 Conclusions
Within the current environment, researchers should be encouraged to validate FEHM against sets of impacts from a range of studies using different data recording methods and response metrics, ideally including cadaver and in vivo references, and a covering a range of kinematic profiles likely to be relevant to the future applications of the FEHM to provide a balanced assessment its performance, and to mitigate the limitations and biases of particular empirical methods and data. As well as the experimental data available, this paper reviewed how validation is conducted in the simulation environment, specifically how impacts are recreated and how outputs are compared to empirical recordings. Impact replication has been largely, and increasingly with time, seen to be achieved by applying kinematics recorded during experimentation directly to the skull of the FEHM. While the skull needs to be modelled as rigid to use this method, its response can be validated in separate simulations, as has been done previously (e.g., by [PERSON] et al. [44]). Directly applying kinematics ensures the FEHM experiences exactly the same motion as the empirical sample, providing a consistent baseline during validation and removes boundary conditions from consideration, such as the inclusion of a neck which was seen to influence kinematic behaviour when other impact initiation methods were used [33]. If modelling the impactor is to be implemented, experimental procedures need to provide detailed information on impactor properties including materials, dimensions and boundary conditions to avoid the range of assumed representations seen in previous studies and to minimise the error introduced through the impactor/FEHM interaction. Assessing the validation performance of FEHM has been largely qualitative. It is clear quantitative assessment is essential to allow for objective conclusions to be drawn, especially when considering the effects of property changes within an FEHM type or the biofidelity of a given model, and therefore its suitability for use in injury research. A handful of measures have been considered for time-series based data. CORA was found to be the most suitable method for comparing output histories, allowing for magnitude, phase and shape characteristics of time-histories to be reliably compared [105] and has been recommended in relevant technical documentation [104] so should become widely adopted. Not all data are suited to this type of analysis. For example, the colour-plots of strain levels across brain slices widely presented from tagged MRI experimentation. Currently, these image-based outputs rely on qualitative assessment. However, this can be supplemented with quantitative analysis of extracted time-based data, including strain-histories at discrete points (e.g., Figure 10) and the area fraction of the brain experiencing strains above given thresholds against time (e.g., Figure 7). FEHM are incredibly valuable tools in numerous research areas. Their development and validation is, however, far from simple. This review has found there is scope to improve the validation procedures in a number of ways. Models can, however, be reasonably investigated and judged before being applied to research. Particularly in terms of how simulations are generated and outputs are assessed, simple selections can move validation procedures towards best practices within the realms of what is currently available and established. A good understanding of the intended applications of the FEHM being validated and the characteristics of each experimental method should help researchers choose impact scenarios for validation. While there is no clear best set of cases, variety is likely to provide the most reliable outcomes. (CfediT) K.M. : Methodology, Formal Analysis, Investigation, Data Curation, Writing -- Original Draft, Writing -- Review & Editing, Visualisation. F.T.-D.: Formal Analysis, Writing -- Review & Editing, Supervision, Resources. A.C.: Formal Analysis, Writing -- Review & Editing, Supervision.