Motor vehicle crashes are the most common cause of serious head injury (Healthy People, 2002). Over the past decade, improvements to seat belts and frontal airbags have reduced the incidence and severity of injuries sustained in frontal crashes, but are less effective in side impact crashes.

Prior studies have shown that both excessive linear and rotational accelerations are the cause of head injury. Although the Head Injury Criteria (HIC) has been beneficial as an indicator of head injury risk, it only considers linear acceleration only.

With the rapid increase in computational power, advanced models of the head/brain complex have been developed in order to gain a better understanding of head injury biomechanics. While these models have been verified against laboratory experimental data, there is a lack of suitable realworld data available for validation. Hence, the objective of the current study is to use real-world data to predict injury outcomes using computer models of the head, and to validate the model results against the actual injuries sustained in two real-world crashes. Two computer models of the head were used:​ The Wayne State University Head Injury Model (WSUHIM) and the NHTSA Simulated Injury Monitor (SIMon). The HIC was also calculated for comparision.

The use of computer models of the brain provide a useful tool for the prediction of brain injury in motor vehicle crashes and may be able to replace criteria such as the HIC in the future.