Traumatic brain injuries constitute a significant portion of injury resulting from automotive collisions, motorcycle crashes, and sports collisions. Brain injuries not only represent a serious trauma for those involved but also place an enormous burden on society, often exacting a heavy economical, social, and emotional price. Development of intervention strategies to prevent or minimize these injuries requires a complete understanding of injury mechanisms, response and tolerance level. In this study, an attempt is made to delineate actual injury causation and establish a meaningful injury criterion through the use of the actual field accident data. Twenty-four head-to-head field collisions that occurred in professional football games were duplicated using a validated finite element human head model. The injury predictors and injury levels were analyzed based on resulting brain tissue responses and were correlated with the site and occurrence of mild traumatic brain injury (MTBI). Predictions indicated that the shear stress around the brainstem region could be an injury predictor for concussion. Statistical analyses were performed to establish the new brain injury tolerance level.

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To test the hypothesis that appropriate and timely neuromuscular control of limb motions plays an important role in the preservation of joint health, we kinematically and kinetically examined the behavior of the legs of young adult subjects at heel strike during natural walking. We compared a group of 18 volunteers, who, we presumed, were preosteoarthrotic because of mild, intermittent, activity-related knee joint pain, with 14 age-matched asymptomatic normal subjects. The two groups of subjects exhibited similar gait patterns with equivalent cadences, walking speeds, terminal stance phase knee flexion, maximum (peak) swing angular velocity, and overall shape of the vertical ground reaction. However, our instrumentation detected statistically significant differences between the two groups within a few milliseconds of heel strike. In the knee pain group, the heel hit the floor with a stronger impact in this brief interval. Just before heel strike, there was a faster downward velocity of the ankle with a larger angular velocity of the shank. The follow-through of the leg immediately after heel strike was more violent with larger peak axial and angular accelerations of the leg echoed by a more rapid rise of the ground reaction force. This sequence of events represents repetitive impulsive loading, which consistently provoked osteoarthrosis in animal experiments. We refer to this micro-incoordination of neuromuscular control not visible to the naked eye as "microklutziness."

This study is aimed to develop a high quality, extensively validated finite element (FE) human head model for enhanced head injury prediction and prevention. The geometry of the model was based on computed tomography (CT) and magnetic resonance imaging scans of an adult male who has the average height and weight of an American. A feature-based multiblock technique was adopted to develop hexahedral brain meshes including the cerebrum, cerebellum, brainstem, corpus callosum, ventricles, and thalamus. Conventional meshing methods were used to create the bridging veins, cerebrospinal fluid, skull, facial bones, flesh, skin, and membranes-including falx, tentorium, pia, arachnoid, and dura. The head model has 270,552 elements in total. Thirty five loading cases were selected from a range of experimental head impacts to check the robustness of the model predictions based on responses including the brain pressure, relative skull-brain motion, skull response, and facial response. The brain pressure was validated against intracranial pressure data reported by Nahum et al. (1977, "Intracranial Pressure Dynamics During Head Impact," Proc. 21st Stapp Car Crash Conference, SAE Technical Paper No. 770922) and Trosseille et al. (1992, "Development of a F.E.M. of the Human Head According to a Specific Test Protocol," Proc. 36th Stapp Car Crash Conference, SAE Technical Paper No. 922527). The brain motion was validated against brain displacements under sagittal, coronal, and horizontal blunt impacts performed by Hardy et al. (2001, "Investigation of Head Injury Mechanisms Using Neutral Density Technology and High-Speed Biplanar X-Ray," Stapp Car Crash Journal, 45, pp. 337-368; and 2007, "A Study of the Response of the Human Cadaver Head to Impact," Stapp Car Crash Journal, 51, pp. 17-80). The facial bone responses were validated under nasal impact (Nyquist et al. 1986, "Facial Impact Tolerance and Response," Proc. 30th Stapp Car Crash Conference, SAE Technical Paper No. 861896), zygoma and maxilla impact (Allsop et al. 1988, "Facial Impact Response - A Comparison of the Hybrid III Dummy and Human Cadaver," Proc. 32nd Stapp Car Crash Conference, SAE Technical Paper No. 881719)]. The skull bones were validated under frontal angled impact, vertical impact, and occipital impact (Yoganandan et al. 1995, "Biomechanics of Skull Fracture," J Neurotrauma, 12(4), pp. 659-668) and frontal horizontal impact (Hodgson et al. 1970, "Fracture Behavior of the Skull Frontal Bone Against Cylindrical Surfaces," 14th Stapp Car Crash Conference, SAE International, Warrendale, PA). The FE head model was further used to study injury mechanisms and tolerances for brain contusion (Nahum et al. 1976, "An Experimental Model for Closed Head Impact Injury," 20th Stapp Car Crash Conference, SAE International, Warrendale, PA). Studies from 35 loading cases demonstrated that the FE head model could predict head responses which were comparable to experimental measurements in terms of pattern, peak values, or time histories. Furthermore, tissue-level injury tolera...

Finite element modeling showed the largest brain deformations occurred after the primary head acceleration. Midbrain strain correlated with memory and cognitive problems and removal from play after concussion. Concussion injuries happen during the rapid displacement and rotation of the cranium, after peak head acceleration and momentum transfer in helmet impacts.

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This study was conducted to investigate differences in brain response due to frontal and lateral impacts based on a partially validated three-dimensional finite element model with all essential anatomical features of a human head. Identical impact and boundary conditions were used for both the frontal and lateral impact simulations. Intracranial pressure and localized shear stress distributions predicted from these impacts were analyzed. The model predicted higher positive pressures accompanied by a relatively large localized skull deformation at the impact site from a lateral impact when compared to a frontal impact. Lateral impact also induced higher localized shear stress in the core regions of the brain. Preliminary results of the simulation suggest that skull deformation and internal partitions may be responsible for the directional sensitivity of the head in terms of intracranial pressure and shear stress response. In previous experimental studies using subhuman primates, it was found that a lateral impact was more injurious than a frontal impact. In this study, shear stress in the brain predicted by the model was much higher in a lateral impact in comparison with a frontal impact of the same severity. If shear deformation is considered as an injury indicator for diffuse brain injuries, a higher shear stress due to a lateral impact indicate that the head would tend to have a decreased tolerance to shear deformation in lateral impact. More research is needed to further quantify the effect of the skull deformation and dural partitions on brain injury due to impacts from a variety of directions and at different locations.