Ice hockey is a sport with high velocities and a large number of impacts to the head. The high occurrence of concussions is being recognized, and both short and long term consequences have been found. As body checking is the main situation inducing concussions, often in the form of shoulder-to-face impacts, there is thought to be a potential to lowering the rates of concussions with equipment that covers the jaw and chin area. In this study, in-game videos from the Swedish Hockey League were analyzed regarding impact situations and impact locations. The most occurring impact situations were simulated with finite element simulation on a Hybrid-III 50th percentile head and neck model wearing a standard ice hockey helmet. Three jawguard designs were developed and tested with the model, and seven different attachments were tested on two of the designs. The results showed varying effect of the jawguard, depending on the impact situation. In impacts to the side of the chin, all three designs reduced the strains in the brain, by successfully reducing the axial rotation. In impacts to the side of the face/head and to the front of the chin, the jawguard designs produced higher strains in the brain than without any protection. The helmet in this study was attached to the head model with a chin cup, and this may have had a significant effect on the strains of the brain. Other limitations to the simulation set up indicates that the jawguards should be tested on a more realistic model to properly evaluate the jawguard.

INTRODUCTION. Frontal collisions have been observed to cause the severe injuries on heavy goods vehicle occupants, and the lower extremities have been frequently injured. Injuries of knee joints are rarely life threatening, however they tend to give long-term consequences. AIM. Evaluate non-lethal frontal impacts towards the knee joint of Total Human Model for Safety (THUMS) v4.0 using a cylindrical barrier. The main objectives are to 1) create local injury risk functions of the knee ligaments restraining frontal impacts, 2) simulate frontal impacts towards the knee joints of THUMS and3) prepare the Hybrid III (HIII)-model for corresponding frontal impacts conducted on THUMS. The intention is for future HIII-simulations to be cross-correlated with the responses from THUMS for the ability to estimate knee ligament strains by investigating impacts on HIII. METHODS. 1) Ligament risk curves of PCL, MCL and LCL were formulated by assembling mean strain threshold values and standard deviations from literature. Virtual values were generated from these pooled strain thresholds, creating the risk curves. 2) THUMS lower body was impacted by a cylindrical steel barrier at four different locations - middle of patella, middle of knee joint, upper tibia and below tibia tuberositas. Four impact velocities ranging from 8-14 km/h were used at each location, giving a total of 16 impacts. 3) The HIII-model was prepared by removing the upper body and inserting the cylindrical steel barrier into the model file. RESULTS. The strain threshold at 50% rupture risk for PCL resulted in 23.6±4.4%, 34.2±6.0% for MCL and 26.6±6.5% for LCL. The simulated THUMS PCL strains reached between 36%-58% for the highest velocity at the impact locations where tibia was involved. Both MCL and LCL gave an approximate 5% strain outcome. The resultant knee displacement for these impacts ranged between 22 mm - 32 mm. The knee displacements at the PCL strain threshold ranged between 14 mm - 16 mm. DISCUSSION and CONCLUSION. Most of the maximal PCL strains exceeded the PCL threshold with large margins. However, the knee displacement at the PCL strain threshold resulted in outcomes comparable to the thresholds used for HIIImodel. These results supported the obtained PCL threshold to be within a reasonable range.