Sub-Concussive Impact Analysis in Collegiate Football Athletes

Contact athletes are at a significantly elevated risk of experiencing sub-concussive impacts—those that do not reach the threshold to cause typical concussion symptoms but may still contribute to long-term neurological damage (Johnson et al., 2014). Current literature suggests that repeated exposure to these impacts may be linked to neurodegeneration, potentially resulting in long-term cognitive deficits and neurodegenerative disorders in this group (Stern et al., 2011). Previous research has relied on helmet accelerometers to detect and quantify the magnitude of these impacts by measuring peak linear acceleration and peak rotational velocity(Champagne et al., 2019). However, numerous studies have revealed that helmet-mounted accelerometers often overestimate both the acceleration and the severity of impacts, leading to inaccuracies in data collection (Camarillo et al., 2013, Greybe et al., 2020, O’Connor et al., 2017). To overcome this limitation, we hypothesize that acceleration measurements obtained from mouthguard accelerometers will show significantly lower peak linear and rotational accelerations compared to helmet-mounted accelerometers when measuring impacts over the same duration in Queen's University Football players. Each participating player will be fitted with a custom boil-and-bite mouthguard accelerometer engineered by Prevent Biometrics, ensuring a closer coupling to the skull for enhanced measurement accuracy. The players will wear these mouthguards throughout training camp and the season, with each impact exceeding a 15-g threshold validated through video analysis. We expect that the study’s findings will include lower recorded peak linear velocity, peak rotational velocity and more frequent sub-concussive exposure due to the increased sensitivity of the device. These findings will support the current literature that mouthguard accelerometers offer an accurate representation of the forces experienced by athletes. These findings will contribute to the growing body of knowledge on sub-concussive exposure in football players. The research has the potential to identify high-risk hitting patterns and influence new protocols for concussion management. Ultimately, this could increase player safety and promote healthier athletic development across all levels of competition. References: Camarillo, D. B., Shull, P. B., Mattson, J., Shultz, R., & Garza, D. (2013). An Instrumented Mouthguard for Measuring Linear and Angular Head Impact Kinematics in American Football. Annals of Biomedical Engineering, 41(9), 1939–1949. https://doi.org/10.1007/s10439-013-0801-y Champagne, A. A., Peponoulas, E., Terem, I., Ross, A., Tayebi, M., Chen, Y., Coverdale, N. S., Nielsen, P. M. F., Wang, A., Shim, V., Holdsworth, S. J., & Cook, D. J. (2019). Novel strain analysis informs about injury susceptibility of the corpus callosum to repeated impacts. Brain Communications, 1(1), fcz021. https://doi.org/10.1093/braincomms/fcz021 Greybe, D. G., Jones, C. M., Brown, M. R., & Williams, E. M. P. (2020). Comparison of head impact measurements via an instrumented mouthguard and an anthropometric testing device. Sports Engineering, 23(1), 12. https://doi.org/10.1007/s12283-020-00324-z Johnson, B., Neuberger, T., Gay, M., Hallett, M., & Slobounov, S. (2014). Effects of Subconcussive Head Trauma on the Default Mode Network of the Brain. Journal of Neurotrauma, 31(23), 1907–1913. https://doi.org/10.1089/neu.2014.3415 O’Connor, K. L., Rowson, S., Duma, S. M., & Broglio, S. P. (2017). Head-Impact–Measurement Devices: A Systematic Review. Journal of Athletic Training, 52(3), 206–227. https://doi.org/10.4085/1062-6050.52.2.05 Stern, R. A., Riley, D. O., Daneshvar, D. H., Nowinski, C. J., Cantu, R. C., & McKee, A. C. (2011). Long-term Consequences of Repetitive Brain Trauma: Chronic Traumatic Encephalopathy. PM&R, 3(10S2), S460–S467. https://doi.org/10.1016/j.pmrj.2011.08.008