Simulation Evaluation of a Liquid Football Helmet under Concussive and Subconcussive Impact Loading

Introduction:: Concern has grown over the potential long-term effects of repeated head impacts and concussions in sports. American football, in particular, presents a significant risk of subconcussive head impact exposure and diagnosed concussions relative to other contact sports. An ideal helmet shock absorber would perform optimally across the entire range of impact velocities that an athlete is exposed to, inclusive of both concussive and subconcussive impacts. Recent advances in impact engineering have yielded the development of soft, collapsible, liquid shock absorbers, which have demonstrated the ability to adapt to a wide range of impact velocities and dramatically attenuate impact forces relative to current shock absorbing technologies. Use of finite element (FE) modeling can reduce cost, time, and difficulty in bringing new helmet technologies to market and aid in identifying the most promising technologies to prevent brain injury. To further explore how liquid shock absorbers can improve the efficacy of helmets for American football, we developed and optimized a FE helmet model including liquid shock absorbers spread out throughout the helmet. We then evaluated the FE helmet model for its efficacy in attenuating impact severity at velocities representative of subconcussive and concussive football impacts.


Materials and Methods:: A cylindrical liquid shock absorber inspired by Vahid Alizadeh et al. (2022) was modeled for integration into a football helmet. During impact, the top surface of the shock absorber is pressed downwards, and the liquid inside is forced to flow through an orifice, thus decelerating the impacting mass. A previously validated FE helmet model (Giudice et al., 2020) was used as the base model for a full helmet, which we modified by integrating 21 liquid shock absorbers.



The liquid helmet was tested according to the NFL’s Helmet Test Protocol using a FE model of a linear impactor and Hybrid III headform (Giudice et al., 2019). This included three impact velocities representative of concussive impacts (5.5, 7.4, 9.3 m/s) and six impact locations. Three additional velocities were tested to explore efficacy for subconcussive impacts (1.6, 3.4, 5.0 m/s). Four previously created football helmet FE models were also tested.



Head Acceleration Response Metric (HARM) was calculated for all impacts. The percentage reduction in HARM afforded by the liquid helmet relative to each existing helmet was calculated. Helmet Performance Score was calculated for each helmet using a weighted sum of HARM values from the concussive tests (Bailey et al., 2020).



The GHBMC head and brain model was used to calculate brain strain for each impact. The head kinematics were assigned to the model skull as the loading to deform brain tissue, and the 95th percentile maximum principal strain (MPS95) across the whole brain was recorded.


Results, Conclusions, and Discussions:: Overall, the liquid helmet yielded the lowest Helmet Performance Score (0.71), compared to the other four helmet models (VICIS = 1.07, Riddell = 1.10, Schutt = 1.21, Xenith = 1.15). The liquid helmet yielded the lowest value of HARM at 33 of the 36 tested impact conditions, with 3 velocities at the Facemask Central Oblique location being the only conditions in which the liquid design did not outperform all of the existing helmet models. Relative to all helmet models, HARM reductions afforded by the liquid helmet averaged 32.0% (range: -2.2% to 50.5%) at concussive velocity impact cases and averaged 33.0% (range: -37.5% to 56.0%) at subconcussive velocity impact cases.



Helmet Performance Score is the primary helmet safety metric for the NFL, and it is used to create an annual public ranking of helmets. Helmet Performance Score may be a meaningful metric to consider when attempting to reduce injury incidence on the field; a recent study found that Helmet Performance Score calculated from laboratory tests of helmets was associated with on-field concussion incidence in NFL game play (Bailey et al., 2020b).



Using the GHBMC FE model, Wu et al. (2022) proposed a 50% risk threshold for mild traumatic brain injury of 0.360 MPS95. Eleven of the concussive NFL impact conditions resulted in all four of the existing FE helmet models exceeding this threshold, while the liquid helmet only resulted in an MPS95 value of 0.360 or greater in five.

Overall, the present study proposes an architecture for a full helmet featuring liquid shock absorbers. The results of FE simulations with this helmet and other helmets suggest that liquid technology has the potential to lower the risk of football-related brain injury by attenuating kinematics-based brain injury criteria and brain strains across a wide range of impact velocities. These findings support the fabrication of helmets featuring liquid shock absorbers to validate simulation results.


Acknowledgements (Optional): :

References (Optional): : Bailey, A.M., McMurry, T.L., Cormier, J.M., Funk, J.R., Crandall, J.R., Mack, C.D., Myers, B.S. and Arbogast, K.B., 2020. Comparison of laboratory and on-field performance of American football helmets. Annals of biomedical engineering, 48, pp.2531-2541.



Bailey, A.M., Sanchez, E.J., Park, G., Gabler, L.F., Funk, J.R., Crandall, J.R., Wonnacott, M., Withnall, C., Myers, B.S. and Arbogast, K.B., 2020. Development and evaluation of a test method for assessing the performance of American football helmets. Annals of biomedical engineering, 48, pp.2566-2579.


Giudice, J.S., Caudillo, A., Mukherjee, S., Kong, K., Park, G., Kent, R. and Panzer, M.B., 2020. Finite element model of a deformable American football helmet under impact. Annals of biomedical engineering, 48, pp.1524-1539.

Giudice, J.S., Park, G., Kong, K., Bailey, A., Kent, R. and Panzer, M.B., 2019. Development of open-source dummy and impactor models for the assessment of American football helmet finite element models. Annals of biomedical engineering, 47, pp.464-474.



Vahid Alizadeh, H., Fanton, M. and Camarillo, D.B., 2022. Collapsible fluid-filled fabric shock absorber with constant force. Journal of Intelligent Material Systems and Structures, 33(4), pp.590-603.


Wu, T., Sato, F., Antona-Makoshi, J., Gabler, L.F., Giudice, J.S., Alshareef, A., Yaguchi, M., Masuda, M., Margulies, S.S. and Panzer, M.B., 2022. Integrating human and nonhuman primate data to estimate human tolerances for traumatic brain injury. Journal of biomechanical engineering, 144(7), p.071003.