Sports-related traumatic brain injuries (TBIs) are among the leading causes of head injuries in the world. Use of helmets is the main protective measure against this epidemic. The design criteria for the majority of the helmets often only consider the kinematics of the head. This approach neglects the importance of regional deformations of the brain especially near the deep white matter structures such as the corpus callosum (CC) which have been implicated in mTBI studies. In this work, we develop a dynamical reduced-order model of the skull-brain-helmet system to analyze the effect of various helmet parameters on the dynamics of the head and CC. Here, we show that the optimal head–helmet coupling values that minimize the CC dynamics are different from the ones that minimize the skull and brain dynamics (at some kinematics, up to two times stiffer for the head motion mitigation). By comparing our results with experimental impact tests performed on seven different helmets for five different sports, we found that the football helmets with an absorption of about 65–75% of the impact energy had the best performance in mitigating the head motion. Here, we found that none of the helmets are effective in protecting the CC from harmful impact energies. Our computational results reveal that the origin of the difference between the properties of a helmet mitigating the CC motion vs. the head motion is nonlinear vs. linear dynamics. Unlike the globally linear behavior of the head dynamics, we demonstrate that the CC exhibits nonlinear mechanical response similar to an energy sink. This means that there are scenarios where, at the instant of impact, the CC does not undergo extreme motions, but these may occur with a time delay as it absorbs shock energy from other parts of the brain. These findings hint at the importance of considering tissue level dynamics in designing new helmets.
This is a preview of subscription content, log in via an institution to check access.
Access this article Subscribe and saveSpringer+ Basic
€34.99 /Month
Price includes VAT (Germany)
Instant access to the full article PDF.
Similar content being viewed by others Explore related subjectsDiscover the latest articles and news from researchers in related subjects, suggested using machine learning. ReferencesAbderezaei, J., W. Zhao, C. L. Grijalva, et al. Nonlinear dynamical behavior of the deep white matter during head impact. Phys. Rev. Appl. 12:014058, 2019.
Andena, L., F. Caimmi, L. Leonardi, et al. Towards safer helmets: characterisation, modelling and monitoring. Procedia Eng. 147:478–483, 2016.
Bailey, A. M., E. J. Sanchez, G. Park, et al. Development and evaluation of a test method for assessing the performance of American football helmets. Ann. Biomed. Eng. 48:2566–2579, 2020.
Bailly, N., Y. Petit, J.-M. Desrosier, et al. Strain rate dependent behavior of vinyl nitrile helmet foam in compression and combined compression and shear. Appl. Sci. 10:8286, 2020.
Bazarian, J. J., T. Zhu, J. Zhong, et al. Persistent, long-term cerebral white matter changes after sports-related repetitive head impacts. PLoS ONE. 9:e94734, 2014.
Beckwith, J. G., J. J. Chu, and R. M. Greenwald. Validation of a noninvasive system for measuring head acceleration for use during boxing competition. J. Appl. Biomech. 23:238, 2007.
Beckwith, J. G., R. M. Greenwald, and J. J. Chu. Measuring head kinematics in football: correlation between the head impact telemetry system and Hybrid III headform. Ann. Biomed. Eng. 40:237–248, 2012.
Bland, M. L., C. McNally, and S. Rowson. Differences in impact performance of bicycle helmets during oblique impacts. J Biomech Eng. 2018. https://doi.org/10.1115/1.4040019.
Bland, M. L., C. McNally, D. S. Zuby, et al. Development of the STAR evaluation system for assessing bicycle helmet protective performance. Ann. Biomed. Eng. 48:47–57, 2020.
Bliven, E., A. Rouhier, S. Tsai, et al. Evaluation of a novel bicycle helmet concept in oblique impact testing. Accid. Anal. Prev. 124:58–65, 2019.
Buck, P. W. Mild traumatic brain injury: a silent epidemic in our practices. Health Soc. Work. 36:299–302, 2011.
Caccese, V., J. Ferguson, J. Lloyd, et al. Response of an impact test apparatus for fall protective headgear testing using a Hybrid-III head/neck assembly. Exp. Techn. 40:413–427, 2016.
Clark, J. M., T. B. Hoshizaki, A. N. Annaidh, et al. Equestrian helmet standards: do they represent real-world accident conditions? Ann. Biomed. Eng. 2020. https://doi.org/10.1007/s10439-020-02531-y.
Coats, B., S. A. Eucker, S. Sullivan, et al. Finite element model predictions of intracranial hemorrhage from non-impact, rapid head rotations in the piglet. Int. J. Dev. Neurosci. 30:191–200, 2012.
Cobb, B. R., A. M. Zadnik, and S. Rowson. Comparative analysis of helmeted impact response of Hybrid III and National Operating Committee on Standards for Athletic Equipment headforms. Proc. Inst. Mech. Eng. Part P J. Sports Eng. Technol. 230:50–60, 2016.
Eppinger, R., M. Kleinberger, and S. Kuppa et al: Development of improved injury criteria for the assessment of advanced automotive restraint systems, 1998.
Fernandes, F. A., R. J. Alves de Sousa, M. Ptak, et al. Helmet design based on the optimization of biocomposite energy-absorbing liners under multi-impact loading. Appl. Sci. 9:735, 2019.
Funk, J. R., R. Jadischke, A. Bailey, et al. Laboratory reconstructions of concussive helmet-to-helmet impacts in the national football league. Ann. Biomed. Eng. 48:2652–2666, 2020.
Gabler, L. F., J. R. Crandall, and M. B. Panzer. Development of a second-order system for rapid estimation of maximum brain strain. Ann. Biomed. Eng. 47:1971–1981, 2019.
Gadd, C. W. Use of a weighted-impulse criterion for estimating injury hazard. In: Vol SAE Technical Paper, 1966.
Ghazi, K., S. Wu, W. Zhao, et al. Instantaneous whole-brain strain estimation in dynamic head impact. J. Neurotrauma. 38:1023–1035, 2021.
Giudice, J. S., A. Caudillo, S. Mukherjee, et al. Finite element model of a deformable American football helmet under impact. Ann. Biomed. Eng. 48:1524–1539, 2020.
Gurdjian, E. S., V. R. Hodgson, L. M. Thomas, et al. Significance of relative movements of scalp, skull, and intracranial contents during impact injury of the head. J. Neurosurg. 29:70, 1968.
Hansen, K., N. Dau, F. Feist, et al. Angular Impact Mitigation system for bicycle helmets to reduce head acceleration and risk of traumatic brain injury. Accid. Anal. Prev. 59:109–117, 2013.
Harmon, K. G., J. Drezner, M. Gammons, et al. American Medical Society for Sports Medicine position statement: concussion in sport. Clin. J. Sport Med. 23:1–18, 2013.
Hernandez, F., L. C. Wu, M. C. Yip, et al. Six degree-of-freedom measurements of human mild traumatic brain injury. Ann. Biomed. Eng. 43:1918–1934, 2015.
Hinton-Bayre, A. D., G. Geffen, and P. Friis. Presentation and mechanisms of concussion in professional Rugby League football. J. Sci. Med. Sport. 7:400–404, 2004.
Holbourn, A. H. S. Mechanics of head injuries. Lancet. 242:438–441, 1943.
Hulkower, M. B., D. B. Poliak, S. B. Rosenbaum, et al. A decade of DTI in traumatic brain injury: 10 years and 100 articles later. Am. J. Neuroradiol. 34:2064–2074, 2013.
Kimpara, H., and M. Iwamoto. Mild traumatic brain injury predictors based on angular accelerations during impacts. Ann. Biomed. Eng. 40:114–126, 2012.
Kleiven, S. Evaluation of head injury criteria using a finite element model validated against experiments on localized brain motion, intracerebral acceleration, and intracranial pressure. Int. J. Crashworthiness. 11:65–79, 2006.
Kleiven, S. Predictors for traumatic brain injuries evaluated through accident reconstructions. The Stapp Association, 2007.
KrzeminskI, D. E., J. T. Goetz, A. P. Janisse, et al. Investigation of linear impact energy management and product claims of a novel American football helmet liner component. Sports Technol. 4:65–76, 2011.
Kumar, R., R. K. Gupta, M. Husain, et al. Comparative evaluation of corpus callosum DTI metrics in acute mild and moderate traumatic brain injury: its correlation with neuropsychometric tests. Brain Injury. 23:675–685, 2009.
Laksari, K., M. Kurt, H. Babaee, et al. Mechanistic insights into human brain impact dynamics through modal analysis. Phys. Rev. Lett. 120:138101, 2018.
Laksari, K., L. C. Wu, M. Kurt, et al. Resonance of human brain under head acceleration. J. R. Soc. Interface. 12:20150331, 2015.
Langlois, J. A., W. Rutland-Brown, and M. M. Wald. The epidemiology and impact of traumatic brain injury: a brief overview. J. Head Trauma Rehabil. 21:375–378, 2006.
Margulies, S. S., and L. E. Thibault. A proposed tolerance criterion for diffuse axonal injury in man. J. Biomech. 25:917–923, 1992.
McAllister, T. W., J. C. Ford, S. Ji, et al. Maximum principal strain and strain rate associated with concussion diagnosis correlates with changes in corpus callosum white matter indices. Ann. Biomed. Eng. 40:127–140, 2012.
McIntosh, A. S., K. Curtis, T. Rankin, et al. Associations between helmet use and brain injuries amongst injured pedal-and motor-cyclists: a case series analysis of trauma centre presentations. J. Austral. Coll. Road Saf. 24:11, 2013.
Mojahed, A., J. Abderezaei, M. Kurt, et al. A nonlinear reduced-order model of the corpus callosum under planar coronal excitation. J. Biomech Eng. 2020. https://doi.org/10.1115/1.4046503.
Ommaya, A. K., F. Faas, and P. Yarnell. Whiplash injury and brain damage: an experimental study. JAMA. 204:285–289, 1968.
Ommaya, A. K., and A. E. Hirsch. Tolerances for cerebral concussion from head impact and whiplash in primates. J. Biomech. 4:13–21, 1971.
Ouckama, R. and D. Pearsall. Projectile impact testing of ice hockey helmets: headform kinematics and dynamic measurement of localized pressure distribution. Proceedings, IRCOBI conference, 2014
Ramirez, B. J., and V. Gupta. Evaluation of novel temperature-stable viscoelastic polyurea foams as helmet liner materials. Mater. Des. 137:298–304, 2018.
Rowson, S., S. M. Duma, J. G. Beckwith, et al. Rotational head kinematics in football impacts: an injury risk function for concussion. Ann. Biomed. Eng. 40:1–13, 2012.
Rowson, B., S. Rowson, and S. M. Duma. Hockey STAR: a methodology for assessing the biomechanical performance of hockey helmets. Ann. Biomed. Eng. 43:2429–2443, 2015.
Shafiee, A., M. T. Ahmadian, H. Hoursan, et al. Effect of linear and rotational acceleration on human brain. Modares Mech. Eng. 15:248–260, 2015.
Smith, D. H., M. Nonaka, R. Miller, et al. Immediate coma following inertial brain injury dependent on axonal damage in the brainstem. J. Neurosurg. 93:315, 2000.
Sproule, D. W., E. T. Campolettano, and S. Rowson. Football helmet impact standards in relation to on-field impacts. Proc. Inst. Mech. Eng. Part P J. Sports Eng. Technol. 231:317–323, 2017.
Sullivan, S., S. A. Eucker, D. Gabrieli, et al. White matter tract-oriented deformation predicts traumatic axonal brain injury and reveals rotational direction-specific vulnerabilities. Biomech. Model. Mechanobiol. 14:877–896, 2015.
Tt, M., A. Ne, L. Be, et al. Functionally-detected cognitive impairment in high school football players without clinically-diagnosed concussion. J. Neurotrauma. 31:327–338, 2014.
Vakakis, A. F., O. V. Gendelman, L. A. Bergman, et al. Nonlinear Targeted Energy Transfer in Mechanical and Structural Systems. Dordrecht: Springer, 2008.
Ward, C., M. Chan, and A. Nahum. Intracranial pressure—a brain injury criterion. SAE Trans. 89:3867–3880, 1980.
Wu, T., A. Alshareef, J. S. Giudice, et al. Explicit modeling of white matter axonal fiber tracts in a finite element brain model. Ann. Biomed. Eng. 47:1908–1922, 2019.
Wu, S., W. Zhao, K. Ghazi, et al. Convolutional neural network for efficient estimation of regional brain strains. Sci. Rep. 9:17326, 2019.
Zhang, K., B. Johnson, D. Pennell, et al. Are functional deficits in concussed individuals consistent with white matter structural alterations: combined FMRI & DTI study. Exp. Brain Res. 204:57–70, 2010.
This work was supported in part by National Science Foundation Grant No. CMMI-17-1727761 and CMMI-17-1728186. Any opinions, findings, and conclusions or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Author information Author notesAlireza Mojahed
Present address: Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
Alireza Mojahed and Javid Abderezaei contributed equally in preparing this article.
Department of Mechanical Science and Engineering, University of Illinois, Urbana, IL, 61801, USA
Alireza Mojahed & Alexander Vakakis
Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ, 07030, USA
Javid Abderezaei & Efe Ozkaya
Department of Aerospace Engineering, University of Illinois, Urbana, IL, 61801, USA
Lawrence Bergman
Icahn School of Medicine at Mount Sinai, Biomedical Engineering and Imaging Institute Imaging Institute, New York, NY, 10029, USA
Mehmet Kurt
Department of Mechanical Engineering, University of Washington, Seattle, WA, 98115, USA
Javid Abderezaei & Mehmet Kurt
Correspondence to Alireza Mojahed.
Additional informationAssociate Editor Stefan M. Duma oversaw the review of this article.
Publisher's NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary InformationBelow is the link to the electronic supplementary material.
Appendix Appendix Experimental Impact amplitude–Duration Relation for Various HelmetsIn Fig. 4, we showed the variation of the optimal helmet-head coupling stiffness (based on minimization of either head, brain or the CC strain) as a function of duration and amplitude of the impact applied to the head. Moreover, for the sake of brevity, we superimposed the experimental impact amplitude-relation resulted from several impact tests done only on a football and a cycling helmet. Here, in Fig. 6, we depict Fig. 4, but with all tested helmets superimposed on the optimal \({\kappa }_{\text{h}}\) contours.
Figure 6Optimal head–helmet coupling, \({\kappa }_{\text{h}}\), minimizing the maximum strain of (a) the CC (\({\kappa }_{\text{h}}^{\text{CC}}\)), and (b) the head (\({\kappa }_{\text{h}}^{\text{h}}\)), (c) the brain (\({\kappa }_{\text{h}}^{\text{b}}\)), and (d) the ratio between the contour of (c) and (a), over a range of rotational acceleration amplitudes and durations.
When comparing (a) and (c) with (b), we observed that while the optimal \({\kappa }_{h}\) based on the brain, \({\kappa }_{\text{h}}^{\text{b}}\), and the CC strain, \({\kappa }_{\text{h}}^{\text{CC}}\), are dependent on both the excitation amplitude and duration, the optimal \({\kappa }_{\text{h}}\) based on the head motion, \({\kappa }_{\text{h}}^{\text{h}}\), is only sensitive to the impact duration and not the amplitude. Interestingly, our measured optimal \({\kappa }_{\text{h}}\) for these brain regions observed in (a) and (c), topologically align with the iso-strain curves computed by Ref. 38, hinting at a physical correspondence between the change of the optimal helmet-head coupling stiffness value as the brain strain level changes. Comparison of the helmet experiments in (a) and (c) with (b) also shows that the current helmet designs, with kinematics aligned nearly vertically for different impact energies, are either based on linear dynamics assumptions or merely the head motion. (The hatched regions in (a), (c) and (d) correspond to scenarios where nontrivial optimal \({\kappa }_{\text{h}}\) was not found and the algorithm converged to the trivial minimum, which is extremely soft helmet-head coupling to avoid transferring energy from helmet to brain). Figure 6 better illustrates that the impact amplitude–duration relation for all the helmets except football align vertically, which correlates with the contour A1b. This further confirms that most of helmets are designed to minimize the strain of the head rather than the brain or any of its substructures.
About this article Cite this articleMojahed, A., Abderezaei, J., Ozkaya, E. et al. Predictive Helmet Optimization Framework Based on Reduced-Order Modeling of the Brain Dynamics. Ann Biomed Eng 50, 1661–1673 (2022). https://doi.org/10.1007/s10439-022-02908-1
Received: 14 June 2021
Accepted: 01 January 2022
Published: 25 January 2022
Issue Date: November 2022
DOI: https://doi.org/10.1007/s10439-022-02908-1
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4