dc.contributor.author | Bruneau, David | |
dc.contributor.author | Cronin, Duane | |
dc.date.accessioned | 2023-03-13 19:49:07 (GMT) | |
dc.date.available | 2023-03-13 19:49:07 (GMT) | |
dc.date.issued | 2021-03 | |
dc.identifier.uri | https://doi.org/10.1016/j.jmbbm.2020.104299 | |
dc.identifier.uri | http://hdl.handle.net/10012/19200 | |
dc.description | This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this article is published in the Journal of the Mechanical Behavior of Biomedical Materials, and is available online at https://doi.org/10.1016/j.jmbbm.2020.104299 | en |
dc.description.abstract | Computational human body models (HBM) present a novel approach to predict brain response
3 in football impact scenarios, with prescribed kinematic boundary conditions for the HBM skull
4 typically used at present. However, computational optimization of helmets requires simulation
5 of the coupled helmet and HBM model; which is much more complex and has not been assessed
6 in the context of brain deformation and existing simplified approaches. In the current study, two
7 boundary conditions and the resulting brain deformations were compared using a HBM head
8 model: (1) a prescribed skull kinematics (PK) boundary condition using measured head kinematics
9 from experimental impacts; and (2) a novel detailed simulation of a HBM head and neck, helmet
10 and linear impactor (HBM‐S). While lateral and rear impacts exhibited similar levels of maximum
11 principal strain (MPS) in the brain tissue using both boundary conditions, differences were noted
12 in the frontal orientation (at 9.3 m/s, MPS was 0.39 for PK, 0.54 for HBM‐S). Importantly, both PK
13 and HBM‐S boundary conditions produced a similar distribution of MPS throughout the brain for
14 each impact orientation considered. Within the corpus callosum and thalamus, high MPS was
15 associated with lateral impacts and lower values with frontal and rear impacts. The good
16 correspondence of both boundary conditions is encouraging for future optimization of helmet
17 designs. A limitation of the PK approach is the need for experimental head kinematics data, while
18 the HBM‐S can predict brain response for varying impact conditions and helmet configurations,
19 with potential as a tool to improve helmet protection performance. | en |
dc.description.sponsorship | The research presented was made possible by a grant from Football Research, Inc. (FRI), the National Football League (NFL), and Biomechanical Consulting and Research, LLC (Biocore) in the USA. | en |
dc.language.iso | en | en |
dc.publisher | Elsevier ScienceDirect | en |
dc.relation.ispartofseries | Journal of the Mechanical Behavior of Biomedical Materials;104299 | |
dc.subject | helmet protection | en |
dc.subject | human body model | en |
dc.subject | brain deformation | en |
dc.subject | anthropometric testing device | en |
dc.subject | 3 impact biomechanics | en |
dc.subject | concussion | en |
dc.subject | american football | en |
dc.title | Brain Response of a Computational Head Model for Prescribed Skull Kinematics and Simulated 3 Football Helmet Impact Boundary Conditions | en |
dc.type | Article | en |
dcterms.bibliographicCitation | Bruneau, D. A., & Cronin, D. S. (2021). Brain response of a computational head model for prescribed skull kinematics and simulated football helmet impact boundary conditions. Journal of the Mechanical Behavior of Biomedical Materials, 115, 104299. https://doi.org/10.1016/j.jmbbm.2020.104299 | en |
uws.contributor.affiliation1 | Faculty of Engineering | en |
uws.contributor.affiliation2 | Mechanical and Mechatronics Engineering | en |
uws.typeOfResource | Text | en |
uws.peerReviewStatus | Reviewed | en |
uws.scholarLevel | Faculty | en |