Assessment of brain injury biomechanics in soccer heading using finite element analysis

Perkins, Richard A., Bakhtiarydavijani, Amirhamed, Ivanoff, Athena E., Jones, Michael ORCID: https://orcid.org/0000-0002-6058-6029, Hammi, Youssef and Prabhu, Raj K. 2022. Assessment of brain injury biomechanics in soccer heading using finite element analysis. Brain Multiphysics 3 , 100052. 10.1016/j.brain.2022.100052

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Abstract

This study presents an in silico finite element (FE) model-based biomechanical analysis of brain injury metrics and associated risks of a soccer ball impact to the head for aware and unaware athletes, considering ball impact velocity and direction. The analysis presented herein implements a validated soccer ball and 50th percentile human head computational FE model for quantifying traumatic brain injury (TBI) metrics. The brain's mechanical properties are designated using a viscoelastic-viscoplastic constitutive material model for the white and gray matter within the human head FE model. FE results show a dynamic human head-soccer ball peak contact area of approximately seven times greater than those documented for helmet-to-helmet hits in American Football. Due to the deformable nature of the soccer ball, the impact dynamics are unique depending on the location and velocity of impact. TBI injury risks also depend on the location of impact and the impact velocity. Impacts to the rear (BrIC:0.48, HIC15:180.7), side (BrIC:0.52, HIC15:176.5), and front (BrIC:0.37, HIC15:129.0) are associated with the highest injury risks. Furthermore, the FE results indicate when an athlete is aware of an incoming ball, HIC15-based Abbreviated Injury Scale 1 (AIS 1) injury risks for the front, side, and rear impacts decrease from 10.5%, 18.5%, and 19.3%, respectively, to approximately 1% in front and side impacts and under 6% in a rear impact. Lastly, the unique contact area between the head and soccer ball produces pressure gradients in the ball that translate into distinguishable stress waves in the skull and the cerebral cortex.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by-nc-nd/4.0/, Start Date: 2022-08-04
Publisher:	Elsevier
ISSN:	2666-5220
Date of First Compliant Deposit:	15 August 2022
Last Modified:	05 May 2023 22:53
URI:	https://orca.cardiff.ac.uk/id/eprint/151953

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