Design of an optimally safe football helmet system requires an awareness and evaluation of the factors and variables that can adversely affect the impact attenuating performance of energy absorbing (EA) pad materials needed to minimize transmission of linear and rotational forces applied to the head so that risk of head injury is reduced. For instance, player head sweating can induce high temperatures and moisture within a helmet system (i.e. a Hot-Wet condition) which can result in degradation of helmet EA capacity and cause increased measures of head injury risk levels, which are often used for comparative evaluation of helmet designs.
In this study, a “multivariable” experimental method was utilized to demonstrate an efficient means for assessment and comparison of currently representative adult and youth football helmet system designs when subjected to a range of variables that included, among other factors: temperature-moisture effects; impact energy; and, repeat impacts. Both quasi-static (QS) compression testing of commonly used EA materials and dynamic impact testing of full helmet systems were conducted and the results are presented in Tables and graphic form.
The EA pad types that were QS tested included: Thermoplastic-Polyurethane (TPU) “waffle shaped” EA pad configurations; load rate sensitive “Gel” foam padding; and, dual and single density elastomeric foam padding. Dynamic helmet repeat impact tests were conducted by using a pendulum impact test device where various helmet designs were mounted to a Hybrid-III head and neck system and impacted against a non-yielding surface at energy levels of 108J and 130J after being subjected to ambient and Hot-Wet conditions.
The QS tests showed that a short Hot-Wet soak time of only a few hours’ noticeably diminished EA levels. Also, the dynamic full helmet system testing demonstrated that the “Hot-Wet” condition tended to degrade helmet impact attenuation performance such that, depending on the size and type of EA material provided in the crush zone, head injury risk measures tended to increase. Finally, examples of the use and benefits of a “multivariable” experimental method for helmet injury risk assessment, not reported on previously, are provided.