Abstract
Due to growing concern on brain injury in sport, and the role that helmets could play in preventing brain injury caused by impact, biomechanics researchers and helmet certification organizations are discussing how helmet assessment methods might change to assess helmets based on impact parameters relevant to brain injury. To understand the relationship between kinematic measures and brain strain, we completed hundreds of impacts using a 50th percentile Hybrid III head-neck wearing an ice hockey helmet and input three-dimensional impact kinematics to a finite element brain model called the Simulated Injury Monitor (SIMon) (n = 267). Impacts to the helmet front, back and side included impact speeds from 1.2 to 5.8 ms−1. Linear regression models, compared through multiple regression techniques, calculating adjusted R2 and the F-statistic, determined the most efficient set of kinematics capable of predicting SIMon-computed brain strain, including the cumulative strain damage measure (specifically CSDM-15) and maximum principal strain (MPS). Resultant change in angular velocity, ΔωR, better predicted CSDM-15 and MPS than the current helmet certification metric, peak g, and was the most efficient model for predicting strain, regardless of impact location. In nearly all cases, the best two-variable model included peak resultant angular acceleration, αR, and ΔωR.
Highlights
Brain injuries, such as concussion, occur in hockey at rates up to 0.54 for high school,19 0.41–3.1 for col-legiate8,15 and 1.81 for professional,32 per 1000 exposures
The text in contemporary helmet standards generally does not include a rationale on the choice of attenuation metric, it is generally accepted that the choice of head acceleration is at least partially motivated by research on head injury biomechanics dating back to the 1950s and 1960s
The regression models that achieved the maximum F-statistic, maximum adjusted R2, and the best twovariable regression model are indicated in Tables 4, 5, and 6, respectively, presenting which variables were used to create each model based on impact location
Summary
Brain injuries, such as concussion, occur in hockey at rates up to 0.54 for high school,19 0.41–3.1 for col-legiate and 1.81 for professional, per 1000 exposures. Despite the widespread use of helmets, sport and recreation-related head injury remains the second most common cause of hospitalization for traumatic brain injury (TBI).. It is understood that helmet use mitigates the risk of severe focal head injury, the perceived increase in rates of sport-related brain injuries has led to increased research efforts examining the role of helmets in brain protection. Minimum helmet protective capacity is currently established through standard laboratory impact testing. Acceleration, or functionals using acceleration, establish helmet ability to attenuate impact. The text in contemporary helmet standards generally does not include a rationale on the choice of attenuation metric, it is generally accepted that the choice of head acceleration is at least partially motivated by research on head injury biomechanics dating back to the 1950s and 1960s.2
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