Hockey STAR: A Methodology for Assessing the Biomechanical Performance of Hockey Helmets

Abstract

Optimizing the protective capabilities of helmets is one of several methods of reducing brain injury risk in sports. This paper presents the experimental and analytical development of a hockey helmet evaluation methodology. The Summation of Tests for the Analysis of Risk (STAR) formula combines head impact exposure with brain injury probability over the broad range of 227 head impacts that a hockey player is likely to experience during one season. These impact exposure data are mapped to laboratory testing parameters using a series of 12 impact conditions comprised of three energy levels and four head impact locations, which include centric and non-centric directions of force. Injury risk is determined using a multivariate injury risk function that incorporates both linear and rotational head acceleration measurements. All testing parameters are presented along with exemplar helmet test data. The Hockey STAR methodology provides a scientific framework for manufacturers to optimize hockey helmet design for injury risk reduction, as well as providing consumers with a meaningful metric to assess the relative performance of hockey helmets.

Keywords: Acceleration; Concussion; Impact; Linear; Risk; Rotational.

Figure 1

The custom impact pendulum device was used to strike a NOCSAE headform mounted on a Hybrid III 50th percentile neck. The head and neck were mounted on a sliding mass that simulates the effective mass of the torso during impact. The slide table has 5 degrees of freedom so that any location on the helmet could be impacted: translation along the x axis, translation along the y axis, translation along the z axis, rotation about the y axis, and rotation about the z axis.

Figure 2

Photographs of the front, side, back, and top impact locations used to assess helmet performance. The side and top impact locations are non-centric, meaning the direction of force is not aligned with the CG of the headform; while the front and back impact locations are centric.

Figure 3

Peak linear and rotational head acceleration values generated during the pendulum tests are overlaid on the bivariate CDFs for each impact location. These plots relate laboratory impact energies to on-ice head impact data and were used to define head impact distributions as a function of impact energy. Where a given impact energy (pendulum arm angle) fell within the distributions varied by impact location. While these plots only illustrate this for male collegiate hockey, this was done for each of the 4 hockey player populations in which on-ice data were previously collected.

Figure 4

Impact energy CDFs for each impact location resulting from the transformation of on-ice data to laboratory impact conditions. The gray lines represent impact energy CDFs for each population and the black line is the equal-weight average of the four populations. The dashed red lines show the bounds used to determine the percentage of impacts at each location associated with the low, medium, and high energy impact conditions. This analysis was used to define the exposure weightings for each impact configuration in the Hockey STAR formula.

Figure 5

Average acceleration traces from the laboratory pendulum tests were compared to corridors developed from on-ice volunteer data by impact location. The head impact response of the laboratory tests closely matches that which was measured directly from hockey players, suggesting the impact system generates a biofidelic response.

Figure 6

Head impact responses generated in the lab were also compared to dummy head impacts collected at an ice rink. Here, average acceleration traces from the laboratory pendulum tests were compared to corridors developed from controlled dummy head impacts to the boards, glass, and ice at an ice rink. The head impact response of the laboratory tests closely matches that which was measured at the ice rink, which further suggests that impact system generates a biofidelic response.