Incorporating neck biomechanics in helmet testing: Evaluation of commercially available WaveCel helmets

Evaluating Polo Helmet Performance Across Different Impact Test Systems

PURPOSE

This study evaluated head impact response between different helmet impact test systems by comparing the performance of ten polo helmets.

METHODS

Helmets were evaluated using three test systems: a twin-wire guided drop tower, an oblique drop tower, and an impact pendulum. Impact tests were conducted at matched locations (front boss, side, rear boss) and speeds (3.46, 5.46 m/s). We employed a linear mixed model with helmet model as a random effect and calculated the least square mean differences between systems for peak linear acceleration (PLA), peak rotational acceleration (PRA), peak rotational velocity (PRV), and concussion risk. Correlations between systems by impact speed were explored, using linear models of each system as a function of the others, and calculated Spearman rank correlation coefficients between test systems for each dependent variable.

RESULTS

Our results found distinct differences in PRA and concussion risk between the oblique and the pendulum impact systems due to the driving force. The acceleration range across helmet models was substantial, and responses differed between test systems at matched impact conditions. However, there were similarities between test systems in the rank order of helmet models. Head acceleration differences between helmets translated to larger differences in concussion risk between helmet models.

CONCLUSION

These trends provide a framework for comparing the headform's response across varying loading conditions. When selecting a test system to evaluate helmets for a specific sport, it is essential to consider the relevant impact conditions and loading patterns to ensure that laboratory tests accurately represent real-world scenarios.

Peaks and Distributions of White Matter Tract-related Strains in Bicycle Helmeted Impacts: Implication for Helmet Ranking and Optimization

Traumatic brain injury (TBI) in cyclists is a growing public health problem, with helmets being the major protection gear. Finite element head models have been increasingly used to engineer safer helmets often by mitigating brain strain peaks. However, how different helmets alter the spatial distribution of brain strain remains largely unknown. Besides, existing research primarily used maximum principal strain (MPS) as the injury parameter, while white matter fiber tract-related strains, increasingly recognized as effective predictors for TBI, have rarely been used for helmet evaluation. To address these research gaps, we used an anatomically detailed head model with embedded fiber tracts to simulate fifty-one helmeted impacts, encompassing seventeen bicycle helmets under three impact locations. We assessed the helmet performance based on four tract-related strains characterizing the normal and shear strain oriented along and perpendicular to the fiber tract, as well as the prevalently used MPS. Our results showed that both the helmet model and impact location affected the strain peaks. Interestingly, we noted that different helmets did not alter strain distribution, except for one helmet under one specific impact location. Moreover, our analyses revealed that helmet ranking outcome based on strain peaks was affected by the choice of injury metrics (Kendall's Tau coefficient: 0.58-0.93). Significant correlations were noted between tract-related strains and angular motion-based injury metrics. This study provided new insights into computational brain biomechanics and highlighted the helmet ranking outcome was dependent on the choice of injury metrics. Our results also hinted that the performance of helmets could be augmented by mitigating the strain peak and optimizing the strain distribution with accounting the selective vulnerability of brain subregions and more research was needed to develop region-specific injury criteria.

Human Head and Helmet Interface Friction Coefficients with Biological Sex and Hair Property Comparisons

Dummy headforms used for impact testing have changed little over the years, and frictional characteristics are thought not to represent the human head accurately. The frictional interface between the helmet and head is an essential factor affecting impact response. However, few studies have evaluated the coefficient of friction (COF) between the human head and helmet surface. This study's objectives were to quantify the human head's static and dynamic COF and evaluate the effect of biological sex and hair properties. Seventy-four participants slid their heads along a piece of helmet foam backed by a fixed load cell at varying normal force levels. As normal force increased, static and dynamic human head COF decreased following power-law curves. At 80 N, the static COF is 0.32 (95% CI 0.30-0.34), and the dynamic friction coefficient is 0.27 (95% CI 0.26-0.28). Biological sex and hair properties were determined not to affect human head COF. The COFs between the head and helmet surface should be used to develop more biofidelic head impact testing methods, define boundary conditions for computer simulations, and aid decision-making for helmet designs.

Evaluation of an Elastomeric Honeycomb Bicycle Helmet Design to Mitigate Head Kinematics in Oblique Impacts

Head impacts in bicycle accidents are typically oblique to the impact surface and transmit both normal and tangential forces to the head, causing linear and rotational head kinematics, respectively. Traditional expanded polystyrene (EPS) foam bicycle helmets are effective at preventing many head injuries, especially skull fractures and severe traumatic brain injuries (TBIs) (primarily from normal contact forces). However, the incidence of concussion from collisions (primarily from rotational head motion) remains high, indicating need for enhanced protection. An elastomeric honeycomb helmet design is proposed herein as an alternative to EPS foam to improve TBI protection and be potentially reusable for multiple impacts, and tested using a twin-wire drop tower. Small-scale normal and oblique impact tests showed honeycomb had lower oblique strength than EPS foam, beneficial for diffuse TBI protection by permitting greater shear deformation and had the potential to be reusable. Honeycomb helmets were developed based on the geometry of an existing EPS foam helmet, prototypes were three-dimensional-printed with thermoplastic polyurethane and full-scale flat and oblique drop tests were performed. In flat impacts, honeycomb helmets resulted in a 34% higher peak linear acceleration and 7% lower head injury criteria (HIC15) than EPS foam helmets. In oblique tests, honeycomb helmets resulted in a 30% lower HIC15 and 40% lower peak rotational acceleration compared to EPS foam helmets. This new helmet design has the potential to reduce the risk of TBI in a bicycle accident, and as such, reduce its social and economic burden. Also, the honeycomb design showed potential to be effective for repetitive impact events without the need for replacement, offering benefits to consumers.