Designing protective systems for the human head—and, hence, the brain—requires understanding the brain’s microstructural response to mechanical insults. We present the behavior of wet and dry porcine brain undergoing quasi-static and high strain rate mechanical deformations to unravel the effect of hydration on the brain’s biomechanics. Here, native ‘wet’ brain samples contained ~80% (mass/mass) water content and ‘dry’ brain samples contained ~0% (mass/mass) water content. First, the wet brain incurred a large initial peak stress that was not exhibited by the dry brain. Second, stress levels for the dry brain were greater than the wet brain. Third, the dry brain stress–strain behavior was characteristic of ductile materials with a yield point and work hardening; however, the wet brain showed a typical concave inflection that is often manifested by polymers. Finally, finite element analysis (FEA) of the brain’s high strain rate response for samples with various proportions of water and dry brain showed that water played a major role in the initial hardening trend. Therefore, hydration level plays a key role in brain tissue micromechanics, and the incorporation of this hydration effect on the brain’s mechanical response in simulated injury scenarios or virtual human-centric protective headgear design is essential.

Purpose: The study purpose was to investigate the laboratory-based performance of three commercially available shell add-on products under varsity-level impact conditions. Methods: Pendulum impact tests were conducted at multiple locations (front, front boss, rear, side) and speeds (3.1, 4.9, 6.4 m/s) using two helmet models. Tests were performed with a single add-on configuration for baseline comparisons and a double add-on configuration to simulate collisions with both players wearing shell add-ons. A linear mixed-effect model was used to evaluate peak linear acceleration (PLA), peak rotational acceleration (PRA), and concussion risk, which was calculated from a bivariate injury risk function, based on shell add-on and test configuration. Results: All shell add-ons decreased peak head kinematics and injury risk compared to controls, with the Guardian NXT producing the largest reductions (PLA: 7.9%, PRA: 14.1%, Risk: 34.1%) compared to the SAFR Helmet Cover (PLA: 4.5%, PRA: 9.3%, Risk: 24.7%) and Guardian XT (PLA: 3.2%, PRA: 5.0%, Risk: 15.5%). The same trend was observed in the double add-on test configuration. However, the Guardian NXT (PLA: 17.1%; PRA: 11.5%; Risk: 62.8%) and SAFR Helmet Cover (PLA: 12.2%; PRA: 9.1%; Risk: 52.2%) produced larger reductions in peak head kinematics and injury risk than the Guardian XT (PLA: 5.7%, PRA: 2.2%, Risk: 21.8%). Conclusion: In laboratory-based assessments that simulated varsity-level impact conditions, the Guardian NXT was associated with larger reductions in PLA, PRA, and injury risk compared to the SAFR Helmet Cover and Guardian XT. Although shell add-ons can enhance head protection, helmet model selection should be prioritized.

This study utilized a guided free-fall drop tower and standard test headform to measure the peak linear acceleration (PLA) generated by different climbing helmet models that were impacted at various speeds (2–6 m s⁻¹) and locations (top, front, rear, side). Wide-ranging impact performance was observed for the climbing helmet models selected. Helmets that produced lower PLAs were composed of protective materials, such as expanded polystyrene (EPS) or expanded polypropylene, which were integrated throughout multiple helmet regions including the front, rear and side. Climbing helmets that produced the highest PLAs consisted of a chinstrap, a suspension system, an acrylontrile butadiene styrene (ABS) outer shell, and an EPS inner layer, which was applied only to the top location. Variation in impact protection was attributed not only to helmet model but also impact location. Although head acceleration measurements were fairly similar between helmet models at the top location, impacts to the front, rear, and side led to larger changes in PLA. A 300 g cutoff for PLA was chosen due to its use as a pass/fail threshold in other helmet safety standards, and because it represents a high risk of severe head injury. All seven helmet models had the lowest acceleration values at the top location with PLAs below 300 g at speeds as high as 6 m s⁻¹. Impact performance varied more substantially at the front, rear, and side locations, with some models generating PLAs above 300 g at speeds as low as 3 m s⁻¹. These differences in impact performance represent opportunities for improved helmet design to better protect climbers across a broader range of impact scenarios in the event of a fall or other collision. An understanding of how current climbing helmets attenuate head acceleration could allow manufacturers to enhance next-generation models with innovative and more robust safety features including smart materials.

Purpose: The current equestrian helmet standards set minimal requirements for passing helmets, highlighting the need for a rating system that differentiates helmets based on their impact performance. This study’s objectives were to compare equestrian helmet impact response kinematics between linear-driven and oblique impact conditions and then to evaluate the effect of incorporating oblique drop tests into a previously established equestrian helmet rating system, Equestrian STAR. Methods: Oblique drop tests were conducted with 45 equestrian helmet models at two impact locations, front boss and rear boss, at an impact velocity of 6.56 m/s. The resulting peak linear and rotational head accelerations were compared to those measured during linear-driven pendulum impacts on the same helmet models. A total of 720 impact tests were performed, making this the largest published study on equestrian helmets to date. Equestrian STAR was modified to include both pendulum and oblique impacts by computing and summing weighted concussion risks for each test condition. Results: Oblique impacts had peak linear accelerations ranging from 105.8 to 204.5 g and peak rotational accelerations ranging from 3304 to 13854 rad/s². Between the linear-driven and oblique impacts, peak linear acceleration was weakly correlated (R ² = 0.34, p < 0.001), while peak rotational acceleration was not correlated (R ² = 0.04, p = 0.21). Equestrian STAR scores calculated using both pendulum and oblique impacts suggested that the worst-performing helmet on both systems had nearly four times the concussion risk as the best-performing. Conclusion: Pendulum and oblique impacts have different methods of generating head rotation, which can highlight different modes of helmet performance. The updated Equestrian STAR helmet rating system differentiates between high-performing and low-performing helmets, enabling equestrians to purchase helmets best at reducing concussion risk and providing companies with a process to compare their helmet designs.

Objective: This study analyzed the influence of reference sensor inputs from anthropomorphic test devices (ATDs) versus postmortem human subjects (PMHSs) on simulations of frontal blunt impacts to the advanced combat helmet (ACH). Methods: A rigid-arm pendulum was used to generate frontal impacts to ACHs mounted on ATDs and PMHS. An appropriately sized ACH was selected according to standard fitting guidelines. The National Operating Committee on Standards for Athletic Equipment (NOCSAE) head was selected for ATD tests due to shape features that enabled a realistic helmet fit. A custom procedure was used to mount a reference sensor internally near the center of gravity (CG) of the PMHS. Reference sensor data from the head CG were used as inputs for the Simulated Injury Monitor (SIMon). Brain responses were assessed with the cumulative strain damage measure set at 10%, or CSDM(10). Results: Compared to ATD tests, PMHS tests produced 18.7% higher peak linear accelerations and 5.2% higher peak angular velocities. Average times to peak for linear accelerations were relatively similar between ATDs (5.5 ms) and PMHSs (5.8 ms). However, times to peak for angular velocities were higher by a factor of up to 3.4 for PMHSs compared to ATDs. Values for were also higher by a factor of up to 13.1 when PMHS inputs were used for SIMon. Conclusions: The preliminary findings of this work indicate that small differences in ATD versus PMHS head kinematics could lead to large differences in strain-derived brain injury metrics such as CSDM.