A New Assessment of Bicycle Helmets: The Brain Injury Mitigation Effects of New Technologies in Oblique Impacts

Equestrian STAR: Development of an Experimental Methodology for Assessing the Biomechanical Performance of Equestrian Helmets

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 (R2 = 0.34, p < 0.001), while peak rotational acceleration was not correlated (R2 = 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.

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.

Helmet material design for mitigating traumatic axonal injuries through AI-driven constitutive law enhancement

Sports helmets provide incomplete protection against brain injuries. Here we aim to improve helmet liner efficiency by employing a novel approach that optimizes their properties. By exploiting a finite element model that simulates head impacts, we developed deep learning models that predict the peak rotational velocity and acceleration of a dummy head protected by various liner materials. The deep learning models exhibited a remarkable correlation coefficient of 0.99 within the testing dataset with mean absolute error of 0.8 rad.s-1 and 0.6 krad.s-2 respectively, highlighting their predictive ability. Deep learning-based material optimization demonstrated a significant reduction in the risk of brain injuries, ranging from -5% to -65%, for impact energies between 250 and 500 Joules. This result emphasizes the effectiveness of material design to mitigate sport-related brain injury risks. This research introduces promising avenues for optimizing helmet designs to enhance their protective capabilities.

How Well Do Popular Bicycle Helmets Protect from Different Types of Head Injury?

Bicycle helmets are designed to protect against skull fractures and associated focal brain injuries, driven by helmet standards. Another type of head injury seen in injured cyclists is diffuse brain injuries, but little is known about the protection provided by bicycle helmets against these injuries. Here, we examine the performance of modern bicycle helmets in preventing diffuse injuries and skull fractures under impact conditions that represent a range of real-world incidents. We also investigate the effects of helmet technology, price, and mass on protection against these pathologies. 30 most popular helmets among UK cyclists were purchased within 9.99-135.00 GBP price range. Helmets were tested under oblique impacts onto a 45° anvil at 6.5 m/s impact speed and four locations, front, rear, side, and front-side. A new headform, which better represents the average human head's mass, moments of inertia and coefficient of friction than any other available headforms, was used. We determined peak linear acceleration (PLA), peak rotational acceleration (PRA), peak rotational velocity (PRV), and BrIC. We also determined the risk of skull fractures based on PLA (linear risk), risk of diffuse brain injuries based on BrIC (rotational risk), and their mean (overall risk). Our results show large variation in head kinematics: PLA (80-213 g), PRV (8.5-29.9 rad/s), PRA (1.6-9.7 krad/s2), and BrIC (0.17-0.65). The overall risk varied considerably with a 2.25 ratio between the least and most protective helmet. This ratio was 1.76 for the linear and 4.21 for the rotational risk. Nine best performing helmets were equipped with the rotation management technology MIPS, but not all helmets equipped with MIPS were among the best performing helmets. Our comparison of three tested helmets which have MIPS and no-MIPS versions showed that MIPS reduced rotational kinematics, but not linear kinematics. We found no significant effect of helmet price on exposure-adjusted injury risks. We found that larger helmet mass was associated with higher linear risk. This study highlights the need for a holistic approach, including both rotational and linear head injury metrics and risks, in helmet design and testing. It also highlights the need for providing information about helmet safety to consumers to help them make an informed choice.

Fracture patterns in bicycle accidents: A descriptive national cohort study of fractures sustained in bicycle accidents in the Swedish Fracture Register 2015-2022

INTRODUCTION

Bicycle accidents account for the majority of traffic-related accidents in Sweden. Despite the widespread everyday use of bicycles, little is known about the fracture panorama resulting from bicycle accidents. This study analysed the fracture patterns of bicycle accidents in Sweden in regard to fracture type, sex, age, and type of bicycle.

MATERIAL AND METHODS

We retrieved data from the Swedish Fracture Register on all fractures caused by bicycle accidents between 2015 and 2022. The study population was comprised of both children and adults who had sustained one or more fractures in a bicycle accident as registered in the Swedish Fracture Register.

RESULTS

We included 33,384 fractures (25,960 in adults and 7424 in children) in 30,815 patients, with a dominance of fractures in men. The mean age at fracture was 41.6 years (SD 23). The majority of fractures (62.7 %, n = 20,932) were sustained via a low energy mechanism. Overall, the most commonly fractured body parts were the forearm (35.2 %, n = 11,747), the hand (15.6 %, n = 5,196) and the clavicle (13.7 %, n = 4,558). In children, fractures of the forearm (56.8 %, n = 4,215) clearly dominated, followed by the hand (11.7 %, n = 868), and the humerus (11.0 %, n = 816). In adults, the top 3 fracture locations were the forearm (29.0 %, n = 7,532), the hand (16.7 %, n = 4,328), and the clavicle (15.7 %, n = 4,086). Mountain bikes and road bikes showed a fracture panorama that was very similar with a predominance of fractures to the clavicle. Fractures were more common during the warm season.

CONCLUSION

The main finding is that bicyclists predominantly sustained fractures of the upper limb via low energy mechanisms. The fracture panorama differed by age, sex, and type of bicycle.

Bicycle helmets are associated with fewer and less severe head injuries and fewer neurosurgical procedures

PURPOSE

This study explores the protective capabilities of bicycle helmets on serious head injury among bicyclists hospitalized in a Norwegian level 1 trauma centre.

METHOD

Information on helmet use, demographic variables, Abbreviated Injury Scale (AIS) and surgical procedure codes was retrieved from the Oslo University Hospital Trauma Registry for patients with bicycle-related injuries from 2005 through 2016. Outcomes were serious head injury defined as maximum AIS severity score ≥ 3 in the AIS region Head, any cranial neurosurgical procedure, and 30-day mortality.

RESULTS

A total of 1256 hospitalized bicyclists were included. The median age was 41 years (quartiles 26-53), 73% were male, 5.3% had severe pre-injury comorbidities, and 54% wore a helmet at the time of injury. Serious head injury occurred in 30%, 9% underwent a cranial neurosurgical procedure, and 30-day mortality was 2%. Compared to non-helmeted bicyclists, helmeted bicyclists were older (43 years, quartiles 27-54, vs. 38 years, quartiles 23-53, p = 0.05), less often crashed during night-time (21% vs. 38%, p < 0.001), less frequently had serious head injury (22% vs. 38%, OR 0.29, 95% CI 0.22-0.39), and less often underwent cranial neurosurgery (6% vs. 14%, OR 0.36, 95% CI 0.24-0.54). No statistically significant difference in 30-day mortality between the two groups was found (1.5% vs. 2.9%, OR 0.50, 95% CI 0.22-1.11).

CONCLUSION

Helmet use was associated with fewer and less severe head injuries and fewer neurosurgical procedures. This adds evidence to the protective capabilities of bicycle helmets.

Trends and Patterns in Bicycle Injuries: The Significance of Protective Equipment

Introduction This research presents a five-year comprehensive analysis of trends and efficacy related to helmet and protective equipment use in bicycle-related incidents. Our areas of comparison included injury severity, hospital stay, the Glasgow Coma Scale (GCS) scores, and demographic data. In light of the current increase in bicycle use popularity, this study aimed to provide clear information regarding the significance of protective equipment to combat the surge in bicycle-related incidents in recent years.  Methods A retrospective analysis was performed using the National Trauma Data Standard (NTDS) as a data source. Our inclusion criteria considered the mechanism of injury involving bicycle incidents, narrowing our pool of patients to 135,605. These cases were screened based on the following parameters: use of helmet/protective equipment, demographic criteria, and several other injury markers. Statistical analyses, including two sample t-tests, were performed using SAS.  Results A total of 5.7 million patients were screened for inclusion criteria, yielding 135,605 cases involving bicycle-related injuries between 2018 and 2022. Of the patients who met the inclusion criteria, patients wearing helmets had an overall high GCS score (p<0.001) and decreased hospital stay (p<0.001) compared to those without helmet use. Similar findings were drawn related to protective equipment use and GCS (p<0.001). The Injury Severity Score (ISS) on average was higher for those wearing helmets (p<0.001). Overall, an increase in helmet use was noted for the years in question (R2=0.467). Additional observations made include large variations in helmet use in different age groups. Patients aged <17 years wore helmets in just 6,514 (22%) cases while those aged +65 years wore helmets in 10,925 (51%) cases.  Conclusions This study observed a statistically significant difference between GCS values in helmet/non-helmet-wearing groups. Similar findings were found regarding other protective equipment use as well. A statistically significant difference was also found regarding increased ISS with helmet use. This challenges our current assumptions about improved injury severity with the use of protective equipment. In line with other studies, we determined that helmet use tends to decrease the level of injuries on the head. Overall, helmet use has increased in the past five years, but several demographic groups were found to wear protective equipment less often. We recommend future research that focuses on understanding the trends in protective equipment use among bicycle-riding individuals under the age of 25 years, Native Americans, and African Americans. Continued research regarding injury reduction interventions is of utmost importance, especially given the widespread increase in the popularity of bicycle use.

Potential of Soft-Shelled Rugby Headgear to Lower Regional Brain Strain Metrics During Standard Drop Tests

BACKGROUND

The growing concern for player safety in rugby has led to an increased focus on head impacts. Previous laboratory studies have shown that rugby headgear significantly reduces peak linear and rotational accelerations compared to no headgear. However, these metrics may have limited relevance in assessing the effectiveness of headgear in preventing strain-based brain injuries like concussions. This study used an instantaneous deep-learning brain injury model to quantify regional brain strain mitigation of rugby headgear during drop tests. Tests were conducted on flat and angled impact surfaces across different heights, using a Hybrid III headform and neck.

RESULTS

Headgear presence generally reduced the peak rotational velocities, with some headgear outperforming others. However, the effect on peak regional brain strains was less consistent. Of the 5 headgear tested, only the newer models that use open cell foams at densities above 45 kg/m3 consistently reduced the peak strain in the cerebrum, corpus callosum, and brainstem. The 3 conventional headgear that use closed cell foams at or below 45 kg/m3 showed no consistent reduction in the peak strain in the cerebrum, corpus callosum, and brainstem.

CONCLUSIONS

The presence of rugby headgear may be able to reduce the severity of head impact exposure during rugby. However, to understand how these findings relate to brain strain mitigation in the field, further investigation into the relationship between the impact conditions in this study and those encountered during actual gameplay is necessary.

An Assessment of Sikh Turban's Head Protection in Bicycle Incident Scenarios

Due to religious tenets, Sikh population wear turbans and are exempted from wearing helmets in several countries. However, the extent of protection provided by turbans against head injuries during head impacts remains untested. One aim of this study was to provide the first-series data of turbans' protective performance under impact conditions that are representative of real-world bicycle incidents and compare it with the performance of bicycle helmets. Another aim was to suggest potential ways for improving turban's protective performance. We tested five different turbans, distinguished by two wrapping styles and two fabric materials with a size variation in one of the styles. A Hybrid III headform fitted with the turban was dropped onto a 45 degrees anvil at 6.3 m/s and head accelerations were measured. We found large difference in the performance of different turbans, with up to 59% difference in peak translational acceleration, 85% in peak rotational acceleration, and 45% in peak rotational velocity between the best and worst performing turbans. For the same turban, impact on the left and right sides of the head produced very different head kinematics, showing the effects of turban layering. Compared to unprotected head impacts, turbans considerably reduce head injury metrics. However, turbans produced higher values of peak linear and rotational accelerations in front and left impacts than bicycle helmets, except from one turban which produced lower peak head kinematics values in left impacts. In addition, turbans produced peak rotational velocities comparable with bicycle helmets, except from one turban which produced higher values. The impact locations tested here were covered with thick layers of turbans and they were impacted against flat anvils. Turbans may not provide much protection if impacts occur at regions covered with limited amount of fabric or if the impact is against non-flat anvils, which remain untested. Our analysis shows that turbans can be easily compressed and bottom out creating spikes in the headform's translational acceleration. In addition, the high friction between the turban and anvil surface leads to higher tangential force generating more rotational motion. Hence, in addition to improving the coverage of the head, particularly in the crown and rear locations, we propose two directions for turban improvement: (i) adding deformable materials within the turban layers to increase the impact duration and reduce the risk of bottoming out; (ii) reducing the friction between turban layers to reduce the transmission of rotational motion to the head. Overall, the study assessed Turbans' protection in cyclist head collisions, with a vision that the results of this study can guide further necessary improvements for advanced head protection for the Sikh community.

Biomechanical Response of Head Surrogate With and Without the Helmet

Measurements of brain deformations under injurious loading scenarios are actively sought. In this work, we report experimentally measured head kinematics and corresponding dynamic, two-dimensional brain simulant deformations in head surrogates under a blunt impact, with and without a helmet. Head surrogates used in this work consisted of skin, skull, dura, falx, tentorium, and brain stimulants. The head surrogate geometry was based on the global human body models consortium's head model. A base head surrogate consisting of skin-skull-brain was considered. In addition, the response of two other head surrogates, skin-skull-dura-brain, and skin-skull-dura-brain-falx-tentorium, was investigated. Head surrogate response was studied for sagittal and coronal plane rotations for impactor velocities of 1 and 3 m/s. Response of head surrogates was compared against strain measurements in PMHS. The strain pattern in the brain simulant was heterogenous, and peak strains were established within ∼30 ms. The choice of head surrogate affect the spatiotemporal evolution of strain. For no helmet case, peak MPS of ∼50-60% and peak MSS of ∼35-50% were seen in brain simulant corresponding to peak rotational accelerations of ∼5000-7000 rad/s2. Peak head kinematics and peak MPS have been reduced by up to 75% and 45%, respectively, with the conventional helmet and by up to 90% and 85%, respectively, with the helmet with antirotational pads. Overall, these results provide important, new data on brain simulant strains under a variety of loading scenarios-with and without the helmets.

An Instrumented Mouthguard for Real-Time Measurement of Head Kinematics under a Large Range of Sport Specific Accelerations

BACKGROUND

Head impacts in sports can produce brain injuries. The accurate quantification of head kinematics through instrumented mouthguards (iMG) can help identify underlying brain motion during injurious impacts. The aim of the current study is to assess the validity of an iMG across a large range of linear and rotational accelerations to allow for on-field head impact monitoring.

METHODS

Drop tests of an instrumented helmeted anthropometric testing device (ATD) were performed across a range of impact magnitudes and locations, with iMG measures collected concurrently. ATD and iMG kinematics were also fed forward to high-fidelity brain models to predict maximal principal strain.

RESULTS

The impacts produced a wide range of head kinematics (16-171 g, 1330-10,164 rad/s2 and 11.3-41.5 rad/s) and durations (6-18 ms), representing impacts in rugby and boxing. Comparison of the peak values across ATD and iMG indicated high levels of agreement, with a total concordance correlation coefficient of 0.97 for peak impact kinematics and 0.97 for predicted brain strain. We also found good agreement between iMG and ATD measured time-series kinematic data, with the highest normalized root mean squared error for rotational velocity (5.47 ± 2.61%) and the lowest for rotational acceleration (1.24 ± 0.86%). Our results confirm that the iMG can reliably measure laboratory-based head kinematics under a large range of accelerations and is suitable for future on-field validity assessments.

An Air-Filled Bicycle Helmet for Mitigating Traumatic Brain Injury

We created a novel air-filled bicycle helmet. The aims of this study were (i) to assess the head injury mitigation performance of the proposed helmet and (ii) to compare those performance results against the performance results of an expanded polystyrene (EPS) traditional bicycle helmet. Two bicycle helmet types were subjected to impacts in guided vertical drop tests onto a flat anvil: EPS helmets and air-filled helmets (Bumpair). The maximum acceleration value recorded during the test on the Bumpair helmet was 86.76 ± 3.06 g, while the acceleration during the first shock on the traditional helmets reached 207.85 ± 5.55 g (p < 0.001). For the traditional helmets, the acceleration increased steadily over the number of shocks. There was a strong correlation between the number of impacts and the response of the traditional helmet (cor = 0.94; p < 0.001), while the Bumpair helmets showed a less significant dependence over time (cor = 0.36; p = 0.048), meaning previous impacts had a lower consequence. The air-filled helmet significantly reduced the maximal linear acceleration when compared to an EPS traditional helmet, showing improvements in impact energy mitigation, as well as in resistance to repeated impacts. This novel helmet concept could improve head injury mitigation in cyclists.

A Review of Cyclist Head Injury, Impact Characteristics and the Implications for Helmet Assessment Methods

Head injuries are common for cyclists involved in collisions. Such collision scenarios result in a range of injuries, with different head impact speeds, angles, locations, or surfaces. A clear understanding of these collision characteristics is vital to design high fidelity test methods for evaluating the performance of helmets. We review literature detailing real-world cyclist collision scenarios and report on these key characteristics. Our review shows that helmeted cyclists have a considerable reduction in skull fracture and focal brain pathologies compared to non-helmeted cyclists, as well as a reduction in all brain pathologies. The considerable reduction in focal head pathologies is likely to be due to helmet standards mandating thresholds of linear acceleration. The less considerable reduction in diffuse brain injuries is likely to be due to the lack of monitoring head rotation in test methods. We performed a novel meta-analysis of the location of 1809 head impacts from ten studies. Most studies showed that the side and front regions are frequently impacted, with one large, contemporary study highlighting a high proportion of occipital impacts. Helmets frequently had impact locations low down near the rim line. The face is not well protected by most conventional bicycle helmets. Several papers determine head impact speed and angle from in-depth reconstructions and computer simulations. They report head impact speeds from 5 to 16 m/s, with a concentration around 5 to 8 m/s and higher speeds when there was another vehicle involved in the collision. Reported angles range from 10° to 80° to the normal, and are concentrated around 30°-50°. Our review also shows that in nearly 80% of the cases, the head impact is reported to be against a flat surface. This review highlights current gaps in data, and calls for more research and data to better inform improvements in testing methods of standards and rating schemes and raise helmet safety.

In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation

Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may be used to predict the risk of TBI. However, lack of collision details can render accident reconstruction nearly impossible. Here, we introduce a reconstruction method to evaluate the brain injury in a bicycle–vehicle collision using the crash helmet alone. Following a thorough inspection of the cyclist’s helmet, we identified a severe impact, a moderate impact and several scrapes, which helped us to determine the impact conditions. We used our helmet test rig and intact helmets identical to the cyclist’s helmet to replicate the damage seen on the cyclist’s helmet involved in the real-world collision. We performed both linear and oblique impacts, measured the translational and rotational kinematics of the head and predicted the strain and the strain rate across the brain using a computational head model. Our results proved the hypothesis that the cyclist sustained a severe impact followed by a moderate impact on the road surface. The estimated head accelerations and velocity (167 g, 40.7 rad/s and 13.2 krad/s2) and the brain strain and strain rate (0.541 and 415/s) confirmed that the severe impact was large enough to produce mild to moderate TBI. The method introduced in this study can guide future accident reconstructions, allowing for the evaluation of TBI using the crash helmet only.

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.

Whitewater Helmet STAR: Evaluation of the Biomechanical Performance and Risk of Head Injury for Whitewater Helmets

More than six million people participate in whitewater kayaking and rafting in the United States each year. Unfortunately, with these six million whitewater participants come 50 deaths annually, making it one of the highest fatality rates of all sports. As the popularity in whitewater activities grows, the number of injuries, including concussions, also increases. The objective of this study was to create a new rating system for whitewater helmets by evaluating the biomechanical performance and risk of head injury of whitewater helmets using the Summation of Tests for the Analysis of Risk (STAR) system. All watersport helmets that passed the EN: 1385: 2012 standard and that were clearly marketed for whitewater use were selected for this study. Two samples of each helmet model were tested on a custom pendulum impactor under conditions known to be associated with the highest risk of head injury and death. A 50th percentile male NOCSAE headform instrumented with three linear accelerometers and a triaxial angular rate sensor coupled with a Hybrid III 50th percentile neck were used for data collection. A total of 126 tests were performed using six different configurations. These included impacts to the front, side, and rear using two speeds of 3.1 and 4.9 m/s that modeled whitewater river flow rates. Each helmet's STAR score was calculated using the combination of exposure and injury risk that was determined from the linear and rotational head accelerations. The resulting head impact accelerations predicted a very high risk of concussion for all impact locations at the 4.9 m/s speed. The STAR score varied between helmets indicating that some helmets provide better protection than others. Overall, these results show a clear need for improvement in whitewater helmets, and the methodologies developed in this research project should provide manufacturers a design tool for improving these products.

Neurotrauma Prevention Review: Improving Helmet Design and Implementation

Neurotrauma continues to contribute to significant mortality and disability. The need for better protective equipment is apparent. This review focuses on improved helmet design and the necessity for continued research. We start by highlighting current innovations in helmet design for sport and subsequent utilization in the lay community for construction. The current standards by sport and organization are summarized. We then address current standards within the military environment. The pathophysiology is discussed with emphasis on how helmets provide protection. As innovative designs emerge, protection against secondary injury becomes apparent. Much research is needed, but this focused paper is intended to serve as a catalyst for improvement in helmet design and implementation to provide more efficient and reliable neuroprotection across broad arenas.

Oblique impact responses of Hybrid III and a new headform with more biofidelic coefficient of friction and moments of inertia

New oblique impact methods for evaluating head injury mitigation effects of helmets are emerging, which mandate measuring both translational and rotational kinematics of the headform. These methods need headforms with biofidelic mass, moments of inertia (MoIs), and coefficient of friction (CoF). To fulfill this need, working group 11 of the European standardization head protection committee (CEN/TC158) has been working on the development of a new headform with realistic MoIs and CoF, based on recent biomechanics research on the human head. In this study, we used a version of this headform (Cellbond) to test a motorcycle helmet under the oblique impact at 8 m/s at five different locations. We also used the Hybrid III headform, which is commonly used in the helmet oblique impact. We tested whether there is a difference between the predictions of the headforms in terms of injury metrics based on head kinematics, including peak translational and rotational acceleration, peak rotational velocity, and BrIC (brain injury criterion). We also used the Imperial College finite element model of the human head to predict the strain and strain rate across the brain and tested whether there is a difference between the headforms in terms of the predicted strain and strain rate. We found that the Cellbond headform produced similar or higher peak translational accelerations depending on the impact location (−3.2% in the front-side impact to 24.3% in the rear impact). The Cellbond headform, however, produced significantly lower peak rotational acceleration (−41.8% in a rear impact to −62.7% in a side impact), peak rotational velocity (−29.5% in a side impact to −47.6% in a rear impact), and BrIC (−29% in a rear-side impact to −45.3% in a rear impact). The 90th percentile values of the maximum brain strain and strain rate were also significantly lower using this headform. Our results suggest that MoIs and CoF have significant effects on headform rotational kinematics, and consequently brain deformation, during the helmeted oblique impact. Future helmet standards and rating methods should use headforms with realistic MoIs and CoF (e.g., the Cellbond headform) to ensure more accurate representation of the head in laboratory impact tests.

Drop Test Kinematics Using Varied Impact Surfaces and Head/Neck Configurations for Rugby Headgear Testing

World Rugby employs a specific drop test method to evaluate headgear performance, but almost all researchers use a different variation of this method. The aim of this study was, therefore, to quantify the differences between variations of the drop testing method using a Hybrid III headform and neck in the following impact setups: (1) headform only, with a flat steel impact surface, approximating the World Rugby method, (2 and 3) headform with and without a neck, respectively, onto a flat MEP pad impact surface, and (4) headform and neck, dropped onto an angled MEP pad impact surface. Each variation was subject to drop heights of 75-600 mm across three orientations (forehead, side, and rear boss). Comparisons were limited to the linear and rotational acceleration and rotational velocity for simplicity. Substantial differences in kinematic profile shape manifested between all drop test variations. Peak accelerations varied highly between variations, but the peak rotational velocities did not. Drop test variation also significantly changed the ratios of the peak kinematics to each other. This information can be compared to kinematic data from field head impacts and could inform more realistic impact testing methods for assessing headgear.

Bicycle-related cervical spine injuries

Background

Bicyclists are vulnerable road users. The aim of this paper was to describe all bicycle-related traumatic cervical spine injuries (CSIs) in the South-East region of Norway (2015-2019), and to investigate whether certain types of CSIs are typical for bicyclists.

Methods

Retrospective cohort study of prospectively collected registry data of all CSIs in the South-East region of Norway (3.0 million inhabitants), from 2015 to 2019. Patient characteristics, injury types, and treatment were summarized with descriptive statistics. Bayesian multivariable logistic regression was used to identify potential factors associated with occipital condyle fractures (OC-Fx) or odontoid fractures (OFx).

Results

During the five-year study period, 2,162 patients with CSIs were registered, and 261 (12%) were bicycle-related. The incidence of bicycle-related CSIs was 1.7/100,000 person-years. The median age of the patients with bicycle-related CSIs was 55 (IQR: 22) years, 83% were male, 71% used a helmet, 16% were influenced by ethanol, 12% had a concomitant cervical spinal cord injury (SCI), and 64% sustained multiple traumas. The three most common bicycle-related CSIs were C6/C7 fracture (Fx) (28%), occipital condyle Fx (OC-Fx) (23%) and C5/C6 Fx (19%). Patients with bicycle-related CSIs compared to patients with non-bicycle related CSIs were younger, more often male, had fewer comorbidities, more likely multiple traumas, more often had OC-Fx, and less often sustained an odontoid fracture (OFx). Multivariable logistic regression of potential risk factors for OC-Fx demonstrated a significantly increased risk of OC-Fx for bicyclists compared to non-bicyclists (OR=2.8).The primary treatment for bicycle-related CSIs was external immobilization in 187/261 (71.6%) cases, open surgical fixation in 44/261 (16.8%), and no treatment in 30/261 (11.5%).

Conclusion

Bicycle crashes are a frequent cause of CSIs in the Norwegian population and should be of concern to the public society. The three most common bicycle-related CSIs were C6/C7 fracture, occipital condyle fracture and C5/C6 fracture.

Evaluation of two rotational helmet technologies to decrease peak rotational acceleration in cycling helmets

The risk of brain trauma has been associated with the rotational kinematics leading to the development of helmets with a variety rotational management technologies. The purpose of this paper was to employ a rotation specific test protocol to evaluate the effectiveness of two of these technologies. Dynamic response of the head was measured to assess the performance of each technology. Three cycling helmets with identical construction were included in this study. One helmet with no rotational technology, an established, commercial technology and a novel helmet rotational technology designed and assembled by the authors were tested. A drop test onto a 45° anvil was used to measure the ability of each helmet to manage the dynamic response of the head form during a series of impacts. The results revealed both rotational helmet technologies resulted in lower peak rotational acceleration and brain strain, however each technology demonstrated unique performance characteristics depending on the impact condition.

The Effect of MIPS, Headform Condition, and Impact Orientation on Headform Kinematics Across a Range of Impact Speeds During Oblique Bicycle Helmet Impacts

Bicycle helmets are designed to attenuate both the linear and rotational response of the head during an oblique impact. Here we sought to quantify how the effectiveness of one popular rotation-attenuating system (MIPS) varied across 3 test headform conditions (bare, covered in stockings, and hair), 3 oblique impact orientations, and 4 impact speeds. We conducted 72 freefall drop tests of a single helmet model with and without MIPS onto a 45° angled anvil and measured the peak linear (PLA) and angular acceleration (PAA) and computed the angular velocity change (PAV) and brain injury criterion (BrIC). Across all headform conditions, MIPS reduced PAA and PAV by 38.2 and 33.2% respectively during X-axis rotation, 47.4 and 38.1% respectively during Y-axis rotation, and 22.9 and 20.5% during a combined ZY-axis rotation. Across all impact orientations, PAA was reduced by 39% and PAV by 32.4% with the bare headform while adding stockings reduced PAA and PAV by 41.6 and 36% respectively and the hair condition reduced PAA and PAV by 30.2 and 24.4% respectively. In addition, our data reveal the importance of using consistent headform conditions when evaluating the effect of helmet systems designed to attenuate head rotations during oblique impacts.

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

BACKGROUND

Cycling helmets often incorporate elements aimed to dissipate rotational energies, which is widely acknowledged to play a key role in concussion mechanics. In this study, we investigated the mechanics of an oblique helmet test protocol that induced helmet rotation while using it to evaluate the effectiveness of three helmet models: two standard expanded polystyrene helmets and a commercially-available helmet equipped with a liner designed to mitigate linear and rotational energies.

METHODS

Helmets equipped with WaveCel were tested against two expanded polystyrene helmet models through guided drops using a Hybrid III (HIII) head-and-neck surrogate. The three helmet models were tested across four impact conditions (n = 5) of different speeds and impact surface angles.

FINDINGS

Across all tests, a similar sequence of head motion was observed - first a flexion phase followed by an extension phase. The extension phase lacked evidence of biofidelity and was likely attributable to the energy stored in the neckform during the flexion phase; it was therefore neglected from analysis. Results showed WaveCel reduced the probability of AIS2 head injury across all tests (3 to 27% reductions in 4.8 m/s impacts; 36 to 37% reductions in 6.2 m/s impacts).

INTERPRETATION

The two-phased response of the HIII suggests that boundary condition selection can influence results and should thus be reported in studies using similar methods. While this protocol involved both axial and tangential impact components and were thus representative of real-world collisions, the efficacy of WaveCel should be further investigated through additional laboratory studies and tracking real-world cycling injury statistics.

Computational prediction of head-ground impact kinematics in e-scooter falls

E-scooters are the fastest growing mode of micro-mobility with important environmental benefits. However, there are serious concerns about injuries caused by e-scooter accidents. Falls due to poor road surface conditions are a common cause of injury in e-scooter riders, and head injuries are one of the most common and concerning injuries in e-scooter falls. However, the head-ground impact biomechanics in e-scooter falls and its relationship with e-scooter speed and design, road surface conditions and wearing helmets remain poorly understood. To address some of these key questions, we predicted the head-ground impact force and velocity of e-scooter riders in different falls caused by potholes. We used multi-body dynamics approach to model a commercially available e-scooter and simulate 180 falls using human body models. We modelled different pothole sizes to test whether the pothole width and depth influences the onset of falls and head-ground impact velocity and force. We also tested whether the e-scooter travelling speed has an influence on the head-ground impact velocity and force. The simulations were carried out with three human body models to ensure that the results of the study are inclusive of a wide range of rider sizes. For our 10 in. diameter e-scooter wheels, we found a sudden increase in the occurrence of falls when the pothole depth was increased from 3 cm (no falls) to 6 cm (41 falls out of 60 cases). When the falls occurred, we found a head-ground impact force of 13.2 ± 3.4kN, which is larger than skull fracture thresholds. The head-ground impact speed was 6.3 ± 1.4 m/s, which is the same as the impact speed prescribed in bicycle helmet standards. All e-scooter falls resulted in oblique head impacts, with an impact angle of 65 ± 10° (measured from the ground). Decreasing the e-scooter speed reduced the head impact speed. For instance, reducing the e-scooter speed from 30 km/h to 20 km/h led to a 14% reduction in the mean impact speed and 12% reduction in the mean impact force, as predicted by the models. The models also showed that the median male riders were sustaining higher head-ground impact force and speed compared with the small female and large male riders. The findings of this study can assist authorities and e-scooter hiring companies to take more informed actions about road surface conditions and speed limits. These results can also help define representative impact test conditions for assessing the performance of helmets used by e-scooter riders in order to reduce head and brain injuries in e-scooter falls.

The relationship between road traffic collision dynamics and traumatic brain injury pathology

Road traffic collisions are a major cause of traumatic brain injury. However, the relationship between road traffic collision dynamics and traumatic brain injury risk for different road users is unknown. We investigated 2065 collisions from Great Britain's Road Accident In-depth Studies collision database involving 5374 subjects (2013-20). Five hundred and ninety-five subjects sustained a traumatic brain injury (20.2% of 2940 casualties), including 315 moderate-severe and 133 mild-probable injuries. Key pathologies included skull fracture (179, 31.9%), subarachnoid haemorrhage (171, 30.5%), focal brain injury (168, 29.9%) and subdural haematoma (96, 17.1%). These results were extended nationally using >1 000 000 police-reported collision casualties. Extrapolating from the in-depth data we estimate that there are ∼20 000 traumatic brain injury casualties (∼5000 moderate-severe) annually on Great Britain's roads, accounting for severity differences. Detailed collision investigation allows vehicle collision dynamics to be understood and the change in velocity (known as delta-V) to be estimated for a subset of in-depth collision data. Higher delta-V increased the risk of moderate-severe brain injury for all road users. The four key pathologies were not observed below 8 km/h delta-V for pedestrians/cyclists and 19 km/h delta-V for car occupants (higher delta-V threshold for focal injury in both groups). Traumatic brain injury risk depended on road user type, delta-V and impact direction. Accounting for delta-V, pedestrians/cyclists had a 6-times higher likelihood of moderate-severe brain injury than car occupants. Wearing a cycle helmet during a collision was protective against overall and mild-to-moderate-to-severe brain injury, particularly skull fracture and subdural haematoma. Cycle helmet protection was not due to travel or impact speed differences between helmeted and non-helmeted cyclist groups. We additionally examined the influence of the delta-V direction. Car occupants exposed to a higher lateral delta-V component had a greater prevalence of moderate-severe brain injury, particularly subarachnoid haemorrhage. Multivariate logistic regression models created using total delta-V value and whether lateral delta-V was dominant had the best prediction capabilities (area under the receiver operator curve as high as 0.95). Collision notification systems are routinely fitted in new cars. These record delta-V and automatically alert emergency services to a collision in real-time. These risk relationships could, therefore, inform how routinely fitted automatic collision notification systems alert the emergency services to collisions with a high brain injury risk. Early notification of high-risk scenarios would enable quicker activation of the highest level of emergency service response. Identifying those that require neurosurgical care and ensuring they are transported directly to a centre with neuro-specialist provisions could improve patient outcomes.

An Overview of the Effectiveness of Bicycle Helmet Designs in Impact Testing

Cycling accidents are the leading cause of sports-related head injuries in the US. Conventional bicycle helmets typically consist of polycarbonate shell over Expanded Polystyrene (EPS) foam and are tested with drop tests to evaluate a helmet’s ability to reduce head kinematics. Within the last decade, novel helmet technologies have been proposed to mitigate brain injuries during bicycle accidents, which necessitates the evaluation of their effectiveness in impact testing as compared to conventional helmets. In this paper, we reviewed the literature to collect and analyze the kinematic data of drop test experiments carried out on helmets with different technologies. In order to provide a fair comparison across different types of tests, we clustered the datasets with respect to their normal impact velocities, impact angular momentum, and the type of neck apparatus. When we analyzed the data based on impact velocity and angular momentum clusters, we found that the bicycle helmets that used rotation damping based technology, namely MIPS, had significantly lower peak rotational acceleration (PRA) and Generalized Acceleration Model for Brain Injury Threshold (GAMBIT) as compared to the conventional EPS liner helmets (p < 0.01). SPIN helmets had a superior performance in PRA compared to conventional helmets (p < 0.05) in the impact angular momentum clustered group, but not in the impact-velocity clustered comparisons. We also analyzed other recently developed helmets that primarily use collapsible structures in their liners, such as WaveCel and Koroyd. In both of the impact velocity and angular momentum groups, helmets based on the WaveCel technology had significantly lower peak linear acceleration (PLA), PRA, and GAMBIT at low impact velocities as compared to the conventional helmets, respectively (p < 0.05). The protective gear with the airbag technology, namely Hövding, also performed significantly better compared to the conventional helmets in the analyzed kinematic-based injury metrics (p < 0.001), possibly due to its advantage in helmet size and stiffness. We also observed that the differences in the kinematic datasets strongly depend on the type of neck apparatus. Our findings highlight the importance and benefits of developing new technologies and impact testing standards for bicycle helmet designs for better prevention of traumatic brain injury (TBI).