Head injury predictors in sports trauma--a state-of-the-art review

Accuracy and efficiency of finite element head models: The role of finite element formulation and material laws

Traumatic brain injury is a significant problem worldwide. In the United States of America, around 1.7 million cases are documented annually, displaying the need for a deeper understanding of the effects on the human brain. The tests required for this assessment are very complex. Tests on cadavers may raise serious ethical questions, and in vivo crash tests are not viable. In this context, there is a great need to developing finite element head models (FEHM) to study the biomechanics of the tissues when submitted to a certain impact or acceleration/deceleration scenario. An excellent compromise between accuracy and CPU efficiency is always desirable for a FEHM, For this reason, this work focuses on the improvement of an existing head model, including the study of the behavior of the brain using distinct finite element types. The finite element type and formulation is of utmost importance for the general accuracy and efficiency of the models. Several validations were performed, comparing the simulation results against experimental data. The simulations with hexahedral elements, under specific conditions, obtained more accurate results with a lower computational cost. Using hexahedrals, a comparison was also performed using two material characterizations with more than 10 years apart, using the latest finite element head model validation experiment. Overall, the newer material model displays a less stiff response, although its implementation must always depend on the overall purpose of the model it is being applied to.

Influence of centroid acceleration acquisition and filtering class on head injury criterion evaluation

BACKGROUND

Although the Head Injury Criteria (HIC) has been widely applied to assess head impact injuries, it faces two outstanding problems: 1) HIC is affected strongly by the cut-off frequency when processing acceleration signals. And these cut-off frequencies are experiential and lack unified guidelines; 2) If the head was impacted on a different part, should the corresponding HIC threshold be the same? If these problems are not resolved, it could potentially lead to a critical misinterpretation of the safety assessment.

METHODS

Finite element method was used to reconstruct head impacts. The head model includes tissues like skull, brainstem, cerebrospinal fluid, etc. The head model was impacted in the frontal, occipital, parietal or lateral direction with different impact velocities. Acceleration signals of the head model were extracted directly from the skull and the head centroid node. To obtain a robust HIC, the filtering class of acceleration signals were analyzed carefully. Then, the relation between rigid body HIC and the centroid node HIC were studied systematically.

RESULTS

When the filtering class of rigid body acceleration and centroid node acceleration reached the cut-off frequency, the corresponding derivative of HIC tended to change smoothly. Using these cut-off frequencies, robust HICs were obtained. The rigid body HIC far exceeded that of centroid node HIC, such as 8, 9, 14 and 31 times exceeded in the frontal, occipital, parietal and lateral impact conditions, respectively. Moreover, approximate linear relations were found between the rigid body HIC and the centroid node HIC in different impact directions, respectively. From these relations, the injury thresholds of rigid body HIC of various directions were given quantitatively.

CONCLUSIONS

The rational filtering class like CFC 800 and CFC 700 were given for rigid body HIC and centroid node HIC, respectively. The rigid body HIC had a significant discrepancy from the centroid node HIC. Linear relations between the rigid body HIC and centroid node HIC were found, and their slopes changed with impact directions. From these relations, we can adjust the injury thresholds reasonably if the head receives different impacts. These findings can effectively enhance the applicability of HIC.

mTBI Biological Biomarkers as Predictors of Postconcussion Syndrome-Review

Postconcussion syndrome (PCS) is one of the leading complications that may appear in patients after mild head trauma. Every day, thousands of people, regardless of age, gender, and race, are diagnosed in emergency departments due to head injuries. Traumatic Brain Injury (TBI) is a significant public health problem, impacting an estimated 1.5 million people in the United States and up to 69 million people worldwide each year, with 80% of these cases being mild. An analysis of the available research and a systematic review were conducted to search for a solution to predicting the occurrence of postconcussion syndrome. Particular biomarkers that can be examined upon admission to the emergency department after head injury were found as possible predictive factors of PCS development. Setting one unequivocal definition of PCS is still a challenge that causes inconsistent results. Neuron Specific Enolase (NSE), Glial Fibrillary Acidic Protein (GFAP), Ubiquitin C-terminal Hydrolase-L1 (UCH-L1), Serum Protein 100 B (s100B), and tau protein are found to be the best predictors of PCS development. The presence of all mentioned biomarkers is confirmed in severe TBI. All mentioned biomarkers are used as predictors of PCS. A combined examination of NSE, GFAP, UCH-1, S100B, and tau protein should be performed to detect mTBI and predict the development of PCS.

Revealing the role of material properties in impact-related injuries: Investigating the influence of brain and skull density variations on head injury severity

Traumatic brain injuries (TBI) resulting from head impacts are a major public health concern, which prompted our research to investigate the complex relationship between the material properties of brain tissue and the severity of TBI. The goal of this research is to investigate how variations in brain and skull density influence the vulnerability of brain tissue to traumatic injury, thereby enhancing our understanding of injury mechanism. To achieve this goal, we employed a well-validated finite element head model (FEHM). The current investigation was divided into two phases: in the first one, three distinct brain viscoelastic materials that had been utilized in prior studies were analyzed. The review of the properties of these three materials has been meticulous, encompassing both the spectrum of mechanical properties and the behaviors that are relevant to the way in which brain tissue reacts to traumatic loading conditions. In the second phase, the material properties of both the brain and skull tissue, alongside the impact conditions, were held constant. After this step, the focus was directed towards the variation of density in the brain and skull, which was consistent with the results obtained from previous experimental investigations, in order to determine the precise impact of these variations in density. This approach allowed a more profound comprehension of the impacts that density had on the simulation results. In the first phase, Material No. 2 exhibited the highest maximum first principal strain value in the frontal region (ε max = 15.41 % ), indicating lower stiffness to instantaneous deformation. This characteristic suggests that Material No. 2 may deform more extensively upon impact, potentially increasing the risk of injury due to its viscoelastic behavior. In contrast, Material No. 1, with a lower maximum first principal strain in the frontal region (ε max = 7.87 % ), displayed greater stiffness to instantaneous deformation, potentially reducing the risk of brain injury upon head impact. The second phase provided quantitative findings revealing a proportional relationship between brain tissue density and the pressures experienced by the brain. A 2 % increase in brain tissue density corresponded to approximately a 1 % increase in pressure on the brain tissue. Similarly, changes in skull density exhibited a similar quantitative relationship, with a 6 % increase in skull density leading to a 2.5 % increase in brain pressure. This preliminary approximate ratio of 2 to 1 between brain and skull density variations provides an initial quantitative framework for assessing the impact of density changes on brain vulnerability. These findings have several implications for the development of protective measures and injury prevention strategies, particularly in contexts where head trauma is a major issue.

A Method for Evaluating Brain Deformation Under Sagittal Blunt Impacts Using a Half-Skull Human-Scale Surrogate

Trauma to the brain is a biomechanical problem where the initiating event is a dynamic loading (blunt, inertial, blast) to the head. To understand the relationship between the mechanical parameters of the injury and the spatial and temporal deformation patterns in the brain, there is a need to develop a reusable and adaptable experimental traumatic brain injury (TBI) model that can measure brain motion under varying parameters. In this effort, we aim to directly measure brain deformation (strain and strain rates) in different brain regions in a human head model using a drop tower.

METHODS

Physical head models consisting of a half, sagittal plane skull, brain, and neck were constructed and subjected to crown and frontal impacts at two impact speeds. All tests were recorded with a high-speed camera at 1000 frames per second. Motion of visual markers within brain surrogates were used to track deformations and calculate spatial strain histories in 6 brain regions of interest. Principal strains, strain rates and strain impulses were calculated and reported.

RESULTS

Higher impact velocities corresponded to higher strain values across all impact scenarios. Crown impacts were characterized by high, long duration strains distributed across the parietal, frontal and hippocampal regions whereas frontal impacts were characterized by sharply rising and falling strains primarily found in the parietal, frontal, hippocampal and occipital regions. High strain rates were associated with short durations and impulses indicating fast but short-lived strains. 2.23 m/s (5 mph) crown impacts resulted in 53% of the brain with shear strains higher than 0.15 verses 32% for frontal impacts.

CONCLUSIONS

The results reveal large differences in the spatial and temporal strain responses between crown and forehead impacts. Overall, the results suggest that for the same speed, crown impact leads to higher magnitude strain patterns than a frontal impact. The data provided by this model provides unique insight into the spatial and temporal deformation patterns that have not been provided by alternate surrogate models. The model can be used to investigate how anatomical, material and loading features and parameters can affect deformation patterns in specific regions of interest in the brain.

Design of an Articulated Neck to Assess Impact Head-Neck Injuries

This paper describes a new solution for an articulated low-cost artificial neck with sensors to assess the effects of head impacts. This prototype is designed as a new solution to evaluate the neck’s response after suffering the head impact. An overview of existing solutions is reported to evaluate the advantages and disadvantages of each one briefly. Problems and requirements for prototype design are outlined to guide to a solution with commercial components. A prototype is developed, and its operating performance is evaluated through a lab test. Several tests are worked out considering the biomechanics involved in the most common accidents of head-neck impacts. Results show a response on the prototype similar to an actual human neck. Future improvements are also outlined for better accurate responses considering the results from the lab test.

Influence of Friction at the Head-Helmet Interface on Advanced Combat Helmet (ACH) Blunt Impact Kinematic Performance

INTRODUCTION

The purpose of this study was to compare the rotational blunt impact performance of an anthropomorphic test device (ATD: male 50% Hybrid III head and neck) headform donning an Advanced Combat Helmet (ACH) between conditions in which the coefficient of static friction (μs) at the head-to-helmet pad interface varied.

MATERIALS AND METHODS

Two ACHs (size large) were used in this study and friction was varied using polytetrafluoroethylene (PTFE), human hair, skullcap, and the native vinyl skin of the ATD. A condition in which hook and loop material adhered the headform to the liner system was also tested, resulting in a total of five conditions: PTFE, Human Hair, Skullcap, Vinyl, and Hook. Blunt impact tests with each helmet in each of the five conditions were conducted on a pneumatic linear impactor at 4.3 m/s. The ATD donning the ACH was impacted in seven locations (Crown, Front, Rear, Left Side, Right Side, Left Nape, and Right Nape). The peak resultant angular acceleration (PAA), velocity (PAV), and the Diffuse Axonal Multi-Axis, General Evaluation (DAMAGE) metric were compared between conditions.

RESULTS

No pairwise differences were observed between conditions for PAA. A positive correlation was observed between mean μs and PAA at the Front (τ = 0.28; P = .044) and Rear (τ = 0.31; P = .024) impact locations. The Hook condition had a mean PAV value that was often less than the other conditions (P ≤ .024). A positive correlation was observed between mean μs and PAV at the Front (τ = 0.32; P = .019) and Right Side (τ = 0.57; P < .001) locations. The Hook condition tended to have the lowest DAMAGE value compared to the other conditions (P ≤ .032). A positive correlation was observed between the mean μs and DAMAGE at the Rear (τ = 0.60; P < .001) location. A negative correlation was observed at the Left Side (τ = -0.28; P = .040), Right Side (τ = -0.58; P < .001) and Left Nape (τ = -0.56; P < .001) locations.

CONCLUSIONS

The results of this study indicate that at some impact locations kinematic responses can vary as a function of the friction at the head-to-helmet pad interface. However, a reduction in the coupling of the head-helmet pad interface did not consistently reduce head angular kinematics or measures of brain strain across impact locations. Thus, for the ACH during collision-type impacts, impact location as opposed to μs seems to have a greater influence on head kinematics and rotational-based measures of brain strain.

Injury Metrics for Assessing the Risk of Acute Subdural Hematoma in Traumatic Events

Worldwide, the ocurrence of acute subdural hematomas (ASDHs) in road traffic crashes is a major public health problem. ASDHs are usually produced by loss of structural integrity of one of the cerebral bridging veins (CBVs) linking the parasagittal sinus to the brain. Therefore, to assess the risk of ASDH it is important to know the mechanical conditions to which the CBVs are subjected during a potentially traumatic event (such as a traffic accident or a fall from height). Recently, new studies on CBVs have been published allowing much more accurate prediction of the likelihood of mechanical failure of CBVs. These new data can be used to propose new damage metrics, which make more accurate predictions about the probability of occurrence of ASDH in road crashes. This would allow a better assessement of the effects of passive safety countermeasures and, consequently, to improve vehicle restraint systems. Currently, some widely used damage metrics are based on partially obsolete data and measurements of the mechanical behavior of CBVs that have not been confirmed by subsequent studies. This paper proposes a revision of some existing metrics and constructs a new metric based on more accurate recent data on the mechanical failure of human CBVs.

Viscoelastic Characterization of Parasagittal Bridging Veins and Implications for Traumatic Brain Injury: A Pilot Study

Many previous studies on the mechanical properties of Parasagittal Bridging Veins (PSBVs) found that strain rate had a significant effect on some mechanical properties, but did not extensively study the viscoelastic effects, which are difficult to detect with uniaxial simple tensile tests. In this study, relaxation tests and tests under cyclic loading were performed, and it was found that PSBVs do indeed exhibit clear viscoelastic effects. In addition, a complete viscoelastic model for the PSBVs is proposed and data from relaxation, cyclic load and load-unload tests for triangular loads are used to find reference values that characterize the viscoelastic behavior of the PSBVs. Although such models have been proposed for other types of blood vessels, this is the first study that clearly demonstrates the existence of viscoelastic effects from an experimental point of view and also proposes a specific model to explain the data obtained. Finally, this study provides reference values for the usual viscoelastic properties, which would allow more accurate numerical simulation of PSBVs by means of computational models.

Mechanical Behavior of Blood Vessels: Elastic and Viscoelastic Contributions

The mechanical properties of the cerebral bridging veins (CBVs) were studied using advanced microtensile equipment. Detailed high-quality curves were obtained at different strain rates, showing a clearly nonlinear stress-strain response. In addition, the tissue of the CBVs exhibits stress relaxation and a preconditioning effect under cyclic loading, unequivocal indications of viscoelastic behavior. Interestingly, most previous literature that conducts uniaxial tensile tests had not found significant viscoelastic effects in CBVs, but the use of more sensitive tests allowed to observe the viscoelastic effects. For that reason, a careful mathematical analysis is presented, clarifying why in uniaxial tests with moderate strain rates, it is difficult to observe any viscoelastic effect. The analysis provides a theoretical explanation as to why many recent studies that investigated mechanical properties did not find a significant viscoelastic effect, even though in other circumstances, the CBV tissue would clearly exhibit viscoelastic behavior. Finally, this study provides reference values for the usual mechanical properties, as well as calculations of constitutive parameters for nonlinear elastic and viscoelastic models that would allow more accurate numerical simulation of CBVs in Finite Element-based computational models in future works.

Sports Specialization and Sports-Related Injuries in Japanese School-Aged Children and Adolescents: A Retrospective Descriptive Study

Although early sports specialization is associated with sports-related injuries, relevant quantitative studies on young non-elite athletes, the majority of sports participants, are scarce. We described sports specialization time points and the characteristics of sports-related injuries. Undergraduate students at a university in Japan (n = 830) recalled their history of sports participation from elementary to high school and sports-related injuries in a self-administered questionnaire. Of 570 valid respondents, 486 (85%) engaged in sports at least once. Significantly more respondents played multiple sports in upper elementary school (30%) than in other school categories (1-23%). In junior high and high schools, 90% and 99% played only one sport, respectively. Of the 486 respondents who played sports, 263 (54%) had experienced acute or overuse injuries. The proportion of injured participants significantly differed by school category: lower elementary school (4%), upper elementary school (21%), junior high (35%), and high school (41%). The proportions of acute or overuse injuries in males were higher than those in females. In conclusion, this study clarified a slight variation in sports items, particularly in junior high and high schools, which demonstrates 13 years as the age of beginning specialization in a single sport. More than half of the non-elite athletes experienced sports-related injuries. Injuries were frequently observed in males and those in junior high and high schools.

A Methodology to Compare Biomechanical Simulations With Clinical Brain Imaging Analysis Utilizing Two Blunt Impact Cases

According to the US Defense and Veterans Brain Injury Center (DVBIC) and Centers for Disease Control and Prevention (CDC), mild traumatic brain injury (mTBI) is a common form of head injury. Medical imaging data provides clinical insight into tissue damage/injury and injury severity, and helps medical diagnosis. Computational modeling and simulation can predict the biomechanical characteristics of such injury, and are useful for development of protective equipment. Integration of techniques from computational biomechanics with medical data assessment modalities (e.g., magnetic resonance imaging or MRI) has not yet been used to predict injury, support early medical diagnosis, or assess effectiveness of personal protective equipment. This paper presents a methodology to map computational simulations with clinical data for interpreting blunt impact TBI utilizing two clinically different head injury case studies. MRI modalities, such as T1, T2, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), were used for simulation comparisons. The two clinical cases have been reconstructed using finite element analysis to predict head biomechanics based on medical reports documented by a clinician. The findings are mapped to simulation results using image-based clinical analyses of head impact injuries, and modalities that could capture simulation results have been identified. In case 1, the MRI results showed lesions in the brain with skull indentation, while case 2 had lesions in both coup and contrecoup sides with no skull deformation. Simulation data analyses show that different biomechanical measures and thresholds are needed to explain different blunt impact injury modalities; specifically, strain rate threshold corresponds well with brain injury with skull indentation, while minimum pressure threshold corresponds well with coup–contrecoup injury; and DWI has been found to be the most appropriate modality for MRI data interpretation. As the findings from these two cases are substantiated with additional clinical studies, this methodology can be broadly applied as a tool to support injury assessment in head trauma events and to improve countermeasures (e.g., diagnostics and protective equipment design) to mitigate these injuries.

A Predictive Model to Analyze the Factors Affecting the Presence of Traumatic Brain Injury in the Elderly Occupants of Motor Vehicle Crashes Based on Korean In-Depth Accident Study (KIDAS) Database

Traumatic brain injury (TBI), also known as intracranial injury, occurs when an external force injures the brain. This study aimed to analyze the factors affecting the presence of TBI in the elderly occupants of motor vehicle crashes. We defined elderly occupants as those more than 55 years old. Damage to the vehicle was presented using the Collision Deformation Classification (CDC) code by evaluation of photos of the damaged vehicle, and a trauma score was used for evaluation of the severity of the patient’s injury. A logistic regression model was used to identify factors affecting TBI in elderly occupants and a predictive model was constructed. We performed this study retrospectively and gathered all the data under the Korean In-Depth Accident Study (KIDAS) investigation system. Among 3697 patients who visited the emergency room in the regional emergency medical center due to motor vehicle crashes from 2011 to 2018, we analyzed the data of 822 elderly occupants, which were divided into two groups: the TBI patients (N = 357) and the non-TBI patients (N = 465). According to multiple logistic regression analysis, the probabilities of TBI in the elderly caused by rear-end (OR = 1.833) and multiple collisions (OR = 1.897) were higher than in frontal collision. Furthermore, the probability of TBI in the elderly was 1.677 times higher in those with unfastened seatbelts compared to those with fastened seatbelts (OR = 1.677). This study was meaningful in that it incorporated several indicators that affected the occurrence of the TBI in the elderly occupants. In addition, it was performed to determine the probability of TBI according to sex, vehicle type, seating position, seatbelt status, collision type, and crush extent using logistic regression analysis. In order to derive more precise predictive models, it would be needed to analyze more factors for vehicle damage, environment, and occupant injury in future studies.

Analysis of HIC and Hydrostatic Pressure in the Human Head during NOCSAE Tests of American Football Helmets

Brain damage is a serious economic and social burden. Contact sports such as American football, are one of the most common sources of concussions. The biomechanical response of the head-helmet system caused by dynamic loading plays a major role. The literature has focused on measuring the resultant kinematics that act on the head and helmet during tackles. However, few studies have focused on helmet validation tests, supported by recent findings and emerging numerical approaches. The future of helmet standards could benefit from insights at the level of injury mechanisms, using numerical tools to assess the helmets. Therefore, in this work, a numerical approach is employed to investigate the influence of intracranial pressure (ICP) on brain pathophysiology during and after helmeted impacts, which are common in American football. The helmeted impacts were performed at several impact locations according to the NOCSAE standard (configurations A, AP, B, C, D, F, R, UT). In order to evaluate the ICP levels, the αHEAD finite element head and brain model was combined with a Hybrid III-neck structure and then coupled with an American football helmet to simulate the NOCSAE impacts. In addition, the ICP level was analyzed together with the resulting HIC value, since the latter is commonly used, in this application and others, as the injury criterion. The obtained results indicate that ICP values exceed the common threshold of head injury criteria and do not correlate with HIC values. Thus, this work raises concern about applying the HIC to predict brain injury in American football direct head impacts, since it does not correlate with ICP predicted with the FE head model.

Injury Biomechanics of a Child’s Head: Problems, Challenges and Possibilities with a New aHEAD Finite Element Model

Traumatic brain injury (TBI) is a major public health problem among children. The predominant causes of TBI in young children are motor vehicle accidents, firearm incidents, falls, and child abuse. The limitation of in vivo studies on the human brain has made the finite element modelling an important tool to study brain injury. Numerical models based on the finite element approach can provide valuable data on biomechanics of brain tissues and help explain many pathological conditions. This work reviews the existing numerical models of a child’s head. However, the existing literature is very limited in reporting proper geometric representation of a small child’s head. Therefore, an advanced 2-year-old child’s head model, named aHEAD 2yo (aHEAD: advanced Head models for safety Enhancement And medical Development), has been developed, which advances the state-of-the-art. The model is one of the first published in the literature, which entirely consists of hexahedral elements for three-dimensional (3D) structures of the head, such as the cerebellum, skull, and cerebrum with detailed geometry of gyri and sulci. It includes cerebrospinal fluid as Smoothed Particle Hydrodynamics (SPH) and a detailed model of pressurized bringing veins. Moreover, the presented review of the literature showed that material models for children are now one of the major limitations. There is also no unambiguous opinion as to the use of separate materials for gray and white matter. Thus, this work examines the impact of various material models for the brain on the biomechanical response of the brain tissues during the mechanical loading described by Hardy et al. The study compares the inhomogeneous models with the separation of gray and white matter against the homogeneous models, i.e., without the gray/white matter separation. The developed model along with its verification aims to establish a further benchmark in finite element head modelling for children and can potentially provide new insights into injury mechanisms.

Development of an Eco-Friendly Head Impact Protection Device

Nowadays, the number of people practising contact sports has increased. In many of them, using head protective equipment is not mandatory, even if the use of headbands could increase the level of safety regarding several types of traumatic brain injuries. Many commercial solutions are currently available, based on plastic-based foams providing a decent level of protection and comfort to the user. This work introduces the use of agglomerated cork as an eco-friendly alternative to synthetic foams but at least keeping safety levels. Cork is a natural cellular material that has been showing excellent crashworthiness properties. In this study, cork agglomerate density is carefully chosen to be incorporated into a protective headband. Results are compared against three other commercial headbands. For each one, the risk of brain injury was analysed for different injury thresholds and impact energies. The results clearly demonstrate that the cork-based apparel may provide comparable, and in some cases, better performances, outlasting the commercial ones.

Certified Motorcycle Helmets: Computational Evaluation of the Efficacy of Standard Requirements with Finite Element Models

Every year, thousands of people die in the European Union as a direct result of road accidents. Helmets are one of the most important types of personal safety gear. The ECE R22.05 standard, adopted in 2000, is responsible for the certification of motorcycle helmets in the European Union and in many other countries. Two decades later, it is still being used with the same requirements, without any update. The aim of this work is to evaluate the efficacy of a motorcycle helmet certified by such standard, using computational models as an assessment tool. First, a finite element model of a motorcycle helmet available on the market was developed and validated by simulating the same impacts required by the standard. Then, a finite element model of the human head is used as an injury prediction tool to assess its safety performance. Results indicate a significant risk of brain injury, which is in accordance with previous studies available in the literature. Therefore, this work underlines and emphasizes the need of improving the requirements of ECE R22.05.

Method to Assess and Enhance Vulnerable Road User Safety during Impact Loading

Every year approximately 1.35 million people die as a consequence of road accidents. Almost 50% of road fatalities are vulnerable road users (VRUs). This research reviews the history of traffic safety for VRUs, presents an interesting insight into the statistics and evaluates the current legislation in Europe for pedestrians, cyclists, children on bicycle-mounted seats and motorcyclists in terms of impact situations and applied criteria. This enabled the author to have a better perspective on how the VRUs’ safety is currently verified. Furthermore, the VRU safety requirements are contrasted with the author’s research, which is mainly focused on VRU’s head biomechanics and kinematics. Finally, a new coherent method is presented, which encompasses the sub-groups of VRUs and proposes some improvements to both the regulations as well as technical countermeasures to mitigate the injuries during an impact. This study highlights the importance of numerical methods, which can serve as a powerful tool to study VRUs’ head injuries and kinematics.

Detection of bridging veins rupture and subdural haematoma onset using a finite element head model

BACKGROUND

One of the most severe traumatic brain injuries, the subdural haematoma, is related to damage and rupture of the bridging veins, generating an abnormal collection of blood between the dura mater and arachnoid mater. Current numerical models of these vessels rely on very simple geometries and material laws, limiting its accuracy and bio-fidelity.

METHODS

In this work, departing from an existing human head numerical model, a realistic geometry for the bridging veins was developed, devoting special attention to the finite elements type employed. A novel and adequate constitutive model including damage behavior was also successfully implemented.

FINDINGS

Results attest that vessel tearing onset was correctly captured, after comparison against experiments on cadavers.

INTERPRETATION

Doing so, the model allow to precisely predict the individual influence of kinematic parameters such as the pulse duration, linear and rotational accelerations in promoting vessel tearing.

Development and Testing of Advanced Cork Composite Sandwiches for Energy-Absorbing Structures

Cork is a sustainable material with remarkable properties. In addition to its main application as wine stoppers, it has also been employed as a sound and thermal insulator in facades, building roofs, aeronautical applications, and, more recently, in impact energy absorption systems. In its natural form, cork is mainly used in wine stopper manufacturing, but for other applications, cork compounds are usually employed, which makes it possible to manufacture complex geometries with nearly isotropic behavior. In this work, an attempt was made to merge the desirable properties of two different cork materials (agglomerated and expanded black) into cork composite sandwich structures. These structures were tested according to impact conditions typically experienced by energy-absorbing liners used in personal safety devices. Additionally, the performance dependency on the working temperature was analyzed. The sole black, expanded cork (EC159) and agglomerated cork (AC199A and AC216) were tested in 500 J impacts. It was found that black cork was characterized by superior thermal stability, while expanded cork allowed absorbing high energies. In the second stage, the composites consisting of both tested materials were tested in 100 J impact scenarios. The combination of two materials of different properties enabled reduction of the peak force exerted on a helmet user’s head during the impact by about 10% compared to agglomerated specimens. Additionally, it was proved that there was no influence of the glue used to join different cork types.

Helmet Design Based on the Optimization of Biocomposite Energy-Absorbing Liners under Multi-Impact Loading

Cellular materials have been used in many applications such as insulation, packaging, and protective gear. Expanded polystyrene has been widely used as energy-absorbing liner in helmets due to its excellent cost-benefit relation. This synthetic material can absorb reasonable amounts of energy via permanent deformation. However, in real-world accidents, helmets may be subjected to multi-impact scenarios. Additionally, oil-derived plastic is presently a major source of societal concern regarding pollution and waste. As a sustainable alternative, cork is a natural cellular material with great crashworthiness properties and it has the remarkable capacity to recover after compression, due to its viscoelastic behavior, which is a desired characteristic in multi-impact applications. Therefore, the main goal is to analyze the applicability of agglomerated cork as padding material in safety helmets. First, a finite element model of a motorcycle helmet available on the market was developed to assess its safety performance and to establish a direct comparison between expanded polystyrene and cork agglomerates as liners. Secondly, a new helmet model with a generic geometry was developed to assess the applicability of agglomerated cork as liner for different types of helmets, based on the head injury risk predictions by the finite element head model, YEt Another Head Model (YEAHM), developed by the authors. Several versions of helmet liners were created by varying its thickness and removing sections of material. In other words, this generic helmet was optimized by carrying out a parametric study, and by comparing its performance under double impacts. The results from these tests indicate that agglomerated cork liners are an excellent alternative to the synthetic ones. Thus, agglomerated cork can be employed in protective gear, improving its overall performance and capacity to withstand multi-impacts.

The development of a threshold curve for the understanding of concussion in sport

Much of what is known concerning human brain injury thresholds is based upon impacts to cadavers and animal models that were used to generate the Wayne State Concussion Tolerance Curve (WSTC) and similar curves. These curves are the foundation for predictive metrics used in standard development as well as helmet design. These curves were based upon a very narrow range of impacts; impacts whose characteristics differ greatly from how the head is impacted in sport. This research examines the uses of time-based curves like the WSTC in the context of understanding mechanisms of brain injury and head protection. Published linear/rotational acceleration magnitude/duration data from Hybrid III laboratory reconstructions of brain injury events were plotted. This research further develops the understanding of injury thresholds in comparison to threshold curves such as the WSTC and Brain Injury Curve Leuven. The data demonstrate the relationships between magnitude and duration of dynamic response on minor traumatic brain injury (mTBI) in sport.

Traumatic brain injury in pedestrian-vehicle collisions: Convexity and suitability of some functionals used as injury metrics

BACKGROUND AND OBJECTIVE

Abrupt accelerations or decelerations can cause large strain in brain tissues and, consequently, different forms of Traumatic Brain Injury (TBI). In order to predict the effect of the accelerations on the soft tissues of the brain, many different injury metrics have been proposed (typically, an injury metric is a real valued functional of the accelerations). The objective of this article is to make a formal and empirical comparison, in order to identify general criteria for reasonable injury metrics, and propose a general guideline to avoid ill-proposed injury metrics.

METHODS

A medium-sized sample of vehicle-pedestrian collisions, from Post Mortem Human Subject (PMHS) tests, is analyzed. A statistical study has been conducted in order to determine the discriminant power of the usual metrics. We use Principal Component Analysis to reduce dimensionality and to check consistency among the different metrics. In addition, this article compares the mathematical properties of some of these functionals, trying to identify the desirable properties that any of those functionals needs to fulfill in order to be useful for optimization.

RESULTS

We have found a pair-wise consistency of all the currently used metrics (any two injury metrics are always positively related). In addition, we observed that two independent principal factors explain about 72.5% of the observed variance among all collision tests. This is remarkable because it indicates that despite high number of different injury metrics, a reduced number of variables can explain the results of all these metrics. With regard to the formal properties, we found that essentially all injury mechanisms can be accounted by means of scalable, differentiable and convex functionals (we propose to call minimization suitable injury metric any metric having these three formal properties). In addition three useful functionals, usable as injury metrics, are identified on the basis of the empirical comparisons.

CONCLUSIONS

The commonly used metrics are highly consistent, but also highly redundant. Formal minimal conditions of a reasonable injury metric has been identified. Future proposals of injury metrics can benefit from the results of this study.

Brain strain uncertainty due to shape variation in and simplification of head angular velocity profiles

Head angular velocity, instead of acceleration, is more predictive of brain strains. Surprisingly, no study exists that investigates how shape variation in angular velocity profiles affects brain strains, beyond characteristics such as peak magnitude and impulse duration. In this study, we evaluated brain strain uncertainty due to variation in angular velocity profiles and further compared with that resulting from simplifying the profiles into idealized shapes. To do so, we used reconstructed head impacts from American National Football League for shape extraction and simulated head uniaxial coronal rotations from onset to full stop. The velocity profiles were scaled to maintain an identical peak velocity magnitude and duration in order to isolate the shape for investigation. Element-wise peak maximum principal strains from 44 selected impacts were obtained. We found that the shape of angular velocity profile could significantly affect brain strain magnitude (e.g., percentage difference of 4.29-17.89 % in the whole brain relative to the group average, with cumulative strain damage measure (CSDM) uncertainty range of 23.9 %) but not pattern (correlation coefficient of 0.94-0.99). Strain differences resulting from simplifying angular velocity profiles into idealized shapes were largely within the range due to shape variation, in both percentage difference and CSDM (signed difference of 3.91 % on average, with a typical range of 0-6 %). These findings provide important insight into the uncertainty or confidence in the performance of kinematics-based injury metrics. More importantly, they suggest the feasibility to simplify head angular velocity profiles into idealized shapes, at least within the confinements of the profiles evaluated, to enable real-time strain estimation via pre-computation in the future.