Figure - available from: Frontiers in Bioengineering and Biotechnology
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Illustration of the biomechanics of an oblique impact (lower), compared to a corresponding perpendicular one (upper), when impacted against the same padding using an identical initial velocity of 6.7 m/s. Maximum principal strain (Green-Lagrange) at maximum for the brain are illustrated together with the maximum von Mises stress for the skull bone. Parts of the figure are modified from Kleiven (2007a).
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Injury statistics have found the most common accident situation to be an oblique impact. An oblique impact will give rise to both linear and rotational head kinematics. The human brain is most sensitive to rotational motion. The bulk modulus of brain tissue is roughly five to six orders of magnitude larger than the shear modulus so that for a given...
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Mild traumatic brain injury (mTBI, also known as concussion) caused by the head impact is a crucial global public health problem, but the physics of mTBI is still unclear. During the impact, the rapid movement of the head injures the brain, so researchers have been endeavoring to investigate the relationship between head kinematic parameters (e.g.,...
Citations
... However, existing helmet testing standards all focused on direct impacts with pass/fail criteria based on linear motion-related metrics (e.g., PLA, Head Injury Criterion (HIC)). Considering the prevalence of oblique impacts in real-life bicycle accidents [9] and the primary role of angular motion in brain injury mechanics [10,11], several consortiums, such as the CEN Technical Committee 158 Working Group 11 in Europe, strived to improve the test standard by involving oblique impact scenarios (e.g., collisions against an angled surface) and angular motionrelated metrics [e.g., peak angular velocity (PAV)] as the pass/fail threshold [12,13]. Although multiple pilot bicycle helmet rating programs with oblique impacts [14][15][16][17][18][19][20][21] have been proposed, none of them is officially involved in the testing standard yet. ...
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.
... In the current study, the rotational velocity values were similar to those in rollercoaster rides, and the rotational acceleration values were higher, suggesting that moderate levels of brain strain may occur during riding. These comparably higher levels of rotation are of concern as research has demonstrated that rotational accelerations correlate to brain strain, making them the primary mechanism for diffuse brain injury [53,54]. ...
The purpose of this longitudinal pilot study was to add to the body of research relating to head kinematics/vibration in sport and their potential to cause short-term alterations in brain function. In horseracing, due to the horse’s movement, repeated low-level accelerations are transmitted to the jockey’s head. To measure this, professional jockeys (2 male, 2 female) wore an inertial measurement unit (IMU) to record their head kinematics while riding out. In addition, a short battery of tests (Stroop, Trail Making Test B, choice reaction time, manual dexterity, and visual function) was completed immediately before and after riding. Pre- and post-outcome measures from the cognitive test battery were compared using descriptive statistics. The average head kinematics measured across all jockeys and days were at a low level: resultant linear acceleration peak = 5.82 ± 1.08 g, mean = 1.02 ± 0.01 g; resultant rotational velocity peak = 10.37 ± 3.23 rad/s, mean = 0.85 ± 0.15 rad/s; and resultant rotational acceleration peak = 1495 ± 532.75 rad/s2, mean = 86.58 ± 15.54 rad/s2. The duration of an acceleration event was on average 127.04 ± 17.22 ms for linear accelerations and 89.42 ± 19.74 ms for rotational accelerations. This was longer than those noted in many impact and non-impact sports. Jockeys experienced high counts of linear and rotational head accelerations above 3 g and 400 rad/s2, which are considered normal daily living levels (average 300 linear and 445 rotational accelerations per hour of riding). No measurable decline in executive function or dexterity was found after riding; however, a deterioration in visual function (near point convergence and accommodation) was seen. This work lays the foundation for future large-scale research to monitor the head kinematics of riders, measure the effects and understand variables that might influence them.
... At the time of publication, current standards use metrics based on linear motion of the head to assess the safety of helmets. These metrics can assess the protection of helmets against head injuries caused by linear mechanisms, such as skull fractures and associated focal injuries, including extradural haematoma [21]. Rotational motion is also a known head injury mechanism, leading to diffuse brain injuries and hemorrhage [22][23][24]. ...
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/s ² ), 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.
... While the linear head motions affect the intracranial pressure response, the rotational head motions have a significant effect on the peak strains that develop in the brain. 19,[21][22][23][24][25] In this study, the bulkhead ATD had the largest MPS value (19%) compared with the desk ATD (12%) and bench ATD (5%). These MPS and MPSR values are largely dependent on the angular acceleration time history. ...
Assessing the survivability of, and potential injury to, a ship’s crew from underwater blast is crucial to understanding the operating capability of a military vessel following blast exposure. One form of injury that can occur and affect a crew member’s ability to perform tasks is traumatic brain injury (TBI). To evaluate the risk of TBI from underwater blasts, injury metrics based on linear head acceleration have traditionally been used. Although these metrics are popular given their ease of use, they do not provide a direct measure of the tissue-level biomechanical responses that have been shown to cause neuronal injury. Tissue-based metrics of injury, on the other hand, may provide more insight into the potential risk of brain injury. Therefore, in this study, we assess the risk of TBI from underwater blasts using tissue-based measures of injury, such as tissue strain, strain rate, and intracranial pressure, in addition to the more commonly used head acceleration-based injury metrics.
A series of computational simulations were performed using a detailed finite element (FE) head model to study how inertial loading of the head from underwater blast events translates to potential injury in the brain. The head kinematics loading conditions for the simulations were obtained directly from Floating Shock Platform (FSP) tests where 3 Anthropomorphic Test Devices (ATDs) were positioned at 3 shipboard locations (desk, bulkhead, and bench), and the head acceleration was directly measured. The effect of the position and orientation of the ATDs and the distance of the underwater blast from the FSP (20–50 ft) on the risk of brain injury were assessed from the FE analysis.
The head accelerations and estimated TBI risk from the underwater blasts highly depend on the positioning of the ATDs on the FSP and decrease in severity as the charge standoff distance is increased. The ATD that was seated at a desk had the largest peak linear head acceleration (77.5 g) and negative intracranial pressure (−51.8 kPa). In contrast, the ATD that was standing at a bulkhead had the largest computed 95th percentile maximum principal strain (19%) and strain rate (25 s−1) in the brain. For all tested conditions, none of the ATDs exceeded the Head Injury Criterion (HIC-15) threshold of 700 for serious or fatal brain injury; however, the predicted tissue strains of the bulkhead ATD at the 20-ft charge standoff distance were within the range of proposed strain thresholds for a 50% risk of concussive injury, which illustrates the added value of considering tissue-level measures in addition to head acceleration when evaluating brain injury risk.
In this work, we assessed the risk of brain injury from underwater blasts using an anatomically detailed subject-specific FE head model. Accurate assessment of the risk of TBI from underwater explosions is important to evaluate the potential injury risk to crew members from underwater blast events, and to guide the development of future injury mitigation strategies to maintain the safety of crew members on military ships.
... However, existing helmet testing standards all focused on direct impacts with pass/fail criteria based on linear motion-related metrics (e.g., PLA, Head Injury Criterion (HIC)). Considering the prevalence of oblique impacts in reallife bicycle accidents (Baker et al. 2023) and the primary role of angular motion in brain injury mechanics (King et al. 2003, Kleiven 2013, several consortiums, such as the CEN Technical Committee 158 Working Group 11 in Europe, strived to improve the test standard by involving oblique impact scenarios (e.g., collisions against an angled surface) and angular motion-related metrics (e.g., peak angular velocity (PAV)) as the pass/fail threshold (Halldin et al. 2001, Halldin et al. 2003, proposing multiple pilot bicycle helmet rating programmes (Mills and Gilchrist 2008, Dau et al. 2012, Hansen et al. 2013, Willinger et al. 2014, Klug et al. 2015, Stigson et al. 2017, Bland et al. 2020. ...
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 conditions. 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 type and impact condition affected the strain peaks. Interestingly, we noted that helmets did not alter strain distribution, except for one helmet under one specific impact condition. Moreover, our analyses revealed that helmet ranking outcome based on strain peaks was affected by the choice of injury metrics (Kendall 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.
... Jacobian, respectively, describes the material's shape and volume change, the shear modulus, power and bulk modulus describe are the material parameters. The bulk modulus describes the ability of the tissue to resist volume change, and is typically orders of magnitude higher than the shear modulus due to the incompressible nature of water in the brain tissue (Kleiven 2013). A prior experimental mouse brain study conducted by MacManus et al. estimated the Ogden shear modulus µ and power a by calibrating the material properties of a simplified brain surface FEM to match experimental indentation tests performed on the cortex of mice (Macmanus et al. 2016). ...
Recent mouse brain injury experiments examine diffuse axonal injury resulting from accelerative head rotations. Evaluating brain deformation during these events would provide valuable information on tissue level thresholds for brain injury, but there are many challenges to imaging the brain’s mechanical response during dynamic loading events, such as a blunt head impact. To address this shortcoming, we present an experimentally validated computational biomechanics model of the mouse brain that predicts tissue deformation, given the motion of the mouse head during laboratory experiments. First, we developed a finite element model of the mouse brain that computes tissue strains, given the same head rotations as previously conducted in situ hemicephalic mouse brain experiments. Second, we calibrated the model using a single brain segment, and then validated the model based on the spatial and temporal strain responses of other regions. The result is a computational tool that will provide researchers with the ability to predict brain tissue strains that occur during mouse laboratory experiments, and to link the experiments to the resulting neuropathology, such as diffuse axonal injury.
... A recently developed paradigm, the closed-head impact model of engineered rotational acceleration (CHIMERA), simulates the mechanics of a closed-head injury occurring in humans by impacting an unrestrained head, allowing it to rotate freely [11]. This is critical to model a clinically relevant mTBI, as the human brain experiences significantly higher strain forces (deformation) in response to rotational acceleration than linear acceleration [12]. Post-concussive symptoms observed after mTBI fall into cognitive, physical, and emotional deficits [4]. ...
Mild traumatic brain injury (mTBI) affects millions of people in the U.S. Approximately 20–30% of those individuals develop adverse symptoms lasting at least 3 months. In a rat mTBI study, the closed-head impact model of engineered rotational acceleration (CHIMERA) produced significant axonal injury in the optic tract (OT), indicating white-matter damage. Because retinal ganglion cells project to the lateral geniculate nucleus (LGN) in the thalamus through the OT, we hypothesized that synaptic density may be reduced in the LGN of rats following CHIMERA injury. A modified SEQUIN (synaptic evaluation and quantification by imaging nanostructure) method, combined with immunofluorescent double-labeling of pre-synaptic (synapsin) and post-synaptic (PSD-95) markers, was used to quantify synaptic density in the LGN. Microglial activation at the CHIMERA injury site was determined using Iba-1 immunohistochemistry. Additionally, the effects of ketamine, a potential neuroprotective drug, were evaluated in CHIMERA-induced mTBI. A single-session repetitive (ssr-) CHIMERA (3 impacts, 1.5 joule/impact) produced mild effects on microglial activation at the injury site, which was significantly enhanced by post-injury intravenous ketamine (10 mg/kg) infusion. However, ssr-CHIMERA did not alter synaptic density in the LGN, although ketamine produced a trend of reduction in synaptic density at post-injury day 4. Further research is necessary to characterize the effects of ssr-CHIMERA and subanesthetic doses of intravenous ketamine on different brain regions and multiple time points post-injury. The current study demonstrates the utility of the ssr-CHIMERA as a rodent model of mTBI, which researchers can use to identify biological mechanisms of mTBI and to develop improved treatment strategies for individuals suffering from head trauma.
... Despite significant progress in the comprehension of the mechanisms underlying head injuries, there remains a knowledge gap regarding the exact impact that properties of brain material have on the severity of such injuries. Although the influence of impact force, angle, and velocity on resulting injuries is widely recognized, the intricate impact of variations in brain density and other material properties has received relatively less attention in the scientific literature [3,[16][17][18][19][20]. Addressing this gap is essential to improve our prediction and to develop effective countermeasures to mitigate the consequences of head impacts. ...
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.
... This study demonstrates that MOI differences between headforms can substantially influence rotational kinematics and that linear kinematics are more affected by the COF differences between headforms. This finding is important because of the relationship between rotational impact response and injury prediction [4,22,23,29,30]. However, this study cannot recommend a singular headform since it does not directly compare the biofidelity of each headform's impact response. ...
Helmet-testing headforms replicate the human head impact response, allowing the assessment of helmet protection and injury risk. However, the industry uses three different headforms with varying inertial and friction properties making study comparisons difficult because these headforms have different inertial and friction properties that may affect their impact response. This study aimed to quantify the influence of headform coefficient of friction (COF) and inertial properties on oblique impact response. The static COF of each headform condition (EN960, Hybrid III, NOCSAE, Hybrid III with a skull cap, NOCSAE with a skull cap) was measured against the helmet lining material used in a KASK prototype helmet. Each headform condition was tested with the same helmet model at two speeds (4.8 & 7.3 m/s) and two primary orientations (y-axis and x-axis rotation) with 5 repetitions, totaling 100 tests. The influence of impact location, inertial properties, and friction on linear and rotational impact kinematics was investigated using a MANOVA, and type II sums of squares were used to determine how much variance in dependent variables friction and inertia accounted for. Our results show significant differences in impact response between headforms, with rotational head kinematics being more sensitive to differences in inertial rather than frictional properties. However, at high-speed impacts, linear head kinematics are more affected by changes in frictional properties rather than inertial properties. Helmet testing protocols should consider differences between headforms’ inertial and frictional properties during interpretation. These results provide a framework for cross-comparative analysis between studies that use different headforms and headform modifiers.
... This behaviour is attributed to the high bulk modulus of the brain relative to its low shear modulus. Other studies (Kleiven, 2007;Kleiven, 2013;Hajiaghamemar et al., 2020;Carlsen et al., 2021) have supported this hypothesis, highlighting the importance of considering rotational kinematics when evaluating injury risk. Over time, various rotational-based metrics, such as DAMAGE and BrIC (Takhounts et al., 2013), have been introduced. ...
Mild traumatic brain injury (mTBI) may be caused by occupational hazards military personnel encounter, such as falls, shocks, exposure to blast overpressure events, and recoil from weapon firing. While it is important to protect against injurious head impacts, the repeated exposure of Canadian Armed Forces (CAF) service members to sub-concussive events during the course of their service may lead to a significant reduction in quality of life. Symptoms may include headaches, difficulty concentrating, and noise sensitivity, impacting how personnel complete their duties and causing chronic health issues. This study investigates how the exposure to the recoil force of long-range rifles results in head motion and brain deformation. Direct measurements of head kinematics of a controlled population of military personnel during firing events were obtained using instrumented mouthguards. The experimentally measured head kinematics were then used as inputs to a finite element (FE) head model to quantify the brain strains observed during each firing event. The efficacy of a concept recoil mitigation system (RMS), designed to mitigate loads applied to the operators was quantified, and the RMS resulted in lower loading to the operators. The outcomes of this study provide valuable insights into the magnitudes of head kinematics observed when firing long-range rifles, and a methodology to quantify effects, which in turn will help craft exposure guidelines, guide training to mitigate the risk of injury, and improve the quality of lives of current and future CAF service members and veterans.
