Pedestrians are one of the least protected groups in urban traffic and frequently suffer fatal head injuries. An important boundary condition for the head is the cervical spine, and it has previously been demonstrated that neck muscle activation is important for head kinematics during inertial loading. It has also been shown in a recent numerical study that a tensed neck musculature also has some influence on head kinematics during a pedestrian impact situation. The aim of this study was to analyze the influence on head kinematics and injury metrics during the isolated time of head impact by comparing a pedestrian with relaxed neck and a pedestrian with increased tonus. The human body Finite Element model THUMS Version 1.4 was connected to head and neck models developed at KTH and used in pedestrian-to-vehicle impact simulations with a generalized hood, so that the head would impact a surface with an identical impact response in all simulations. In order to isolate the influence of muscle tonus, the model was activated shortly before head impact so the head would have the same initial position prior to impact among different tonus. A symmetric and asymmetric muscle activation scheme that used high level of activation was used in order to create two extremes to investigate. It was found that for the muscle tones used in this study, the influence on the strain in the brain was very minor, in general about 1-14% change. A relatively large increase was observed in a secondary peak in maximum strains in only one of the simulated cases. 

Finite element (FE) models are a powerful tool that can be used to understand injury mechanisms and develop better safety systems. This study aims to extend the understanding of pediatric spine biomechanics, where there is a paucity of studies available. A newly developed and continuously scalable FE model was validated and scaled to 1.5-, 3-, 6-, 10-, 14- and 18-year-old using a non-linear scaling technique, accounting for local topological changes. The oldest and youngest ages were also scaled using homogeneous geometric scaling. To study the effect of pediatric spinal growth on head kinematics and intervertebral disc strain, the models were exerted to 3.5 g acceleration pulse at the T1 vertebra to simulate frontal, rear and side impacts. It was shown that the head rotation increases with age, but is over predicted when geometrically scaling down from 18- to 1.5-year-old and under predicted when geometrically scaling up from 1.5- to 18-year-old. The strain in the disc, however, showed a clear decrease with age in side impact and for the upper cervical spine in rear impact, indicating a higher susceptibility for neck injury at younger ages. In the frontal impact, no clear age dependence could be seen, suggesting a large contribution from changed facet joint angles, and lower levels of strain, suggesting a lower risk of injury. The results also highlight the benefit of rearward facing children in a seat limiting head lateral motion.

Virtual testing of helmets using finite element (FE) analysis can be a valuable tool during product development. Still, its usefulness is limited by the quality of the constitutive model of the energy-absorbing material, usually foam. Built-in constitutive models in commercial FE software are developed for traditional linear compression loading. However, modern oblique test methods load the foam in combined compression and shear. Therefore, we aim to evaluate to what extent built-in constitutive models in commercial FE software can represent Expanded Polystyrene (EPS) foam during combined compression and shear loading (CCSL). EPS foam is tested experimentally in a newly developed test rig for CCSL (V-test). The response is compared against the simulation using three different constitutive models available in LS-DYNA (M83, M126, and M181). The models are assessed by their ability to capture the correct response, focusing on how well the continuum models can capture the phenomenological events seen in the experiments. The results show that the models perform well in compression, as expected. However, we point out limitations in the shear response and significant limitations in the unloading response, both important for oblique helmet testing. Due to these limitations, we conclude that the existing models are inadequate for accurately simulating oblique helmet impacts. There is a clear need to develop and implement new constitutive models focused on capturing CCSL including the unloading. Additionally, frictional sliding was found to substantially influence the measured response in the V-test method. Minimizing interface sliding is therefore critical for isolating the material behavior.

Photopolymerization is a key enabling technology offering spatial and temporal control to allow for future functional materials to be made to meet societal needs. However, gaining access to robust experimental techniques to describe the evolution of nanoscale morphology in photo-initiated polymeric systems has proven so far to be a challenging task. Here, we show that these physical transformations can be monitored and quantified at the nanoscale in situ and in real-time. It is demonstrated that the initial structural features of the liquid precursors significantly affect the final morphology and the physical properties of the resulting solid via the occurrence of local heterogeneities in the molecular mobility during the curing transformation. We have made visible how local physical arrestings in the liquid, associated with both cross-linking and vitrification, determine the length scale of the local heterogeneities forming upon curing, found to be in the 10-200nm range. Acomplete account of the structural evolution occurring during photopolymerisation is lacking. Here the physical changes occurring on the nanometer scale during photopolymerisation of acrylates are followed over time by FTIR, X-ray reflectometry, AFM, and GISAXS, offering insight into the mechanism by which initial composition influences the final morphology.

Work-related traumatic brain injuries (wrTBIs) in the construction industry have been studied in North America but, to the best of our knowledge, not in Europe. This study analyzed sets of public data on head injuries occurring in the construction industry from the workers' compensation systems in Sweden and Germany, 2014 - 2018. The ratio of wrTBI varied from 11% to 61% of all head injuries, with higher ratios for more severe injuries. The average yearly incidence (per 100,000 FTE) of wrTBI resulting in more than four days absence from work was nine in Sweden and 117 in Germany, as compared to 22-212 in North American studies. A limitation of studies based on workers' compensation claims is that they underestimate the true burden of wrTBI. The most frequent events leading to wrTBI were falls, followed by loss of control, failure of material agents, and body movements without stress. Falls from a height caused 35% of all wrTBI with more than 14 days off work in Sweden and 57% of all new injury pensions granted in Germany. In North American studies, 52-78% of the wrTBI were caused by falls. This highlights the relevance of fall safety measures to reduce wrTBI in the construction industry, such as avoiding work at heights, use of safety nets, education, and etcetera. The energy absorption of safety helmets mainly protects the head excluding face of which 49-62% were wrTBI, indicating that helmet testing standards should evaluate protection against TBI as well as skull fractures.

Repeated head impact exposure and concussions are common in American football. Identifying the factors associated with high magnitude impacts aids in informing sport policy changes, improvements to protective equipment, and better understanding of the brain’s response to mechanical loading. Recently, the Stanford Instrumented Mouthguard (MiG2.0) has seen several improvements in its accuracy in measuring head kinematics and its ability to correctly differentiate between true head impact events and false positives. Using this device, the present study sought to identify factors (e.g., player position, helmet model, direction of head acceleration, etc.) that are associated with head impact kinematics and brain strain in high school American football athletes. 116 athletes were monitored over a total of 888 athlete exposures. 602 total impacts were captured and verified by the MiG2.0’s validated impact detection algorithm. Peak values of linear acceleration, angular velocity, and angular acceleration were obtained from the mouthguard kinematics. The kinematics were also entered into a previously developed finite element model of the human brain to compute the 95th percentile maximum principal strain. Overall, impacts were (mean ± SD) 34.0 ± 24.3 g for peak linear acceleration, 22.2 ± 15.4 rad/s for peak angular velocity, 2979.4 ± 3030.4 rad/s2 for peak angular acceleration, and 0.262 ± 0.241 for 95th percentile maximum principal strain. Statistical analyses revealed that impacts resulting in Forward head accelerations had higher magnitudes of peak kinematics and brain strain than Lateral or Rearward impacts and that athletes in skill positions sustained impacts of greater magnitude than athletes in line positions. 95th percentile maximum principal strain was significantly lower in the observed cohort of high school football athletes than previous reports of collegiate football athletes. No differences in impact magnitude were observed in athletes with or without previous concussion history, in athletes wearing different helmet models, or in junior varsity or varsity athletes. This study presents novel information on head acceleration events and their resulting brain strain in high school American football from our advanced, validated method of measuring head kinematics via instrumented mouthguard technology.

The meninges are membranous tissues that are pivotal in maintaining homeostasis of the central nervous system. Despite the importance of the cranial meninges in nervous system physiology and in head injury mechanics, our knowledge of the tissues' mechanical behavior and structural composition is limited. This systematic review analyzes the existing literature on the mechanical properties of the meningeal tissues. Publications were identified from a search of Scopus, Academic Search Complete, and Web of Science and screened for eligibility according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The review details the wide range of testing techniques employed to date and the significant variability in the observed experimental findings. Our findings identify many gaps in the current literature that can serve as a guide for future work for meningeal mechanics investigators. The review identifies no peer-reviewed mechanical data on the falx and tentorium tissues, both of which have been identified as key structures in influencing brain injury mechanics. A dearth of mechanical data for the pia-arachnoid complex also was identified (no experimental mechanics studies on the human pia-arachnoid complex were identified), which is desirable for biofidelic modeling of human head injuries. Finally, this review provides recommendations on how experiments can be conducted to allow for standardization of test methodologies, enabling simplified comparisons and conclusions on meningeal mechanics.

Head injuries are among the most common injuries in motorcycle accidents, where the helmet is the main protection. Until recently, the test standards have only evaluated protection against linear impacts. Evaluating protection against rotational impacts has been recently introduced. The objective of this study was to evaluate how current motorcycle helmets perform in ECE R22.06 rotational impact tests. The rotational impact tests were performed on three helmet models and the linear impact tests were performed on one helmet model. All the helmets passed the rotational impact tests. The maximum value for the experimental tests was 4.5 krad/s2 for PRA and 0.48 for BrIC compared to the threshold values of 10.4 krad/s2 and 0.78. In the linear impact tests five out of twenty-two impact tests failed the threshold for peak linear acceleration or head injury criterion. The results from this study suggest that motorcycle helmets will be more optimised towards reducing linear-induced injuries and not rotational-induced injuries in the newly introduced test standard ECE R22.06. This is not responding to the protection requirements when evaluating the accident statistics, which shows that rotational-induced injuries are as common or even more common than linear-induced injuries in helmeted motorcycle accidents. 

Bicycle helmets are shown to offer protection against head injuries. Rating methods and test standards are used to evaluate different helmet designs and safety performance. Both strain-based injury criteria obtained from finite element brain injury models and metrics derived from global kinematic responses can be used to evaluate helmet safety performance. Little is known about how different injury models or injury metrics would rank and rate different helmets. The objective of this study was to determine how eight brain models and eight metrics based on global kinematics rank and rate a large number of bicycle helmets (n=17) subjected to oblique impacts. The results showed that the ranking and rating are influenced by the choice of model and metric. Kendall’s tau varied between 0.50 and 0.95 when the ranking was based on maximum principal strain from brain models. One specific helmet was rated as 2-star when using one brain model but as 4-star by another model. This could cause confusion for consumers rather than inform them of the relative safety performance of a helmet. Therefore, we suggest that the biomechanics community should create a norm or recommendation for future ranking and rating methods.

Playgrounds surface test standards have been introduced to reduce the number of fatal and severe injuries. However, these test standards have several simplifications to make it practical, robust and cost-effective, such as the head is represented with a hemisphere, only the linear kinematics is evaluated and the body is excluded. Little is known about how these simplifications may influence the test results. The objective of this study was to evaluate the effect of these simplifications on global head kinematics and head injury prediction for different age groups. The finite element human body model PIPER was used and scaled to seven different age groups from 1.5 up to 18 years old, and each model was impacted at three different playground surface stiffness and three head impact locations. All simulations were performed in pairs, including and excluding the body. Linear kinematics and skull bone stress showed small influence if excluding the body while head angular kinematics and brain tissue strain were underestimated by the same simplification. The predicted performance of the three different playground surface materials, in terms of head angular kinematics and brain tissue strain, was also altered when including the body. A body and biofidelic neck need to be included, together with suitable head angular kinematics based injury thresholds, in future physical or virtual playground surface test standards to better prevent brain injuries.

Finite element head models are a tool to better understand brain injury mechanisms. Many of the models use strain as output but with different percentile values such as 100th, 95th, 90th, and 50th percentiles. Some use the element value, whereas other use the nodal average value for the element. Little is known how strain post-processing is affecting the injury predictions and evaluation of different prevention systems. The objective of this study was to evaluate the influence of strain output on injury prediction and ranking.& nbsp;Two models with different mesh densities were evaluated (KTH Royal Institute of Technology head model and the Total Human Models for Safety (THUMS)). Pulses from reconstructions of American football impacts with and without a diagnosis of mild traumatic brain injury were applied to the models. The value for 100th, 99th, 95th, 90th, and 50th percentile for element and nodal averaged element strain was evaluated based on peak values, injury risk functions, injury predictability, correlation in ranking, and linear correlation.& nbsp;The injury risk functions were affected by the post-processing of the strain, especially the 100th percentile element value stood out. Meanwhile, the area under the curve (AUC) value was less affected, as well as the correlation in ranking (Kendall's tau 0.71-1.00) and the linear correlation (Pearson's r2 0.72-1.00). With the results presented in this study, it is important to stress that the same post-processed strain should be used for injury predictions as the one used to develop the risk function.

This study describes a method to identify laboratory test procedures and impact response requirements suitable for assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of the experimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility and relevance of the available experimental data. A weighted averaging procedure was chosen in order to consider different contributions from the various test conditions and target measurements based on experimental error. According to the quality criteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of response curves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time history response to the measured data. Optimization of the CORA global settings led to the recommendation of performing curve comparison on a fixed time interval of 0-30 ms for intracranial pressure and at least 0-40 ms for brain motion and deformation. The allowable maximum time shift was adjusted depending on the shape of the experimental curves (DMAX = 0.12 for intracranial pressure, DMAX = 0.40 for brain motion and DMAX = 0.25 for brain deformation). Finally, bigger penalization of ratings was assigned to curves with fundamentally incorrect shape compared to those having inaccuracies in amplitude or time shift (cubic vs linear). This rigorous approach is necessary to ensure confidence in the model results and progress in the usage of finite element head models for traumatic brain injury prediction. 

Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided. Logistic regression analysis is employed to compare binary injury data (concussion/no concussion) with continuous strain/kinematics data. The threshold corresponding to 50% of injury probability is determined for each parameter. The predictive power (area under the ROC curve, AUC) is calculated from receiver operating characteristic (ROC) curve analysis. The measure with the highest AUC is considered to be the best predictor of mTBI.Logistic regression shows a statistical correlation between all the mechanical predictors and injury data for different regions of the brain. Peaks of axonal strain have the highest AUC and determine a strain threshold of 0.07 for corpus callosum and 0.15 for the brainstem, in agreement with previously experimentally derived injury thresholds for reversible axonal injury. For a data set of mild TBI from the national football league, the strain in the axonal direction is found to be a better injury predictor than MPS, AESM, CSDM, BrIC and HIC. 

Communication sounds across all mammals consist of multiple frequencies repeated in sequence. The onset and offset of vocalizations are potentially important cues for recognizing distinct units, such as phonemes and syllables, which are needed to perceive meaningful communication. The superior paraolivary nucleus (SPON) in the auditory brainstem has been implicated in the processing of rhythmic sounds. Here, we compared how best frequency tones (BFTs), broadband noise (BBN), and natural mouse calls elicit onset and offset spiking in the mouse SPON. The results demonstrate that onset spiking typically occurs in response to BBN, but not. BFT stimulation, while spiking at the sound offset occurs for both stimulus types. This effect of stimulus bandwidth on spiking is consistent with two of the established inputs to the SPON from the octopus cells (onset spiking) and medial nucleus of the trapezoid body (offset spiking). Natural mouse calls elicit two main spiking peaks. The first spiking peak, which is weak or absent with BFT stimulation, occurs most consistently during the call envelope, while the second spiking peak occurs at the call offset. This suggests that the combined spiking activity in the SPON elicited by vocalizations reflects the entire envelope, that is, the coarse amplitude waveform. Since the output from the SPON is purely inhibitory, it is speculated that, at the level of the inferior colliculus, the broadly tuned first peak may improve the signal-to-noise ratio of the subsequent, more call frequency-specific peak. Thus, the SPON may provide a dual inhibition mechanism for tracking phonetic boundaries in social-vocal communication.

Post-mortem computed tomography (PMCT) enables the creation of subject-specific 3D head models suitable for quantitative analysis such as finite element analysis (FEA). FEA of proposed traumatic events is an objective and repeatable numerical method for assessing whether an event could cause a skull fracture such as seen at autopsy. FEA of blunt force skull fracture in adults with subject-specific 3D models in forensic pathology remains uninvestigated. This study aimed to assess the feasibility of FEA for skull fracture analysis in routine forensic pathology. Five cases with blunt force skull fracture and sufficient information on the kinematics of the traumatic event to enable numerical reconstruction were chosen. Subject-specific finite element (FE) head models were constructed by mesh morphing based on PMCT 3D models and A Detailed and Personalizable Head Model with Axons for Injury Prediction (ADAPT) FE model. Morphing was successful in maintaining subject-specific 3D geometry and quality of the FE mesh in all cases. In three cases, the simulated fracture patterns were comparable in location and pattern to the fractures seen at autopsy/PMCT. In one case, the simulated fracture was in the parietal bone whereas the fracture seen at autopsy/PMCT was in the occipital bone. In another case, the simulated fracture was a spider-web fracture in the frontal bone, whereas a much smaller fracture was seen at autopsy/PMCT; however, the fracture in the early time steps of the simulation was comparable to autopsy/PMCT. FEA might be feasible in forensic pathology in cases with a single blunt force impact and well-described event circumstances.

Featured Application: The results proposed a new approach to evaluate the protection effectiveness of energy-absorbing floors for fall-related injury prevention. Also, it could help to reduce the huge associated costs related to fall-related injuries among the children and elderly population. Energy-absorbing floor (EAF) has been proposed as one of several biomechanically effective strategies to mitigate the risk of fall-related injuries by decreasing peak loads and enhancing system energy absorption. This study aims to compare the protective capacity of four commercially available EAF products (Igelkott Floor, Kradal, SmartCells, and OmniSports) in terms of head impacts using the finite element (FE) method. The stress–strain curves acquired from mechanical tests were applied to material models in LS-Dyna. The established FE models were then validated using Hybrid III or hemispheric drop tests to compare the acceleration–time curves between experiments and simulations. Finally, the validated FE models were utilized to simulate a typical pedestrian fall accident scenario. It was demonstrated that EAFs can substantially reduce the peak forces, acceleration, and velocity changes during fall-related head impacts. Specifically, in the accident reconstruction scenario, SmartCells provided the largest reduction in peak linear acceleration and skull fracture risk, while Igelkott Floor provided the largest reduction in peak angular velocity and concussion risk. This performance was caused by different energy absorption mechanisms. Consequently, the results can contribute to supporting the implementation of EAFs and determine the effectiveness of various protective strategies for fall-related head injury prevention.

Developing vehicle finite element (FE) models that match real accident-involved vehicles is challenging. This is related to the intricate variety of geometric features and components. The current study proposes a novel method to efficiently and accurately generate case-specific buck models for car-to-pedestrian simulations. To achieve this, we implemented the vehicle side-view images to detect the horizontal position and roundness of two wheels to rectify distortions and deviations and then extracted the mid-section profiles for comparative calculations against baseline vehicle models to obtain the transformation matrices. Based on the generic buck model which consists of six key components and corresponding matrices, the case-specific buck model was generated semi-automatically based on the transformation metrics. Utilizing this image-based method, a total of 12 vehicle models representing four vehicle categories including family car (FCR), Roadster (RDS), small Sport Utility Vehicle (SUV), and large SUV were generated for car-to-pedestrian collision FE simulations in this study. The pedestrian head trajectories, total contact forces, head injury criterion (HIC), and brain injury criterion (BrIC) were analyzed comparatively. We found that, even within the same vehicle category and initial conditions, the variation in wrap around distance (WAD) spans 84–165 mm, in HIC ranges from 98 to 336, and in BrIC fluctuates between 1.25 and 1.46. These findings highlight the significant influence of vehicle frontal shape and underscore the necessity of using case-specific vehicle models in crash simulations. The proposed method provides a new approach for further vehicle structure optimization aiming at reducing pedestrian head injury and increasing traffic safety.

Falls among the elderly cause a huge number of hip fractures worldwide. Energy absorbing floors (EAFs) represent a promising strategy to decrease impact force and hip fracture risk during falls. Femoral neck force is an effective predictor of hip injury. However, the biomechanical effectiveness of EAFs in terms of mitigating femoral neck force remains largely unknown. To address this, a whole-body computational model representing a small-size elderly woman with a biofidelic representation of the soft tissue near the hip region was employed in this study, to measure the attenuation in femoral neck force provided by four commercially available EAFs (Igelkott, Kradal, SmartCells, and OmniSports). The body was positioned with the highest hip force with a -10 degrees trunk angle and +10 degrees degrees anterior pelvis rotation. At a pelvis impact velocity of 3 m/s, the peak force attenuation provided by four EAFs ranged from 5% to 19%. The risk of hip fractures also demonstrates a similar attenuation range. The results also exhibited that floors had more energy transferred to their internal energy demonstrated greater force attenuation during sideways falls. By comparing the biomechanical effectiveness of existing EAFs, these results can improve the floor design that offers better protection performance in high-fall-risk environments for the elderly.

Finite element (FE) modeling provides a means to examine how global kinematics of repetitive head loading in sports influences tissue level injury metrics. FE simulations of controlled soccer headers in two directions were completed using a human head FE model to estimate biomechanical loading on the brain by direction. Overall, headers were associated with 95th percentile peak maximum principal strains up to 0.07 and von Mises stresses up to 1450 Pa, and oblique headers trended toward higher values than frontal headers but below typical injury levels. These quantitative data provide insight into repetitive loading effects on the brain.

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. 

3D printing has been applied in the fabrication of Ti-6Al-4V implants due to its high processing efficiency and flexibility. However, the biological inertness of 3D-printed Ti-6Al-4V implant surface limits its further clinical application. This paper aims to improve the biocompatibility of 3D-printed Ti-6Al-4V implants through multi-scale composite structure and bioactive coating. The samples are prepared by selective laser melting (SLM). The multi-scale composite structure is constructed by acid etching and anodic oxidation, and then the bioactive coating is added by hydrothermal treatment. The results indicate that acid etching removes the residuals on the surface and builds micron-/sub-micron structures. Anodic oxidation superimposes TiO2 nanotube arrays with a diameter of ≈80 nm, forming the multi-scale composite structure. The polydopamine-magnesium ion coating is added by hydrothermal treatment on the basis of retaining the multi-scale composite structure. After modification, the surface wettability and corrosion resistance are improved, and the roughness is slightly reduced. Regarding the biocompatibility of the modified 3D-printed Ti-6Al-4V implant, its admirable osteogenic induction performance is verified on osteoblasts (MC3T3-E1). Also, the addition of magnesium ions achieves better antibacterial properties. The results provide new target points for the surface modification of 3D-printed Ti-6Al-4V implant to attain better clinical performance. 

Titanium and its alloys have been widely used in bone tissue defect treatment owing to their excellent comprehensive properties. However, because of the biological inertness of the surface, it is difficult to achieve satisfactory osseointegration with the surrounding bone tissue when implanted into the body. Meanwhile, an inflammatory response is inevitable, which leads to implantation failure. Therefore, solving these two problems has become a new research hotspot. In current studies, various surface modification methods were proposed to meet the clinical needs. Yet, these methods have not been classified as a system to guide the follow-up research. These methods are demanded to be summarized, analyzed, and compared. In this manuscript, the effect of physical signal regulation (multi-scale composite structure) and chemical signal regulation (bioactive substance) generated by surface modification in promoting osteogenesis and reducing inflammatory responses was generalized and discussed. Finally, from the perspective of material preparation and biocompatibility experiments, the development trend of surface modification in promoting titanium implant surface osteogenesis and anti-inflammatory research was proposed.

Acute subdural hematoma (ASDH) is one of the most frequent traumatic brain injuries (TBIs) with high mortality rate. Bridging vein (BV) ruptures is a major cause of ASDH. The KTH finite element head model includes bridging veins to predict acute subdural hematoma due to BV rupture. In this model, BVs were positioned according to Oka et al. (1985). The aim of the current study is to investigate whether the location and entry angles of these BVs could be modelled using data from a greater statistical sample, and what the impact of this improvement would be on the model's predictive capability of BV rupture. From the CT angiogram data of 78 patients, the relative position of the bridging veins and their entry angles along the superior sagittal sinus was determined. The bridging veins were repositioned in the model accordingly. The performance of the model, w.r.t. BV rupture prediction potential was tested on simulations of full body cadaver head impact experiments. The experiments were simulated on the original version of the model and on three other versions which had updated BV positions according to mean, maximum and minimum entry angles. Even though the successful prediction rate between the models stayed the same, the location of the rupture site significantly improved for the model with the mean entry angles. Moreover, the models with maximum and minimum entry angles give an insight of how BV biovariability can influence ASDH. In order to further improve the successful prediction rate, more biofidelic data are needed both with respect to bridging vein material properties and geometry. Furthermore, more experimental data are needed in order to investigate the behaviour of FE head models in depth.

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 low shear modulus and nearly incompressible properties of brain tissue make it to deform primarily in shear for a given impact. This gives a large sensitivity of the brain to rotational loading and a small sensitivity to linear kinematics. Therefore, rotational kinematics is the best indicator of TBI risk. A radial impact, such as in fall accidents, causes substantially higher stresses in the skull with an associated higher risk of skull fractures and TBIs secondary to those impacts.

Falls among the elderly cause a huge number of hip fractures world-wide. The objective is to generate hip fracture force risk functions for elderly women and men in sideways falls which can be used for determining effectiveness of fall prevention measures as well as for individual assessment of fracture risk at the clinics. A literature survey was performed and ten publications were identified who contained several hundred individual femoral neck fracture forces in sideways fall for both elderly women and men. Theoretical distributions were tested for goodness of fit against the pooled dataset with the Anderson-Darling test (AD-test) and root mean square errors (RMSE) were extracted. According to the AD-test, a Weibull distribution is a plausible model for the distribution of hip fracture forces. A simple, exponential two-parameter Weibull function was therefore proposed, having a RMSE below 2.2% compared to the experimental distribution for both men and women. It was demonstrated that elderly women only can endure nearly half the proximal femur force for 5 and 10% fracture risk as elderly men. It should be noted though, that women were found to have significantly lesser body height and body weight which would produce less impact force during falls from standing height. The proposed sex-specific hip fracture risk functions can be used for biomechanically optimizing hip protectors and safety floors and for determining their effectiveness as a fall prevention measure.

Whole-body models are historically developed for traffic injury prevention, and they are positioned accordingly in the standing or sitting configuration representing pedestrian or occupant postures. Those configurations are appropriate for vehicle accidents or pedestrian-vehicle accidents; however, they are uncommon body posture during a fall accident to the ground. This study aims to investigate the influence of trunk and pelvis angles on the proximal femur forces during sideways falls. For this purpose, a previously developed whole-body model was positioned into different fall configurations varying the trunk and pelvis angles. The trunk angle was varied in steps of 10 degrees from 10 to 80 degrees, and the pelvis rotation was changed every 5 degrees from -20 degrees (rotation toward posterior) to +20 degrees (rotation toward anterior). The simulations were performed on a medium-size male (177 cm, 76 kg) and a small-size female (156 cm, 55 kg), representative for elderly men and women, respectively. The results demonstrated that the highest proximal femur force measured on the femoral head was reached when either male or female model had a 10-degree trunk angle and +10 degrees anterior pelvis rotation.

Whole-body models are historically developed for traffic injury prevention, and they are positioned accordingly in the standing or sitting configurations representing pedestrian or occupant postures. Those configurations are appropriate for vehicle accidents or pedestrian-vehicle accidents; however, they are uncommon body posture during a fall accident to the ground. This study aims to investigate the influence of trunk and pelvis angles on the proximal femur forces during sideways falls. For this purpose, a previously developed whole-body model was positioned into different fall configurations varying the trunk and pelvis angles. The trunk angle was varied in steps of 10 degrees from 10 to 80 degrees, and the pelvis rotation was changed every 5 degrees from -20 degrees (rotation toward posterior) to +20 degrees (rotation toward anterior). The simulations were performed on a medium-size male (177 cm, 76 kg) and a small-size female (156 cm, 55 kg), representative for elderly men and women, respectively. The results demonstrated that the highest proximal femur force measured on the femoral head was reached when either male or female model had a 10-degree trunk angle and +10 degree anterior pelvis rotation.

Bridging veins (BV) rupture is a major cause of Acute Subdural Hematoma. This study aims to quantify their biovariability to better understand their properties and increase the biofidelity of finite element (FE) head models. The number of BV and their measured diameters were manually counted in CT angiograms from 67 patients. A mixed linear model was used for the statistical analysis and the results were implemented in the KTH FE head model. LS-DYNA simulations were used to evaluate the amount of successful BV rupture predictions. The false positive and false negative predictions were also counted. The human brain has a mean of 23,18 BV, with diameters ranging between 0,37 and 3,24 mm. In the initial version of the KTH model two BV mechanical properties datasets gave a 6/8 successful prediction rate with one false positive and one false negative and one dataset gave a 7/8 successful prediction rate with one false negative. For the updated version all sets gave a 7/8 successful prediction rate with one false negative. The number of BV and BV diameter size is segment dependent, but not hemisphere dependent. The implementation of these findings in the FE head model is a good preliminary attempt to increase BV rupture predictability.

Bridging veins (BV) rupture is a major cause of Acute Subdural Hematoma. This study aims to quantify their biovariability to better understand their properties and increase the biofidelity of finite element (FE) head models. The number of BV and their measured diameters were manually counted in CT angiograms from 67 patients. A mixed linear model was used for the statistical analysis and the results were implemented in the KTH FE head model. LS-DYNA simulations were used to evaluate the amount of successful BV rupture predictions. The false positive and false negative predictions were also counted. The human brain has a mean of 23,18 BV, with diameters ranging between 0,37 and 3,24 mm. In the initial version of the KTH model two BV mechanical properties datasets gave a 6/8 successful prediction rate with one false positive and one false negative and one dataset gave a 7/8 successful prediction rate with one false negative. For the updated version all sets gave a 7/8 successful prediction rate with one false negative. The number of BV and BV diameter size is segment dependent, but not hemisphere dependent. The implementation of these findings in the FE head model is a good preliminary attempt to increase BV rupture predictability.

Although concussion is one of the greatest health challenges today, our physical understanding of the cause of injury is limited. In this Letter, we simulated football head impacts in a finite element model and extracted the most dominant modal behavior of the brain’s deformation. We showed that the brain’s deformation is most sensitive in low frequency regimes close to 30 Hz, and discovered that for most subconcussive head impacts, the dynamics of brain deformation is dominated by a single global mode. In this Letter, we show the existence of localized modes and multimodal behavior in the brain as a hyperviscoelastic medium. This dynamical phenomenon leads to strain concentration patterns, particularly in deep brain regions, which is consistent with reported concussion pathology.

Finite element (FE) head models have become powerful tools in many fields within neuroscience, especially for studying the biomechanics of traumatic brain injury (TBI). Subject-specific head models accounting for geometric variations among subjects are needed for more reliable predictions. However, the generation of such models suitable for studying TBIs remains a significant challenge and has been a bottleneck hindering personalized simulations. This study presents a personalization framework for generating subject-specific models across the lifespan and for pathological brains with significant anatomical changes by morphing a baseline model. The framework consists of hierarchical multiple feature and multimodality imaging registrations, mesh morphing, and mesh grouping, which is shown to be efficient with a heterogeneous dataset including a newborn, 1-year-old (1Y), 2Y, adult, 92Y, and a hydrocephalus brain. The generated models of the six subjects show competitive personalization accuracy, demonstrating the capacity of the framework for generating subject-specific models with significant anatomical differences. The family of the generated head models allows studying age-dependent and groupwise brain injury mechanisms. The framework for efficient generation of subject-specific FE head models helps to facilitate personalized simulations in many fields of neuroscience.

Playground-related traumatic brain injuries (TBIs) in children remain a considerable problem world-wide and current safety standards are being questioned due to historical reasons where the injury thresholds had been perpetuated from automobile industry. Here we investigated head injury mechanisms due to falls on playgrounds using a previously developed and validated age-scalable and positionable whole body child model impacted at front, back and side of the head simulating head-first falls from 1.59 meters (m). The results show that a playground material passing the current testing standards (HIC < 1000 and resultant linear acceleration <200g) resulted in maximum strain in the brain higher than known injury thresholds, thus not offering sufficient protection especially for younger children. The analysis highlights the age dependence of head injuries in children due to playground falls and the youngest have a higher risk of brain injury and skull fracture. Further, the results provide the first biomechanical evidence guiding age-dependent injury thresholds for playground testing standards. The results also have direct implications for novel designs of playground materials for a better protection of children from TBIs. Only making the playground material thicker and more compliant is not sufficient. This study represents the first initiative of using full body human body models of children as a new tool to improve playground testing standards and to better protect the children at playgrounds.

Abusive Head Trauma (AHT) is considered by some authors to be a leading cause of traumatic death in children less than two years of age and skull fractures are commonly seen in cases of suspected AHT. Today, diagnosing whether the observed fractures are caused by abuse or accidental fall is still a challenge within both the medical and the legal communities and the central question is a biomechanical question: can the described history explain the observed fractures? Finite element (FE) analysis has been shown a valuable tool for biomechanical analysis accounting for detailed head geometry, advanced material modelling, and case-specific factors (e.g. head impact location, impact surface properties). Here, we reconstructed two well-documented suspected abuse cases (a 3- and a 4-month-old) using subject-specific FE head models. The models incorporate the anatomical details and age-dependent anisotropic material properties of infant cranial bones that reflect the grainy fibres radiating from ossification centres. The impact locations are determined by combining multimodality images. The results show that the skull fracture patterns in both cases of suspected abuse could be explained by the described accidental fall history, demonstrating the inherent potential of FE analysis for providing biomechanical evidence to aid forensic investigations. Increased knowledge of injury mechanisms in children may have enormous medico-legal implications world-wide. 

Decompressive craniectomy (DC) is a reliable neurosurgical approach to reduce a pathologically increased intracranial pressure after neurological diseases such as severe traumatic brain injury (TBI) and stroke. The procedure has substantially reduced the mortality rate but at the expense of increased neurological cognitive impairments. Finite Element (FE) modeling in the past decades has become an important tool to develop innovative treatment strategies in various areas of the clinical neuroscience field. The aim of this study was to develop patient-specific FE models to simulate DC surgery and validate the models against patients' clinical data. The FE models were created based on the Computed Tomography (CT) images of six patients treated with DC. Brain tissue was modeled as poroelastic material. To validate the model prediction, the motion of brain surface at the DC area from the simulation was compared with the measured values from medical images which were derived from image registration. The results from the computational simulations gave a reliable prediction of brain surface motion at DC area for all the six patients evaluated. Both the deformation pattern and the quantitative values of the brain surface displacement from the model simulation were found in good agreement with measured values from medical images. The developed FE model and its validation in this study is a prerequisite for future investigations aiming at finding optimal treatment for a specific patient which hopefully will significantly improve patients' outcome.

The anatomy of children’s heads is unique and distinct from adults, with smaller and softer skulls and unfused fontanels and sutures. Despite this, most current helmet testing standards for children use the same peak linear acceleration threshold as for adults. It is unclear whether this is reasonable and otherwise what thresholds should be. To answer these questions, helmet-protected head responses for different ages are needed which is however lacking today. In this study, we apply continuously scalable PIPER child head models of 1.5, 3, and 6 years old (YO), and an upgraded 18YO to study child helmet protection under extensive linear and oblique impacts. The results of this study reveal an age-dependence trend in both global kinematics and tissue response, with younger children experiencing higher levels of acceleration and velocity, as well as increased skull stress and brain strain. These findings indicate the need for better protection for younger children, suggesting that youth helmets should have a lower linear kinematic threshold, with a preliminary value of 150g for 1.5-year-old helmets. However, the results also show a different trend in rotational kinematics, indicating that the threshold of rotational velocity for a 1.5YO is similar to that for adults. The results also support the current use of small-sized adult headforms for testing child helmets before new child headforms are available.