67 results found
Psarras S, Muñoz R, Ghajari M, 2023, Compression performance of composite plates after multi-site impacts: A combined experimental and finite element study, Composite Structures, Vol: 322, Pages: 117342-117342, ISSN: 0263-8223
Jones CM, Austin K, Augustus SN, et al., 2023, An instrumented mouthguard for real-time measurement of head kinematics under a large range of sport specific accelerations, Sensors, Vol: 23, Pages: 1-15, ISSN: 1424-8220
BACKGROUND: Head impacts in sports can produce brain injuries. The accurate quantification of head kinematics through instrumented mouthguards (iMG) can help identify underlying brain motion during injurious impacts. The aim of the current study is to assess the validity of an iMG across a large range of linear and rotational accelerations to allow for on-field head impact monitoring. METHODS: Drop tests of an instrumented helmeted anthropometric testing device (ATD) were performed across a range of impact magnitudes and locations, with iMG measures collected concurrently. ATD and iMG kinematics were also fed forward to high-fidelity brain models to predict maximal principal strain. RESULTS: The impacts produced a wide range of head kinematics (16-171 g, 1330-10,164 rad/s2 and 11.3-41.5 rad/s) and durations (6-18 ms), representing impacts in rugby and boxing. Comparison of the peak values across ATD and iMG indicated high levels of agreement, with a total concordance correlation coefficient of 0.97 for peak impact kinematics and 0.97 for predicted brain strain. We also found good agreement between iMG and ATD measured time-series kinematic data, with the highest normalized root mean squared error for rotational velocity (5.47 ± 2.61%) and the lowest for rotational acceleration (1.24 ± 0.86%). Our results confirm that the iMG can reliably measure laboratory-based head kinematics under a large range of accelerations and is suitable for future on-field validity assessments.
Baker CE, Yu X, Patel S, et al., 2023, A review of cyclist head injury, impact characteristics and the implications for helmet assessment methods, Annals of Biomedical Engineering, Vol: 51, Pages: 875-904, ISSN: 0090-6964
Head injuries are common for cyclists involved in collisions. Such collision scenarios result in a range of injuries, with different head impact speeds, angles, locations, or surfaces. A clear understanding of these collision characteristics is vital to design high fidelity test methods for evaluating the performance of helmets. We review literature detailing real-world cyclist collision scenarios and report on these key characteristics. Our review shows that helmeted cyclists have a considerable reduction in skull fracture and focal brain pathologies compared to non-helmeted cyclists, as well as a reduction in all brain pathologies. The considerable reduction in focal head pathologies is likely to be due to helmet standards mandating thresholds of linear acceleration. The less considerable reduction in diffuse brain injuries is likely to be due to the lack of monitoring head rotation in test methods. We performed a novel meta-analysis of the location of 1809 head impacts from ten studies. Most studies showed that the side and front regions are frequently impacted, with one large, contemporary study highlighting a high proportion of occipital impacts. Helmets frequently had impact locations low down near the rim line. The face is not well protected by most conventional bicycle helmets. Several papers determine head impact speed and angle from in-depth reconstructions and computer simulations. They report head impact speeds from 5 to 16 m/s, with a concentration around 5 to 8 m/s and higher speeds when there was another vehicle involved in the collision. Reported angles range from 10° to 80° to the normal, and are concentrated around 30°-50°. Our review also shows that in nearly 80% of the cases, the head impact is reported to be against a flat surface. This review highlights current gaps in data, and calls for more research and data to better inform improvements in testing methods of standards and rating schemes and raise helmet s
Yu X, Baker C, Brown M, et al., 2023, In-depth bicycle collision reconstruction: from a crash helmet to brain injury evaluation, Bioengineering, Vol: 10, Pages: 1-16, ISSN: 2306-5354
Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may be used to predict the risk of TBI. However, lack of collision details can render accident reconstruction nearly impossible. Here, we introduce a reconstruction method to evaluate the brain injury in a bicycle–vehicle collision using the crash helmet alone. Following a thorough inspection of the cyclist’s helmet, we identified a severe impact, a moderate impact and several scrapes, which helped us to determine the impact conditions. We used our helmet test rig and intact helmets identical to the cyclist’s helmet to replicate the damage seen on the cyclist’s helmet involved in the real-world collision. We performed both linear and oblique impacts, measured the translational and rotational kinematics of the head and predicted the strain and the strain rate across the brain using a computational head model. Our results proved the hypothesis that the cyclist sustained a severe impact followed by a moderate impact on the road surface. The estimated head accelerations and velocity (167 g, 40.7 rad/s and 13.2 krad/s2) and the brain strain and strain rate (0.541 and 415/s) confirmed that the severe impact was large enough to produce mild to moderate TBI. The method introduced in this study can guide future accident reconstructions, allowing for the evaluation of TBI using the crash helmet only.
Yu X, Baker CE, Ghajari M, 2023, Head impact location, speed and angle from falls and trips in the workplace, Annals of Biomedical Engineering, Pages: 1-16, ISSN: 0090-6964
Traumatic brain injury (TBI) is a common injury in the workplace. Trips and falls are the leading causes of TBI in the workplace. However, industrial safety helmets are not designed for protecting the head under these impact conditions. Instead, they are designed to pass the regulatory standards which test head protection against falling heavy and sharp objects. This is likely to be due to the limited understanding of head impact conditions from trips and falls in workplace. In this study, we used validated human multi-body models to predict the head impact location, speed and angle (measured from the ground) during trips, forward falls and backward falls. We studied the effects of worker size, initial posture, walking speed, width and height of the tripping barrier, bracing and falling height on the head impact conditions. Overall, we performed 1692 simulations. The head impact speed was over two folds larger in falls than trips, with backward falls producing highest impact speeds. However, the trips produced impacts with smaller impact angles to the ground. Increasing the walking speed increased the head impact speed but bracing reduced it. We found that 41% of backward falls and 19% of trips/forward falls produced head impacts located outside the region of helmet coverage. Next, we grouped all the data into three sub-groups based on the head impact angle: [0°, 30°], (30°, 60°] and (60°, 90°] and excluded groups with small number of cases. We found that most trips and forward falls lead to impact angles within the (30°, 60°] and (60°, 90°] groups while all backward falls produced impact angles within (60°, 90°] group. We therefore determined five representative head impact conditions from these groups by selecting the 75th percentile speed, mean value of angle intervals and median impact location (determined by elevation and azimuth angles) of each group. This led to two representative head impact conditions for trip
He L, Maiolino P, Leong F, et al., 2023, Robotic simulators for tissue examination training with multimodal sensory feedback, IEEE Reviews in Biomedical Engineering, Vol: 16, Pages: 514-529, ISSN: 1941-1189
Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators.
Zimmerman K, 2022, The biomechanical signature of loss of consciousness: computational modelling of elite athlete head injuries, Brain: a journal of neurology, ISSN: 0006-8950
Leong F, Chow Yin L, Siamak Farajzadeh K, et al., 2022, A surrogate model based on a finite element model of abdomen for real-time visualisation of tissue stress during physical examination training, Bioengineering, Vol: 9, ISSN: 2306-5354
Robotic patients show great potential to improve medical palpation training as they can provide feedback that cannot be obtained in a real patient. Providing information about internal organs deformation can significantly enhance palpation training by giving medical trainees visual insight based on their finger behaviours. This can be achieved by using computational models of abdomen mechanics. However, such models are computationally expensive, thus able to provide real-time predictions. In this work, we proposed an innovative surrogate model of abdomen mechanics using machine learning (ML) and finite element (FE) modelling to virtually render internal tissue deformation in real-time. We first developed a new high-fidelity FE model of the abdomen mechanics from computerized tomography (CT) images. We performed palpation simulations to produce a large database of stress distribution on the liver edge, an area of interest in most examinations. We then used artificial neural networks (ANN) to develop the surrogate model and demonstrated its application in an experimental palpation platform. Our FE simulations took 1.5 hrs to predict stress distribution for each palpation while this only took a fraction of a second for the surrogate model. Our results show that the ANN has a 92.6% accuracy. We also show that the surrogate model is able to use the experimental input of palpation location and force to provide real-time projections onto the robotics platform. This enhanced robotics platform has potential to be used as a training simulator for trainees to hone their palpation skills.
Yu X, Logan I, Sarasola IDP, et al., 2022, The protective performance of modern motorcycle helmets under oblique impacts, Annals of Biomedical Engineering, Vol: 50, Pages: 1674-1688, ISSN: 0090-6964
Motorcyclists are at high risk of head injuries, including skull fractures, focal brain injuries, intracranial bleeding and diffuse brain injuries. New helmet technologies have been developed to mitigate head injuries in motorcycle collisions, but there is limited information on their performance under commonly occurring oblique impacts. We used an oblique impact method to assess the performance of seven modern motorcycle helmets at five impact locations. Four helmets were fitted with rotational management technologies: a low friction layer (MIPS), three-layer liner system (Flex) and dampers-connected liner system (ODS). Helmets were dropped onto a 45° anvil at 8 m/s at five locations. We determined peak translational and rotational accelerations (PTA and PRA), peak rotational velocity (PRV) and brain injury criteria (BrIC). In addition, we used a human head finite element model to predict strain distribution across the brain and in corpus callosum and sulci. We found that the impact location affected the injury metrics and brain strain, but this effect was not consistent. The rear impact produced lowest PTAs but highest PRAs. This impact produced highest strain in corpus callosum. The front impact produced the highest PRV and BrIC. The side impact produced the lowest PRV, BrIC and strain across the brain, sulci and corpus callosum. Among helmet technologies, MIPS reduced all injury metrics and brain strain compared with conventional helmets. Flex however was effective in reducing PRA only and ODS was not effective in reducing any injury metrics in comparison with conventional helmets. This study shows the importance of using different impact locations and injury metrics when assessing head protection effects of helmets. It also provides new data on the performance of modern motorcycle helmets. These results can help with improving helmet design and standard and rating test methods.
Baker CE, Montemiglio A, Li R, et al., 2022, Assessing the influence of parameter variation on kinematic head injury metric uncertainty in multibody reconstructions of real-world pedestrian vehicle and ground impacts, 2022 IRCOBI Conference, Pages: 393-394, ISSN: 2235-3151
Yu X, Halldin P, Ghajari M, 2022, Oblique impact responses of Hybrid III and a new headform with more biofidelic coefficient of friction and moments of inertia, Frontiers in Bioengineering and Biotechnology, Vol: 10, Pages: 1-14, ISSN: 2296-4185
New oblique impact methods for evaluating head injury mitigation effects of helmets are emerging, which mandate measuring both translational and rotational kinematics of the headform. These methods need headforms with biofidelic mass, moments of inertia (MoIs) and coefficient of friction (CoF). To fulfil this need, the working group 11 of the European standardization head protection committee (CEN/TC158) has been working on the development of a new headform with realistic MoIs and CoF, based on recent biomechanics research on the human head. In this study, we used a version of this headform (Cellbond) to test a motorcycle helmet under oblique impacts at 8m/s at five different locations. We also used the Hybrid III headform, which is commonly used in helmet oblique impacts. We tested whether there is a difference between the predictions of the headforms in terms of injury metrics based on head kinematics, including peak translational and rotational acceleration, peak rotational velocity and BrIC (Brain Injury Criterion). We also used Imperial College finite element model of human head to predict strain and strain rate across the brain and tested whether there is a difference between the headforms in terms of predicted strain and strain rate. We found that the Cellbond headform produced similar or higher peak translational accelerations depending on the impact location (-3.2% in front-side impact to 24.3% in rear impact). The Cellbond headform however produced significantly lower peak rotational acceleration (-41.8% in rear impact to -62.7% in side impact), peak rotational velocity (-29.5% in side impact to -47.6% in rear impact) and BrIC (-29% in rear-side impact to -45.3% in rear impact). The 90th percentile value of the maximum brain strain and strain rate were also significantly lower using this headform. Our results suggest that MoIs and CoF have significant effects on headform rotational kinematics, and consequently brain deformation, during helmeted oblique imp
Ji S, Ghajari M, Mao H, et al., 2022, Use of brain biochemical models for monitoring impact exposure in contact sports, Annals of Biomedical Engineering, Vol: 50, Pages: 1389-1408, ISSN: 0090-6964
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.
Yu X, Nguyen T, Wu T, et al., 2022, Non-lethal blasts can generate cavitation in cerebrospinal fluid while severe helmeted impacts cannot: a novel mechanism for blast brain injury, Frontiers in Bioengineering and Biotechnology, Vol: 10, ISSN: 2296-4185
Cerebrospinal fluid (CSF) cavitation is a likely physical mechanism for producing traumatic brain injury (TBI) under mechanical loading. In this study, we investigated CSF cavitation under blasts and helmeted impacts which represented loadings in battlefield and road traffic/sports collisions. We first predicted the human head response under the blasts and impacts using computational modelling and found that the blasts can produce much lower negative pressure at the contrecoup CSF region than the impacts. Further analysis showed that the pressure waves transmitting through the skull and soft tissue are responsible for producing the negative pressure at the contrecoup region. Based on this mechanism, we hypothesised that blast, and not impact, can produce CSF cavitation. To test this hypothesis, we developed a one-dimensional simplified surrogate model of the head and exposed it to both blasts and impacts. The test results confirmed the hypothesis and computational modelling of the tests validated the proposed mechanism. These findings have important implications for prevention and diagnosis of blast TBI.
Abayazid FF, Carpanen D, Ghajari M, 2022, New viscoelastic circular cell honeycombs for controlling shear and compressive responses in oblique impacts, INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, Vol: 222, ISSN: 0020-7403
Duckworth H, Azor A, Wischmann N, et al., 2022, A finite element model of cerebral vascular injury for predicting microbleeds location, Frontiers in Bioengineering and Biotechnology, Vol: 10, ISSN: 2296-4185
Finite Element (FE) models of brain mechanics have improved our understanding of the brain response to rapid mechanical loads that produce traumatic brain injuries. However, these models have rarely incorporated vasculature, which limits their ability to predict the response of vessels to head impacts. To address this shortcoming, here we used high-resolution MRI scans to map the venous system anatomy at a submillimetre resolution. We then used this map to develop an FE model of veins and incorporated it in an anatomically detailed FE model of the brain. The model prediction of brain displacement at different locations was compared to controlled experiments on post-mortem human subject heads, yielding over 3,100 displacement curve comparisons, which showed fair to excellent correlation between them. We then used the model to predict the distribution of axial strains and strain rates in the veins of a rugby player who had small blood deposits in his white matter, known as microbleeds, after sustaining a head collision. We hypothesised that the distribution of axial strain and strain rate in veins can predict the pattern of microbleeds. We reconstructed the head collision using video footage and multi-body dynamics modelling and used the predicted head accelerations to load the FE model of vascular injury. The model predicted large axial strains in veins where microbleeds were detected. A region of interest analysis using white matter tracts showed that the tract group with microbleeds had 95th percentile peak axial strain and strain rate of 0.197 and 64.9 s−1 respectively, which were significantly larger than those of the group of tracts without microbleeds (0.163 and 57.0 s−1). This study does not derive a threshold for the onset of microbleeds as it investigated a single case, but it provides evidence for a link between strain and strain rate applied to veins during head impacts and structural damage and allows for future work to generate threshold valu
Yu X, Wu T, Nguyen T-TN, et al., 2022, Investigation of blast-induced cerebrospinal fluid cavitation: Insights from a simplified head surrogate, International Journal of Impact Engineering, Vol: 162, Pages: 1-9, ISSN: 0734-743X
Blast induced traumatic brain injury (bTBI) has been a prevalent injury in recent conflicts. Post-mortem studies have shown damage in the brain tissue close to the cerebrospinal fluid (CSF) in bTBI cases compared to non-blast TBI cases. CSF cavitation is a potential mechanism for this brain/CSF interface injury. In this study, our aim was to explore the possibility and mechanism of blast induced CSF cavitation. We first developed a one-dimensional simplified human head surrogate and exposed it to nonlethal blast waves using a shock tube. High-speed videography and pressure sensors data showed the formation and collapse of cavitation in the CSF simulant. Then, we explored the mechanism of the cavitation using a finite element model of the head surrogate. We found that the pressure waves transmitting through the skull (outer wave) and tissue simulants (inner wave) are responsible for the generation and collapse of the cavitation bubbles, respectively. Next, we used this insight to explore the possibility of CSF cavitation in the human head using a detailed finite element model. The simulations verified the role of the inner and outer waves in the generation and collapse of cavitation. Our results suggested that CSF cavitation is likely to happen in the human head under blast loading. Finally, we studied the CSF cavitation in head surrogate models with different lengths. The results showed that the head length significantly affected the CSF cavitation, indicating the potential drawback of using small animals to study bTBI in human head. Our findings can improve our understanding of the brain/CSF interface injury after blast exposure and inform the design of protection systems and animal tests.
Yu X, Ghajari M, 2022, Protective performance of helmets and goggles in mitigating brain biomechanical response to primary blast exposure, Annals of Biomedical Engineering, Vol: 50, Pages: 1579-1595, ISSN: 0090-6964
The current combat helmets are primarily designed to mitigate blunt impacts and ballistic loadings. Their protection against primary blast wave is not well studied. In this paper, we comprehensively assessed the protective capabilities of the advanced combat helmet and goggles against blast waves with different intensity and directions. Using a high-fidelity human head model, we compared the intracranial pressure (ICP), cerebrospinal fluid (CSF) cavitation, and brain strain and strain rate predicted from bare head, helmet-head and helmet-goggles-head simulations. The helmet was found to be effective in mitigating the positive ICP (24-57%) and strain rate (5-34%) in all blast scenarios. Goggles were found to be effective in mitigating the positive ICP in frontal (6-16%) and lateral (5-7%) blast exposures. However, the helmet and goggles had minimal effects on mitigating CSF cavitation and even increased brain strain. Further investigation showed that wearing a helmet leads to higher risk of cavitation. In addition, their presence increased the head kinetic energy, leading to larger strains in the brain. Our findings can improve our understanding of the protective effects of helmets and goggles and guide the design of helmet pads to mitigate brain responses to blast.
Posirisuk P, Baker C, Ghajari M, 2022, Computational prediction of head-ground impact kinematics in e-scooter falls, Accident Analysis and Prevention, Vol: 167, Pages: 1-11, ISSN: 0001-4575
E-scooters are the fastest growing mode of micro-mobility with important environmental benefits. However, there are serious concerns about injuries caused by e-scooter accidents. Falls due to poor road surface conditions are a common cause of injury in e-scooter riders, and head injuries are one of the most common and concerning injuries in e-scooter falls. However, the head-ground impact biomechanics in e-scooter falls and its relationship with e-scooter speed and design, road surface conditions and wearing helmets remain poorly understood. To address some of these key questions, we predicted the head-ground impact force and velocity of e-scooter riders in different falls caused by potholes. We used multi-body dynamics approach to model a commercially available e-scooter and simulate 180 falls using human body models. We modelled different pothole sizes to test whether the pothole width and depth influences the onset of falls and head-ground impact speed and force. We also tested whether the e-scooter travelling speed has an influence on the head-ground impact force and velocity. The simulations were carried out with three human body models to ensure that the results of the study are inclusive of a wide range of rider sizes. For our 10inch diameter e-scooter wheels, we found a sudden increase in the occurrence of falls when the pothole depth was increased from 3cm (no falls) to 6cm (41 falls out of 60 cases). When the falls occurred, we found a head-ground impact force of 13.23.4kN, which is larger than skull fracture thresholds. The head-ground impact speed was 6.31.4m/s, which is nearly the same as the impact speed prescribed in bicycle helmet standards. All e-scooter falls resulted in oblique head impacts, with an impact angle of 6510 (measured from the ground). Decreasing the e-scooter speed reduced the head impact speed. For instance, reducing the e-scooter speed from 30km/h to 20km/h led to a 14% reduction in the mean impact speed and 12% reduction in th
Baker C, Martin P, Wilson M, et al., 2022, The relationship between road traffic collision dynamics and traumatic brain injury pathology, Brain Communications, Vol: 4, ISSN: 2632-1297
Road traffic collisions are a major cause of traumatic brain injury. However, the relationship between road traffic collision dynamics and traumatic brain injury risk for different road users is unknown. We investigated 2,065 collisions from Great Britain’s Road Accident In-depth Studies collision database involving 5,374 subjects (2013-20). 595 subjects sustained a traumatic brain injury (20.2% of 2,940 casualties), including 315 moderate-severe and 133 mild-probable. Key pathologies included skull fracture (179, 31.9%), subarachnoid haemorrhage (171, 30.5%), focal brain injury (168, 29.9%) and subdural haematoma (96, 17.1%). These results were extended nationally using >1,000,000 police-reported collision casualties. Extrapolating from the in-depth data we estimate that there are ~20,000 traumatic brain injury casualties (~5,000 moderate-severe) annually on Great Britain’s roads, accounting for severity differences. Detailed collision investigation allows vehicle collision dynamics to be understood and the change-in-velocity (known as delta-V) to be estimated for a subset of in-depth collision data. Higher delta-V increased the risk of moderate-severe brain injury for all road users. The four key pathologies were not observed below 8km/h delta-V for pedestrians/cyclists and 19km/h delta-V for car occupants (higher delta-V threshold for focal injury in both groups). Traumatic brain injury risk depended on road user type, delta-V and impact direction. Accounting for delta-V, pedestrians/cyclists had a 6-times higher likelihood of moderate-severe brain injury than car occupants. Wearing a cycle helmet was protective against overall and mild-to-moderate-severe brain injury, particularly skull fracture and subdural haematoma. Cycle helmet protection was not due to travel or impact speed differences between helmeted and non-helmeted cyclist groups. We additionally examined the influence of delta-V direction. Car occupants exposed to a higher latera
Farajzadeh Khosroshahi S, Yin X, Donat C, et al., 2021, Multiscale modelling of cerebrovascular injury reveals the role of vascular anatomy and parenchymal shear stresses, Scientific Reports, Vol: 11, ISSN: 2045-2322
Neurovascular injury is often observed in traumatic brain injury (TBI). However, the relationship between mechanical forces and vascular injury is still unclear. A key question is whether the complex anatomy of vasculature plays a role in increasing forces in cerebral vessels and producing damage. We developed a high-fidelity multiscale finite element model of the rat brain featuring a detailed definition of the angioarchitecture. Controlled cortical impacts were performed experimentally and in-silico. The model was able to predict the pattern of blood–brain barrier damage. We found strong correlation between the area of fibrinogen extravasation and the brain area where axial strain in vessels exceeds 0.14. Our results showed that adjacent vessels can sustain profoundly different axial stresses depending on their alignment with the principal direction of stress in parenchyma, with a better alignment leading to larger stresses in vessels. We also found a strong correlation between axial stress in vessels and the shearing component of the stress wave in parenchyma. Our multiscale computational approach explains the unrecognised role of the vascular anatomy and shear stresses in producing distinct distribution of large forces in vasculature. This new understanding can contribute to improving TBI diagnosis and prevention.
Abayazid F, Ding K, Zimmerman K, et al., 2021, A new assessment of bicycle helmets: the brain injury mitigation effects of new technologies in oblique impacts, Annals of Biomedical Engineering, Vol: 49, Pages: 2716-2733, ISSN: 0090-6964
New helmet technologies have been developed to improve the mitigation of traumatic brain injury (TBI) in bicycle accidents. However, their effectiveness under oblique impacts, which produce more strains in the brain in comparison with vertical impacts adopted by helmet standards, is still unclear. Here we used a new method to assess the brain injury prevention effects of 27 bicycle helmets in oblique impacts, including helmets fitted with a friction-reducing layer (MIPS), a shearing pad (SPIN), a wavy cellular liner (WaveCel), an airbag helmet (Hövding) and a number of conventional helmets. We tested whether helmets fitted with the new technologies can provide better brain protection than conventional helmets. Each helmeted headform was dropped onto a 45° inclined anvil at 6.3 m/s at three locations, with each impact location producing a dominant head rotation about one anatomical axes of the head. A detailed computational model of TBI was used to determine strain distribution across the brain and in key anatomical regions, the corpus callosum and sulci. Our results show that, in comparison with conventional helmets, the majority of helmets incorporating new technologies significantly reduced peak rotational acceleration and velocity and maximal strain in corpus callosum and sulci. Only one helmet with MIPS significantly increased strain in the corpus collosum. The helmets fitted with MIPS and WaveCel were more effective in reducing strain in impacts producing sagittal rotations and a helmet fitted with SPIN in coronal rotations. The airbag helmet was effective in reducing brain strain in all impacts, however, peak rotational velocity and brain strain heavily depended on the analysis time. These results suggest that incorporating different impact locations in future oblique impact test methods and designing helmet technologies for the mitigation of head rotation in different planes are key to reducing brain injuries in bicycle accidents.
Duckworth H, Sharp DJ, Ghajari M, 2021, Smoothed particle hydrodynamic modelling of the cerebrospinal fluid for brain biomechanics: accuracy and stability, International Journal for Numerical Methods in Biomedical Engineering, Vol: 37, ISSN: 1069-8299
The Cerebrospinal Fluid (CSF) can undergo shear deformations under head motions. Finite Element (FE) models, which are commonly used to simulate biomechanics of the brain, including traumatic brain injury, employ solid elements to represent the CSF. However, the limited number of elements paired with shear deformations in CSF can decrease the accuracy of their predictions. Large deformation problems can be accurately modelled using the mesh-free Smoothed Particle Hydrodynamics (SPH) method, but there is limited previous work on using this method for modelling the CSF. Here we explored the stability and accuracy of key modelling parameters of an SPH model of the CSF when predicting relative brain/skull displacements in a simulation of an in vivo mild head impact in human. The Moving Least Squares (MLS) SPH formulation and Ogden rubber material model were found to be the most accurate and stable. The strain and strain rate in the brain differed across the SPH and FE models of CSF. The FE mesh anchored the gyri, preventing them from experiencing the level of strains seen in the in vivo brain experiments and predicted by the SPH model. Additionally, SPH showed higher levels of strains in the sulci compared to the FE model. However, tensile instability was found to be a key challenge of the SPH method, which needs to be addressed in future. Our study provides a detailed investigation of the use of SPH and shows its potential for improving the accuracy of computational models of brain biomechanics.
Zimmerman K, Kim J, Karton C, et al., 2021, Player position in American Football influences the magnitude of mechanical strains produced in the location of chronic traumatic encephalopathy pathology: a computational modelling study, Journal of Biomechanics, Vol: 118, ISSN: 0021-9290
American football players are frequently exposed to head impacts, which can cause concussions and may lead to neurodegenerative diseases such as chronic traumatic encephalopathy (CTE). Player position appears to influence the risk of concussion but there is limited work on its effect on the risk of CTE. Computational modelling has shown that large brain deformations during head impacts co-localise with CTE pathology in sulci. Here we test whether player position has an effect on brain deformation within the sulci, a possible biomechanical trigger for CTE. We physically reconstructed 148 head impact events from video footage of American Football games. Players were separated into 3 different position profiles based on the magnitude and frequency of impacts. A detailed finite element model of TBI was then used to predict Green-Lagrange strain and strain rate across the brain and in sulci. Using a one-way ANOVA, we found that in positions where players were exposed to large magnitude and low frequency impacts (e.g. defensive back and wide receiver), strain and strain rate across the brain and in sulci were highest. We also found that rotational head motion is a key determinant in producing large strains and strain rates in the sulci. Our results suggest that player position has a significant effect on impact kinematics, influencing the magnitude of deformations within sulci, which spatially corresponds to where CTE pathology is observed. This work can inform future studies investigating different player-position risks for concussion and CTE and guide design of prevention systems.
Fahlstedt M, Abayazid F, Panzer MB, et al., 2021, Ranking and rating bicycle helmet safety performance in oblique impacts using eight different brain injury models, Annals of Biomedical Engineering, Vol: 49, Pages: 1097-1109, ISSN: 0090-6964
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.
Baker CE, Martin PS, Wilson M, et al., 2021, Traumatic brain injury findings from Great Britain's in-depth RAIDS database relating to delta-V, Pages: 726-727, ISSN: 2235-3151
Donat C, Yanez Lopez M, Sastre M, et al., 2021, From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury., Brain: a journal of neurology, Vol: 144, Pages: 70-91, ISSN: 0006-8950
The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a Controlled Cortical Impact, mild and moderate injuries(1 and 2 mm) were performed. Focal and axonal injuries were quantified withvolumetric and diffusion 9.4T MRI two weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters,along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes.The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in segments of the corpus callosum predicted to have a high strain, indicating white matter changes. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning
Yu X, Azor A, Sharp DJ, et al., 2020, Mechanisms of tensile failure of cerebrospinal fluid in blast traumatic brain injury, Extreme Mechanics Letters, Vol: 38, Pages: 1-9, ISSN: 2352-4316
Mechanisms of blast-induced Traumatic Brain Injury (BTBI), particularly those linked to the primary pressure wave, are still not fully understood. One possible BTBI mechanism is cavitation in the cerebrospinal fluid (CSF) caused by CSF tensile failure, which is likely to increase strain and strain rate in the brain tissue near the CSF. Blast loading of the head can generate rarefaction (expansion) waves and rapid head motion, which both can produce tensile forces in the CSF. However, it is not clear which of these mechanisms is more likely to cause CSF tensile failure. In this study, we used a high-fidelity 3-dimensional computational model of the human head to test whether the CSF tensile failure increases brain deformation near the brain/CSF boundary and to determine the key failure mechanisms. We exposed the head model to a frontal blast wave and predicted strain and strain rate distribution in the cortex. We found that CSF tensile failure significantly increased strain and strain rate in the cortex. We then studied whether the rapid head motion or the rarefaction wave causes strain and strain rate concentration in cortex. We isolated these two effects by conducting simulations with pure head motion loading (i.e. prescribing the skull velocity but eliminating the pressure wave) and pure blast wave loading (i.e. eliminating head motion by fixing the skull base). Our results showed that the strain increase in the cortex was mainly caused by head motion. In contrast, strain rate increase was caused by both rapid head motion and rarefaction waves, but head motion had a stronger effect on elevating strain rate. Our results show that rapid motion of the head produced by blast wave is the key mechanism for CSF tensile failure and subsequent concentration of strain and strain rate in cortex. This finding suggests that mitigation of rapid head motion caused by blast loading needs to be addressed in the design of protective equipment in order to prevent the tensile failure
Abayazid F, Ghajari M, 2020, Material characterisation of additively manufactured elastomers at different strain rates and build orientations, Additive Manufacturing, Vol: 33, ISSN: 2214-8604
Material jetting, particularly PolyJet technology, is an additive manufacturing (AM) process which has introduced novel flexible elastomers used in bio-inspired soft robots, compliant structures and dampers. Finite Element Analysis (FEA) is a key tool for the development of such applications, which requires comprehensive material characterisation utilising advanced material models. However, in contrast to conventional rubbers, PolyJet elastomers have been less explored leading to a few material models with various limitations in fidelity. Therefore, one aim of this study was to characterise the mechanical response of the latest PolyJet elastomers, Agilus30 (A30) and Tango+ (T+), under large strain tension-compression and time-dependent high-frequency/relaxation loadings. Another aim was to calibrate a visco-hyperelastic material model to accurately predict these responses. Tensile, compressive, cyclic, dynamic mechanical analysis (DMA) and stress relaxation tests were carried out on pristine A30 and T+ samples. Quasi-static tension-compression tests were used to calibrate a 3-term Ogden hyperelastic model. Stress relaxation and DMA results were combined to determine the constants of a 5-term Prony series across a large window of relaxation time (10 μs–100 s). A numerical time-stepping scheme was employed to predict the visco-hyperelastic response of the 3D-printed elastomers at large strains and different strain rates. In addition, the anisotropy in the elastomers, which stemmed from build orientation, was explored. Highly nonlinear stress-strain relationships were observed in both elastomers, with a strong dependency on strain rate. Relaxation tests revealed that A30 and T+ elastomers relax to 50 % and 70 % of their peak stress values respectively in less than 20 s. The effect of orientation on the loading response was most pronounced with prints along the Z-direction, particularly at large strains and lower strain rates. Moreover, the visco-hyperelastic m
Soleiman Fallah A, Ghajari M, Safa Y, 2019, Computational modelling of dynamic delamination in morphing composite blades and wings, The International Journal of Multiphysics, Vol: 13, Pages: 393-430, ISSN: 1750-9548
Morphing blades have been promising in lifting restrictions on rated capacity of wind turbines and improving lift-to-drag ratio for aircraft wings at higher operational angles of attack. The present study focuses on one aspect of the response of morphing blades viz. dynamic delamination. A numerical study of delamination in morphing composite blades is conducted. Both components i.e. the composite part and the stiffener are studied. The eXtended Finite Element Method (XFEM) and nonlocal continuum mechanics (peridynamics) have both been used to study fracture in the isotropic stiffener used in conjunction with the blade. As for the composite morphing blade, cohesive elements are used to represent the interlaminar weak zone and delamination has been studied under dynamic pulse loads. Intraply damage is studied using the nonlocal model as the peridynamic model is capable of addressing the problem adequately for the necessary level of sophistication.The differences and similarities between delamination patterns for impulsive, dynamic, and quasi-static loadings are appreciated and in each case detailed analyses of delamination patterns are presented. The dependence of delamination pattern on loading regime is established, however; further parametric studies are not included as they lie beyond the scope of the study. Through the use of fracture energy alone the nonlocal model is capable of capturing intra- and interlaminar fractures. The proposed modelling scheme can thus have a major impact in design applications where dynamic pulse and impact loads of all natures (accidental, extreme, service, etc.) are to be considered and may therefore be utilised in design of lightweight morphing blades and wings where delamination failure mode is an issue.
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