Explaining and predicting the increased thorax injury in aged females: age and subject-specific thorax geometry coupled with improved bone constitutive models and age-specific material properties evaluated in side impact conditions.

Predicting and understanding thorax injury is fundamental for the assessment and development of safety systems to mitigate injury risk to the increasing and vulnerable aged population. While computational human models have contributed to the understanding of injury biomechanics, contemporary human body models have struggled to predict rib fractures and explain the increased incidence of injury in the aged population. The present study enhanced young and aged human body models (HBMs) by integrating a biofidelic cortical bone constitutive model and population-based bone material properties. The HBMs were evaluated using side impact sled tests assessed using chest compression and number of rib fractures. The increase in thoracic kyphosis and the associated change in rib angle with increasing age, led to increased rib torsional moment increasing the rib shear stress. Coupled with and improved cortical bone constitutive model and aged material properties, the higher resulting shear stress led to an increased number of rib fractures in the aged model. The importance of shear stress resulting from torsional load was further investigated using an isolated rib model. In contrast, HBM chest compression, a common thorax injury-associated metric, was insensitive to the aging factors studied. This study proposes an explanation for the increased incidence of thorax injury with increasing age reported in epidemiological data, and provides an enhanced understanding of human rib mechanics that will benefit assessment and design of future safety systems.

Assessment of brain response in operators subject to recoil force from firing long-range rifles.

Mild traumatic brain injury (mTBI) may be caused by occupational hazards military personnel encounter, such as falls, shocks, exposure to blast overpressure events, and recoil from weapon firing. While it is important to protect against injurious head impacts, the repeated exposure of Canadian Armed Forces (CAF) service members to sub-concussive events during the course of their service may lead to a significant reduction in quality of life. Symptoms may include headaches, difficulty concentrating, and noise sensitivity, impacting how personnel complete their duties and causing chronic health issues. This study investigates how the exposure to the recoil force of long-range rifles results in head motion and brain deformation. Direct measurements of head kinematics of a controlled population of military personnel during firing events were obtained using instrumented mouthguards. The experimentally measured head kinematics were then used as inputs to a finite element (FE) head model to quantify the brain strains observed during each firing event. The efficacy of a concept recoil mitigation system (RMS), designed to mitigate loads applied to the operators was quantified, and the RMS resulted in lower loading to the operators. The outcomes of this study provide valuable insights into the magnitudes of head kinematics observed when firing long-range rifles, and a methodology to quantify effects, which in turn will help craft exposure guidelines, guide training to mitigate the risk of injury, and improve the quality of lives of current and future CAF service members and veterans.

Brain Material Properties and Integration of Arachnoid Complex for Biofidelic Impact Response for Human Head Finite Element Model.

Finite element head models offer great potential to study brain-related injuries; however, at present may be limited by geometric and material property simplifications required for continuum-level human body models. Specifically, the mechanical properties of the brain tissues are often represented with simplified linear viscoelastic models, or the material properties have been optimized to specific impact cases. In addition, anatomical structures such as the arachnoid complex have been omitted or implemented in a simple lumped manner. Recent material test data for four brain regions at three strain rates in three modes of loading (tension, compression, and shear) was used to fit material parameters for a hyper-viscoelastic constitutive model. The material model was implemented in a contemporary detailed head finite element model. A detailed representation of the arachnoid trabeculae was implemented with mechanical properties based on experimental data. The enhanced head model was assessed by re-creating 11 ex vivo head impact scenarios and comparing the simulation results with experimental data. The hyper-viscoelastic model faithfully captured mechanical properties of the brain tissue in three modes of loading and multiple strain rates. The enhanced head model showed a high level of biofidelity in all re-created impacts in part due to the improved brain-skull interface associated with implementation of the arachnoid trabeculae. The enhanced head model provides an improved predictive capability with material properties based on tissue level data and is positioned to investigate head injury and tissue damage in the future.

Impact Location Dependence of Behind Armor Blunt Trauma Injury Assessed Using a Human Body Finite Element Model.

Behind armor blunt trauma (BABT), resulting from dynamic deformation of protective ballistic armor into the thorax, is currently assessed assuming a constant threshold of maximum backface deformation (BFDs) (44 mm). Although assessed for multiple impacts on the same armor, testing is focused on armor performance (shot-to-edge and shot-to-shot) without consideration of the underlying location on the thorax. Previous studies identified the importance of impacts on organs of animal surrogates wearing soft armor. However, the effect of impact location was not quantified outside the threshold of 44 mm. In the present study, a validated biofidelic advanced human thorax model (50th percentile male) was utilized to assess the BABT outcome from varying impact location. The thorax model was dynamically loaded using a method developed for recreating BABT impacts, and BABT events within the range of real-world impact severities and locations were simulated. It was found that thorax injury depended on impact location for the same BFDs. Generally, impacts over high compliance locations (anterolateral rib cage) yielded increased thoracic compression and loading on the lungs leading to pulmonary lung contusion (PLC). Impacts at low compliance locations (top of sternum) yielded hard tissue fractures. Injuries to the sternum, ribs, and lungs were predicted at BFDs lower than 44 mm for low compliance locations. Location-based injury risk curves demonstrated greater accuracy in injury prediction. This study quantifies the importance of impact location on BABT injury severity and demonstrates the need for consideration of location in future armor design and assessment.

Quantifying the Importance of Active Muscle Repositioning a Finite Element Neck Model in Flexion Using Kinematic, Kinetic, and Tissue-Level Responses.

PURPOSE: Non-neutral neck positions are important initial conditions in impact scenarios, associated with a higher incidence of injury. Repositioning in finite element (FE) neck models is often achieved by applying external boundary conditions (BCs) to the head while constraining the first thoracic vertebra (T1). However, in vivo, neck muscles contract to achieve a desired head and neck position generating initial loads and deformations in the tissues. In the present study, a new muscle-based repositioning method was compared to traditional applied BCs using a contemporary FE neck model for forward head flexion of 30°. METHODS: For the BC method, an external moment (2.6 Nm) was applied to the head with T1 fixed, while for the muscle-based method, the flexors and extensors were co-contracted under gravity loading to achieve the target flexion. RESULTS: The kinematic response from muscle contraction was within 10% of the in vivo experimental data, while the BC method differed by 18%. The intervertebral disc forces from muscle contraction were agreeable with the literature (167 N compression, 12 N shear), while the BC methodology underpredicted the disc forces owing to the lack of spine compression. Correspondingly, the strains in the annulus fibrosus increased by an average of 60% across all levels due to muscle contraction compared to BC method. CONCLUSION: The muscle repositioning method enhanced the kinetic response and subsequently led to differences in tissue-level responses compared to the conventional BC method. The improved kinematics and kinetics quantify the importance of repositioning FE neck models using active muscles to achieve non-neutral neck positions.

Effect of muscle pre-tension and pre-impact neck posture on the kinematic response of the cervical spine in simulated low-speed rear impacts.

Computational human body models (HBMs) can identify potential injury pathways not easily accessible through experimental studies, such as whiplash induced injuries. However, previous computational studies investigating neck response to simulated impact conditions have neglected the effect of pre-impact neck posture and muscle pre-tension on the intervertebral kinematics and tissue-level response. The purpose of the present study was addressing this knowledge gap using a detailed neck model subjected to simulated low-acceleration rear impact conditions, towards improved intervertebral kinematics and soft tissue response for injury assessment. An improved muscle path implementation in the model enabled the modeling of muscle pre-tension using experimental muscle pre-stretch data determined from previous cadaver studies. Cadaveric neck impact tests and human volunteer tests with the corresponding cervical spine posture were simulated using a detailed neck model with the reported boundary conditions and no muscle activation. Computed intervertebral kinematics of the model with pre-tension achieved, for the first time, the S-shape behavior of the neck observed in low severity rear impacts of both cadaver and volunteer studies. The maximum first principal strain in the muscles for the model with pre-tension was 27% higher than that without pre-tension. Although, the pre-impact neck posture was updated to match the average posture reported in the experimental tests, the change in posture was generally small with only small changes in vertebral kinematics and muscle strain. This study provides a method to incorporate muscle pre-tension in HBM and quantifies the importance of pre-tension in calculating tissue-level distractions.

Characterizing In-Situ Metatarsal Fracture Risk During Simulated Workplace Impact Loading.

Metatarsal fractures represent the most common traumatic foot injury; however, metatarsal fracture thresholds remain poorly characterized, which affects performance targets for protective footwear. This experimental study investigated impact energies, forces, and deformations to characterize metatarsal fracture risk for simulated in situ workplace impact loading. A drop tower setup conforming to ASTM specifications for testing impact resistance of metatarsal protective footwear applied a target impact load (22-55 J) to 10 cadaveric feet. Prior to impact, each foot was axially loaded through the tibia with a specimen-specific bodyweight load to replicate a natural weight-bearing stance. Successive iterations of impact tests were performed until a fracture was observed with X-ray imaging. Descriptive statistics were computed for force, deformation, and impact energy. Correlational analysis was conducted on donor age, BMI, deformation, force, and impact energy. A survival analysis was used to generate injury risk curves (IRC) using impact energy and force. All 10 specimens fractured with the second metatarsal being the most common fracture location. The mean peak energy, force, and deformation during fracture were 46.6 J, 4640 N, 28.9 mm, respectively. Survival analyses revealed a 50% fracture probability was associated with 35.8 J and 3562 N of impact. Foot deformation was not significantly correlated (p = 0.47) with impact force, thus deformation is not recommended to predict metatarsal fracture risk. The results from this study can be used to improve test standards for metatarsal protection, provide performance targets for protective footwear developers, and demonstrate a methodological framework for future metatarsal fracture research.

Enhancing the Biofidelity of an Upper Cervical Spine Finite Element Model Within the Physiologic Range of Motion and Its Effect on the Full Ligamentous Neck Model Response.

Contemporary finite element (FE) neck models are developed in a neutral posture; however, evaluation of injury risk for out-of-position impacts requires neck model repositioning to non-neutral postures, with much of the motion occurring in the upper cervical spine (UCS). Current neck models demonstrate a limitation in predicting the intervertebral motions within the UCS within the range of motion, while recent studies have highlighted the importance of including the tissue strains resulting from repositioning FE neck models to predict injury risk. In the current study, the ligamentous cervical spine from a contemporary neck model (GHBMC M50 v4.5) was evaluated in flexion, extension, and axial rotation by applying moments from 0 to 1.5 N·m in 0.5 N·m increments, as reported in experimental studies and corresponding to the physiologic loading of the UCS. Enhancements to the UCS model were identified, including the C0-C1 joint-space and alar ligament orientation. Following geometric enhancements, an analysis was undertaken to determine the UCS ligament laxities, using a sensitivity study followed by an optimization study. The ligament laxities were optimized to UCS-level experimental data from the literature. The mean percent difference between UCS model response and experimental data improved from 55% to 23% with enhancements. The enhanced UCS model was integrated with a ligamentous cervical spine (LS) model and assessed with independent experimental data. The mean percent difference between the LS model and the experimental data improved from 46% to 35% with the integration of the enhanced UCS model.

Spinal Cord Boundary Conditions Affect Brain Tissue Strains in Impact Simulations.

Brain and spinal cord injuries have devastating consequences on quality of life but are challenging to assess experimentally due to the traumatic nature of such injuries. Finite element human body models (HBM) have been developed to investigate injury but are limited by a lack of biofidelic spinal cord implementation. In many HBM, brain models terminate with a fixed boundary condition at the brain stem. The goals of this study were to implement a comprehensive representation of the spinal cord into a contemporary head and neck HBM, and quantify the effect of the spinal cord on brain deformation during simulated impacts. Spinal cord tissue geometries were developed, based on 3D medical imaging and literature data, meshed, and implemented into the GHBMC 50th percentile male model. The model was evaluated in frontal, lateral, rear, and oblique impact conditions, and the resulting maximum principal strains in the brain tissue were compared, with and without the spinal cord. A new cumulative strain curve metric was proposed to quantify brain strain distribution. Presence of the spinal cord increased brain tissue strains in all simulated cases, owing to a more compliant boundary condition, highlighting the importance of the spinal cord to assess brain response during impact.

Arc-Length Re-Parametrization and Signal Registration to Determine a Characteristic Average and Statistical Response Corridors of Biomechanical Data.

A characteristic average and biofidelity response corridors are commonly used to represent the average behaviour and variability of biomechanical signal data for analysis and comparison to surrogates such as anthropometric test devices and computational models. However, existing methods for computing the characteristic average and corresponding response corridors of experimental data are often customized to specific types or shapes of signal and therefore limited in general applicability. In addition, simple methods such as point-wise averaging can distort or misrepresent important features if signals are not well aligned and highly correlated. In this study, an improved method of computing the characteristic average and response corridors of a set of experimental signals is presented based on arc-length re-parameterization and signal registration. The proposed arc-length corridor method was applied to three literature datasets demonstrating a range of characteristics common to biomechanical data, such as monotonic increasing force-displacement responses with variability, oscillatory acceleration-time signals, and hysteretic load-unload data. The proposed method addresses two challenges in assessing experimental data: arc-length re-parameterization enables the assessment of complex-shaped signals, including hysteretic load-unload data, while signal registration aligned signal features such as peaks and valleys to prevent distortion when determining the characteristic average response. The arc-length corridor method was shown to compute the characteristic average and response corridors for a wide range of biomechanical data, while providing a consistent statistical framework to characterize variability in the data. The arc-length corridor method is provided to the community in the freely available and open-source software package, ARCGen.

Comparison of numerical methods for cerebrospinal fluid representation and fluid-structure interaction during transverse impact of a finite element spinal cord model.

Spinal cord impacts can have devastating consequences. Computational models can investigate such impacts but require biofidelic numerical representations of the neural tissues and fluid-structure interaction with cerebrospinal fluid. Achieving this biofidelity is challenging, particularly for efficient implementation of the cerebrospinal fluid in full computational human body models. The goal of this study was to assess the biofidelity and computational efficiency of fluid-structure interaction methods representing the cerebrospinal fluid interacting with the spinal cord, dura, and pia mater using experimental pellet impact test data from bovine spinal cords. Building on an existing finite element model of the spinal cord and pia mater, an orthotropic hyperelastic constitutive model was proposed for the dura mater and fit to literature data. The dura mater and cerebrospinal fluid were integrated with the existing finite element model to assess four fluid-structure interaction methods under transverse impact: Lagrange, pressurized volume, smoothed particle hydrodynamics, and arbitrary Lagrangian-Eulerian. The Lagrange method resulted in an overly stiff mechanical response, whereas the pressurized volume method over-predicted compression of the neural tissues. Both the smoothed particle hydrodynamics and arbitrary Lagrangian-Eulerian methods were able to effectively model the impact response of the pellet on the dura mater, outflow of the cerebrospinal fluid, and compression of the spinal cord; however, the arbitrary Lagrangian-Eulerian compute time was approximately five times higher than smoothed particle hydrodynamics. Crucial to implementation in human body models, the smoothed particle hydrodynamics method provided a computationally efficient and representative approach to model spinal cord fluid-structure interaction during transverse impact.

In-Situ Fracture Tolerance of the Metatarsals During Quasi-Static Compressive Loading of the Human Foot.

Accidental foot injuries including metatarsal fractures commonly result from compressive loading. The ability of personal protective equipment to prevent these traumatic injuries depends on the understanding of metatarsal fracture tolerance. However, the in situ fracture tolerance of the metatarsals under direct compressive loading to the foot's dorsal surface remains unexplored, even though the metatarsals are the most commonly fractured bones in the foot. The goal of this study was to quantify the in situ fracture tolerance of the metatarsals under simulated quasi-static compressive loading. Fresh-frozen cadaveric feet (n = 10) were mounted into a testing apparatus to replicate a natural stance and loaded at the midmetatarsals with a cylindrical bar to simulate a crushing-type injury. A 900 N compressive force was initially applied, followed by 225 N successive load increments. Specimens were examined using X-ray imaging between load increments to assess for the presence of metatarsal fractures. Descriptive statistics were conducted for metatarsal fracture force and deformation. Pearson correlation tests were used to quantify the correlation between fracture force with age and body mass index (BMI). The force and deformation at fracture were 1861 ± 642 N (mean ± standard deviation) and 22.6 ± 3.4 mm, respectively. Fracture force was correlated with donor BMI (r = 0.90). Every fractured specimen experienced a transverse fracture in the second metatarsal. New biomechanical data from this study further quantify the metatarsal fracture risk under compressive loading and will help to improve the development and testing of improved personal protective equipment for the foot to avoid catastrophic injury.

A Hyper-Viscoelastic Continuum-Level Finite Element Model of the Spinal Cord Assessed for Transverse Indentation and Impact Loading.

Finite Element (FE) modelling of spinal cord response to impact can provide unique insights into the neural tissue response and injury risk potential. Yet, contemporary human body models (HBMs) used to examine injury risk and prevention across a wide range of impact scenarios often lack detailed integration of the spinal cord and surrounding tissues. The integration of a spinal cord in contemporary HBMs has been limited by the need for a continuum-level model owing to the relatively large element size required to be compatible with HBM, and the requirement for model development based on published material properties and validation using relevant non-linear material data. The goals of this study were to develop and assess non-linear material model parameters for the spinal cord parenchyma and pia mater, and incorporate these models into a continuum-level model of the spinal cord with a mesh size conducive to integration in HBM. First, hyper-viscoelastic material properties based on tissue-level mechanical test data for the spinal cord and hyperelastic material properties for the pia mater were determined. Secondly, the constitutive models were integrated in a spinal cord segment FE model validated against independent experimental data representing transverse compression of the spinal cord-pia mater complex (SCP) under quasi-static indentation and dynamic impact loading. The constitutive model parameters were fit to a quasi-linear viscoelastic model with an Ogden hyperelastic function, and then verified using single element test cases corresponding to the experimental strain rates for the spinal cord (0.32-77.22 s-1) and pia mater (0.05 s-1). Validation of the spinal cord model was then performed by re-creating, in an explicit FE code, two independent ex-vivo experimental setups: 1) transverse indentation of a porcine spinal cord-pia mater complex and 2) dynamic transverse impact of a bovine SCP. The indentation model accurately matched the experimental results up to 60% compression of the SCP, while the impact model predicted the loading phase and the maximum deformation (within 7%) of the SCP experimental data. This study quantified the important biomechanical contribution of the pia mater tissue during spinal cord deformation. The validated material models established in this study can be implemented in computational HBM.

Biomechanical comparison of a C1 posterior arch clamp with C1 lateral mass screws in constructs for C1-C2 fusion.

The aim of this experimental study was to assess the biomechanical performance of a novel C1 posterior arch (C1PA) clamp compared with C1 lateral mass (C1LM) screws in constructs used to treat atlantoaxial instability. These constructs had either C2 pedicle (C2P) screws or C2 translaminar (C2TL) screws. Eight fresh-frozen human cadaveric ligamentous spine specimens (C0-C3) were tested under six conditions: the intact state, the destabilized state after a simulated odontoid fracture, and when instrumented with four constructs (C1LM-C2P, C1LM-C2TL, C1PA-C2P, C1PA-C2TL). Each specimen was tested in a spinal loading simulator that separately applied axial rotation, flexion-extension and lateral bending. In each test condition, displacement controlled angular motion was applied in both directions at a speed of 2 deg/s until a resulting moment of 1.5 Nm was achieved. The measured ranges of motion (ROM) of the C1-C2 segments were compared for each test condition using nonparametric Friedman tests. The destabilized state had significantly more C1-C2 motion (p < 0.05) than the intact state in all cases, and all constructs greatly reduced this motion. C2 pedicle screw constructs that used the C1PA clamp had significantly less C1-C2 motion (p < 0.05) than those with C1LM screws in flexion-extension as well as axial rotation and no statistically significant difference was detected in lateral bending. C2 translaminar screw constructs that used the C1PA clamp had significantly less C1-C2 motion (p < 0.05) than those with C1LM screws in flexion-extension and no statistically significant difference was detected in axial rotation or in lateral bending. Data from the current study suggested that constructs using the novel C1PA clamp would provide as good, or improved, biomechanical stability to the C1-C2 segment compared with constructs using C1LM screws.

Vestibulocollic and Cervicocollic Muscle Reflexes in a Finite Element Neck Model During Multidirectional Impacts.

Active neck musculature plays an important role in the response of the head and neck during impact and can affect the risk of injury. Finite element Human Body Models (HBM) have been proposed with open and closed-loop controllers for activation of muscle forces; however, controllers are often calibrated to specific experimental loading cases, without considering the intrinsic role of physiologic muscle reflex mechanisms under different loading conditions. This study aimed to develop a single closed-loop controller for neck muscle activation in a contemporary male HBM based on known reflex mechanisms and assess how this approach compared to current open-loop controllers across a range of impact directions and severities. Controller parameters were optimized using volunteer data and independently assessed across twelve impact conditions. The kinematics from the closed-loop controller simulations showed good average CORA rating to the experimental data (0.699) for the impacts following the ISO/TR9790 standard. Compared to previously optimized open-loop activation strategy, the average difference was less than 9%. The incorporation of the reflex mechanisms using a closed-loop controller can provide robust performance for a range of impact directions and severities, which is critical to improving HBM response under a larger spectrum of automotive impact simulations.

Night Vision Goggle and Counterweight Use Affect Neck Muscle Activity During Reciprocal Scanning.

BACKGROUND: Mass, moment of inertia, and amplitude of neck motion were altered during a reciprocal scanning task to investigate how night vision goggles (NVGs) use mechanistically is associated with neck trouble among rotary-wing aircrew.METHODS: There were 30 subjects measured while scanning between targets at 2 amplitudes (near and far) and under 4 head supported mass conditions (combinations of helmet, NVGs, and counterweights). Electromyography (EMG) was measured bilaterally from the sternocleidomastoid and upper neck extensors. Kinematics were measured from the trunk and head.RESULTS: Scanning between the far amplitude targets required higher peak angular accelerations (7% increase) and neck EMG (between 1.24.5% increase), lower muscle cocontraction ratios (6.7% decrease), and fewer gaps in EMG (up to a 59% decrease) relative to the near targets. Increasing the mass of the helmet had modest effects on neck EMG, while increasing the moment of inertia did not.DISCUSSION: Target amplitude, not head supported mass configuration, had a greater effect on exposure metrics. Use of NVGs restricts field-of-view, requiring an increased amplitude of neck movement. This may play an important role in understanding links between neck trouble and NVG use.Healey LA, Derouin AJ, Callaghan JP, Cronin DS, Fischer SL. Night vision goggle and counterweight use affect neck muscle activity during reciprocal scanning. Aerosp Med Hum Perform. 2021; 92(3):172181.

Brain response of a computational head model for prescribed skull kinematics and simulated football helmet impact boundary conditions.

Computational human body models (HBM) present a novel approach to predict brain response in football impact scenarios, with prescribed kinematic boundary conditions for the HBM skull typically used at present. However, computational optimization of helmets requires simulation of the coupled helmet and HBM model; which is much more complex and has not been assessed in the context of brain deformation and existing simplified approaches. In the current study, two boundary conditions and the resulting brain deformations were compared using a HBM head model: (1) a prescribed skull kinematics (PK) boundary condition using measured head kinematics from experimental impacts; and (2) a novel detailed simulation of a HBM head and neck, helmet and linear impactor (HBM-S). While lateral and rear impacts exhibited similar levels of maximum principal strain (MPS) in the brain tissue using both boundary conditions, differences were noted in the frontal orientation (at 9.3 m/s, MPS was 0.39 for PK, 0.54 for HBM-S). Importantly, both PK and HBM-S boundary conditions produced a similar distribution of MPS throughout the brain for each impact orientation considered. Within the corpus callosum and thalamus, high MPS was associated with lateral impacts and lower values with frontal and rear impacts. The good correspondence of both boundary conditions is encouraging for future optimization of helmet designs. A limitation of the PK approach is the need for experimental head kinematics data, while the HBM-S can predict brain response for varying impact conditions and helmet configurations, with potential as a tool to improve helmet protection performance.

Multilevel Validation of a Male Neck Finite Element Model With Active Musculature.

Computational models of the human neck have been developed to assess human response in impact scenarios; however, the assessment and validation of such models is often limited to a small number of experimental data sets despite being used to evaluate the efficacy of safety systems and potential for injury risk in motor vehicle collisions. In this study, a full neck model (NM) with active musculature was developed from previously validated motion segment models of the cervical spine. Tissue mechanical properties were implemented from experimental studies, and were not calibrated. The neck model was assessed with experimental studies at three levels of increasing complexity: ligamentous cervical spine in axial rotation, axial tension, frontal impact, and rear impact; postmortem human subject (PMHS) rear sled impact; and human volunteer frontal and lateral sled tests using an open-loop muscle control strategy. The neck model demonstrated good correlation with the experiments ranging from quasi-static to dynamic, assessed using kinematics, kinetics, and tissue-level response. The contributions of soft tissues, neck curvature, and muscle activation were associated with higher stiffness neck response, particularly for low severity frontal impact. Experiments presenting single-value data limited assessment of the model, while complete load history data and cross-correlation enabled improved evaluation of the model over the full loading history. Tissue-level metrics demonstrated higher variability and therefore lower correlation relative to gross kinematics, and also demonstrated a dependence on the local tissue geometry. Thus, it is critical to assess models at the gross kinematic and the tissue levels.

Optimization of muscle activation schemes in a finite element neck model simulating volunteer frontal impact scenarios.

Neck muscle activation is increasingly important for accurate prediction of occupant response in automotive impact scenarios and occupant excursion resulting from active safety systems such as autonomous emergency braking. Muscle activation and optimization in frontal impact scenarios using computational Human Body Models have not been investigated over the broad range of accelerations relevant to these events. This study optimized the muscle activation of a contemporary finite element model of the human head and neck for human volunteer experiments over a range of frontal impact severities (2 g to 15 g). The neck muscles were grouped as flexors and extensors, and optimization was undertaken for each group based on muscle activation level and activation time. The boundaries for optimization were defined using data from the literature and a preliminary parametric study. A linear polynomial method was used to optimize the model head kinematics to the volunteer experiments for each impact severity. The optimized models predicted muscle activation to increase with higher impact severities, and improved the average cross-correlation by 35% (0.561-0.755) relative to the Maximum Muscle Activation (MMA) scheme in the original model. Importantly, a newly proposed Cocontraction Muscle Activation (CMA) scheme for maintaining the head in a neutral posture provided a 23% on average improvement in correlation compared to the MMA scheme. In conclusion, this study identified a new scheme to obtain more accurate response kinematics across multiple impact severities in computational Human Body Models as well as contributing to the understanding of muscle influence during frontal impact scenarios.

Head and Neck Response of an Active Human Body Model and Finite Element Anthropometric Test Device During a Linear Impactor Helmet Test.

It has been proposed that neck muscle activation may play a role in head response resulting from impacts in American Football. The importance of neck stiffness and active musculature in the standard linear impactor helmet test was assessed using a detailed head and neck finite element (FE) model from a current human body model (HBM) compared to a validated hybrid III head and neck FE model. The models were assessed for bare-head and helmeted impacts at three speeds (5.5, 7.4, and 9.3 m/s) and three impact orientations. The HBM head and neck was assessed without muscle activation and with a high level of muscle activation representing a braced condition. The HBM and hybrid III had an average cross-correlation rating of 0.89 for acceleration in the primary impact direction, indicating excellent correspondence regardless of muscle activation. Differences were identified in the axial head acceleration, attributed to axial neck stiffness (correlation rating of 0.45), but these differences did not have a large effect on the overall head response using existing head response metrics (head injury criteria, brain injury criteria, and head impact power). Although responses that develop over longer durations following the impact differed slightly, such as the moment at the base of the neck, this occurred later in time, and therefore, did not considerably affect the short-term head kinematics in the primary impact direction. Though muscle activation did not play a strong role in the head response for the test configurations considered, muscle activation may play a role in longer duration events.