Probabilistic Finite Element Analysis of Human Rib Biomechanics: A Framework for Improved Generalizability.

In dynamic impact events, thoracic injuries often involve rib fractures, which are closely related to injury severity. Previous studies have investigated the behavior of isolated ribs under impact loading conditions, but often neglected the variability in anatomical shape and tissue material properties. In this study, we used probabilistic finite element analysis and statistical shape modeling to investigate the effect of population-wide variability in rib cortical bone tissue mechanical properties and rib shape on the biomechanical response of the rib to impact loading. Using the probabilistic finite element analysis results, a response surface model was generated to rapidly investigate the biomechanical response of an isolated rib under dynamic anterior-posterior load given the variability in rib morphometry and tissue material properties. The response surface was used to generate pre-fracture force-displacement computational corridors for the overall population and a population sub-group of older mid-sized males. When compared to the experimental data, the computational mean response had a RMSE of 4.28N (peak force 94N) and 6.11N (peak force 116N) for the overall population and sub-group respectively, whereas the normalized area metric when comparing the experimental and computational corridors ranged from 3.32% to 22.65% for the population and 10.90% to 32.81% for the sub-group. Furthermore, probabilistic sensitivities were computed in which the contribution of uncertainty and variability of the parameters of interest was quantified. The study found that rib cortical bone elastic modulus, rib morphometry and cortical thickness are the random variables that produce the largest variability in the predicted force-displacement response. The proposed framework offers a novel approach for accounting biological variability in a representative population and has the potential to improve the generalizability of findings in biomechanical studies.

Investigating the Impact of Blunt Force Trauma: A Probabilistic Study of Behind Armor Blunt Trauma Risk.

Evaluating Behind Armor Blunt Trauma (BABT) is a critical step in preventing non-penetrating injuries in military personnel, which can result from the transfer of kinetic energy from projectiles impacting body armor. While the current NIJ Standard-0101.06 standard focuses on preventing excessive armor backface deformation, this standard does not account for the variability in impact location, thorax organ and tissue material properties, and injury thresholds in order to assess potential injury. To address this gap, Finite Element (FE) human body models (HBMs) have been employed to investigate variability in BABT impact conditions by recreating specific cases from survivor databases and generating injury risk curves. However, these deterministic analyses predominantly use models representing the 50th percentile male and do not investigate the uncertainty and variability inherent within the system, thus limiting the generalizability of investigating injury risk over a diverse military population. The DoD-funded I-PREDICT Future Naval Capability (FNC) introduces a probabilistic HBM, which considers uncertainty and variability in tissue material and failure properties, anthropometry, and external loading conditions. This study utilizes the I-PREDICT HBM for BABT simulations for three thoracic impact locations-liver, heart, and lower abdomen. A probabilistic analysis of tissue-level strains resulting from a BABT event is used to determine the probability of achieving a Military Combat Incapacitation Scale (MCIS) for organ-level injuries and the New Injury Severity Score (NISS) is employed for whole-body injury risk evaluations. Organ-level MCIS metrics show that impact at the heart can cause severe injuries to the heart and spleen, whereas impact to the liver can cause rib fractures and major lacerations in the liver. Impact at the lower abdomen can cause lacerations in the spleen. Simulation results indicate that, under current protection standards, the whole-body risk of injury varies between 6 and 98% based on impact location, with the impact at the heart being the most severe, followed by impact at the liver and the lower abdomen. These results suggest that the current body armor protection standards might result in severe injuries in specific locations, but no injuries in others.

The I-PREDICT 50th Percentile Male Warfighter Finite Element Model: Development and Validation of the Thoracolumbar Spine.

Military personnel are commonly at risk of lower back pain and thoracolumbar spine injury. Human volunteers and postmortem human subjects have been used to understand the scenarios where injury can occur and the tolerance of the warfighter to these loading regimes. Finite element human body models (HBMs) can accurately simulate the mechanics of the human body and are a useful tool for understanding injury. In this study, a HBM thoracolumbar spine was developed and hierarchically ï»¿validated as part of the Incapacitation Prediction for Readiness in Expeditionary Domains: an Integrated Computational Tool (I-PREDICT) program. Constitutive material models were sourced from literature and the vertebrae and intervertebral discs were hexahedrally meshed from a 50th percentile male CAD dataset. Ligaments were modeled through attaching beam elements at the appropriate anatomical insertion sites. 94 simulations were replicated from experimental PMHS tests at the vertebral body, functional spinal unit (FSU), and regional lumbar spine levels. The BioRank (BRS) biofidelity ranking system was used to assess the response of the I-PREDICT model. At the vertebral body level, the I-PREDICT model showed good agreement with experimental results. The I-PREDICT FSUs showed good agreement in tension and compression and had comparable stiffness values in flexion, extension, and axial rotation. The regional lumbar spine exhibited "good" biofidelity when tested in tension, compression, extension, flexion, posterior shear, and anterior shear (BRS regional average = 1.05). The validated thoracolumbar spine of the I-PREDICT model can be used to better understand and mitigate injury risk to the warfighter.

Head Impact Exposure in Youth and Collegiate American Football.

The relationship between head impact and subsequent brain injury for American football players is not well-defined, especially for youth. The objective of this study is to quantify and assess Head Impact Exposure (HIE) metrics among youth and collegiate football players. This multi-season study enrolled 639 unique athletes (354 collegiate; 285 youth, ages 9-14), recording 476,209 head impacts (367,337 collegiate; 108,872 youth) over 971 sessions (480 collegiate; 491 youth). Youth players experienced 43 and 65% fewer impacts per competition and practice, respectively, and lower impact magnitudes compared to collegiate players (95th percentile peak linear acceleration (PLA, g) competition: 45.6 vs 61.9; 95th percentile PLA practice: 42.6 vs 58.8; 95th percentile peak rotational acceleration (PRA, rad·s-2) competition: 2262 vs 4422; 95th percentile PRA practice: 2081 vs 4052; 95th percentile HITsp competition: 25.4 vs 32.8; 95th percentile HITsp practice: 23.9 vs 30.2). Impacts during competition were more frequent and of greater magnitude than during practice at both levels. Quantified comparisons of head impact frequency and magnitude between youth and collegiate athletes reveal HIE differences as a function of age, and expanded insight better informs the development of age-appropriate guidelines for helmet design, prevention measures, standardized testing, brain injury diagnosis, and recovery management.

Effect of body size and enhanced helmet systems on risk for motorsport drivers.

OBJECTIVE: Computational modeling has been shown to be a useful tool for simulating representative motorsport impacts and analyzing data for relative injury risk assessment. Previous studies have used computational modeling to analyze the probability of injury in specific regions of a 50th percentile male driver. However, NASCAR drivers can represent a large range in terms of size and female drivers are becoming increasingly more common in the sport. Additionally, motorsport helmets can be outfitted with external attachments, or enhanced helmet systems (EHS), whose effect is unknown relative to head and neck kinematics. The current study expands on this previous work by incorporating the F05-OS and M95-OS into the motorsport environment in order to determine correlations between metrics and factors such as PDOF, resultant ΔV occupant size, and EHS. METHODS: A multi-step computational process was used to integrate the Global Human Body Models Consortium family of simplified occupant models into a motorsport environment. This family included the 5th percentile female (F05-OS), 50th percentile male (M50-OS), and 95th percentile male (M95-OS), which provide a representative range for the size and sex of drivers seen in NASCAR's racing series'. A series of 45 representative impacts, developed from real-world crash data, and set of observed on-track severe impacts were conducted with these models. These impacts were run in triplicate for three helmet configurations: bare helmet, helmet with visor, helmet with visor and camera. This resulted in 450 total simulations. A paired t-test was initially performed as an exploratory analysis to study the effect of helmet configuration on 10 head and neck injury metrics. A mixed-effects model with unstructured covariance matrix was then utilized to correlate the effect between five independent variables (resultant ΔV, body size, helmet configuration, impact quadrant, and steering wheel position) and a selection of 25 metrics. All simulations were conducted in LS-Dyna R. 9.1. RESULTS: Risk estimates from the M50-OS with bare helmet were used as reference values to determine the effect of body size and helmet configuration. The paired t-test found significance for helmet configuration in select head-neck metrics, but the relative increase in these metrics was low and not likely to increase injury risk. The mixed-effects model analyzed statistical relationships across multiple types of variables. Within the mixed-effects model, no significance was found between helmet configuration and metrics. The greatest effect was found from resultant ΔV, body size, and impact quadrant. CONCLUSIONS: Overall, smaller drivers showed statistically significant reductions in injury metrics, while larger drivers showed statistically significant increases. Lateral impacts showed the greatest effect on neck metrics and, on average, showed decreases for head metrics related to linear acceleration and increases for head metrics related to angular velocity. HBM parametric studies such as this may provide an avenue to assist injury detection for motorsport incidents, improve triage effectiveness, and assist in the development of safety standards.

Analysis of longitudinal head impact exposure and white matter integrity in returning youth football players.

OBJECTIVE: The objective of this study was to characterize changes in head impact exposure (HIE) across multiple football seasons and to determine whether changes in HIE correlate with changes in imaging metrics in youth football players. METHODS: On-field head impact data and pre- and postseason imaging data, including those produced by diffusion tensor imaging (DTI), were collected from youth football athletes with at least two consecutive seasons of data. ANCOVA was used to evaluate HIE variations (number of impacts, peak linear and rotational accelerations, and risk-weighted cumulative exposure) by season number. DTI scalar metrics, including fractional anisotropy, mean diffusivity, and linear, planar, and spherical anisotropy coefficients, were evaluated. A control group was used to determine the number of abnormal white matter voxels, which were defined as 2 standard deviations above or below the control group mean. The difference in the number of abnormal voxels between consecutive seasons was computed for each scalar metric and athlete. Linear regression analyses were performed to evaluate relationships between changes in HIE metrics and changes in DTI scalar metrics. RESULTS: There were 47 athletes with multiple consecutive seasons of HIE, and corresponding imaging data were available in a subsample (n = 19) of these. Increases and decreases in HIE metrics were observed among individual athletes from one season to the next, and no significant differences (all p > 0.05) in HIE metrics were observed by season number. Changes in the number of practice impacts, 50th percentile impacts per practice session, and 50th percentile impacts per session were significantly positively correlated with changes in abnormal voxels for all DTI metrics. CONCLUSIONS: These results demonstrate a significant positive association between changes in HIE metrics and changes in the numbers of abnormal voxels between consecutive seasons of youth football. Reducing the number and frequency of head impacts, especially during practice sessions, may decrease the number of abnormal imaging findings from one season to the next in youth football.

The Effect of Player Contact Characteristics on Head Impact Exposure in Youth Football Games.

To reduce head impact exposure (HIE) in youth football, further understanding of the context in which head impacts occur and the associated biomechanics is needed. The objective of this study was to evaluate the effect of contact characteristics on HIE during player versus player contact scenarios in youth football. Head impact data and time-synchronized video were collected from 4 youth football games over 2 seasons in which opposing teams were instrumented with the Head Impact Telemetry (HIT) System. Coded contact characteristics included the player's role in the contact, player speed and body position, contact height, type, and direction, and head contact surface. Head accelerations were compared among the contact characteristics using mixed-effects models. Among 72 instrumented athletes, 446 contact scenarios (n = 557 impacts) with visible opposing instrumented players were identified. When at least one player had a recorded impact, players who were struck tended to have higher rotational acceleration than players in striking positions. When both players had a recorded impact, lighter players and taller players experienced higher mean head accelerations compared with heavier players and shorter players. Understanding the factors influencing HIE during contact events in football may help inform methods to reduce head injury risk.

Simulation-based assessment of injury risk for an average male motorsport driver.

OBJECTIVE: While well-protected through a variety of safety countermeasures, motorsports drivers can be exposed to a large variety of crash modes and severities. Computational human body models (HBMs) are currently used to assess occupant safety for the general driving public in production vehicles. The purpose of this study was to incorporate a HBM into a motorsport environment using a simulation-based approach and provide quantitative data on relative risk for on-track motorsport crashes. METHODS: Unlike a traditional automotive seat, the NASCAR driver environment is driver-customized and form-fitting. A multi-step process was developed to integrate the Global Human Body Models Consortium (GHBMC) 50th percentile male simplified occupant into a representative motorsport environment which includes a donned helmet, a 7-point safety belt system, head and neck restraint (HNR), poured-foam seat, steering wheel, and leg enclosure. A series of 45 representative impacts, developed from real-world crash data, of varying severity (10 kph ≤ ΔV ≤ 100 kph) and impact direction (∼290° ≤ PDOF ≤ 20°) were conducted with the GHBMC 50th percentile male simplified occupant (M50-OS v2.2). Kinematic and kinetic data, and a variety of injury criteria, were output from each of the simulations and used to calculate AIS 1+, 2+, and 3+ injury risk. All simulations were conducted in LS-Dyna R. 9.1. RESULTS: Injury risk of the occupant using the previously mentioned injury criteria was calculated for the head, neck, thorax, and lower extremity, and the probability of injury for each region was plotted. Of the simulated impacts, five had a maximum AIS 1+ injury risk >20%, six had a maximum AIS 2+ injury risk >10%, and no cases had a maximum AIS 3+ injury >1%. Overall, injury risk estimates were reasonable compared to on-track data reported from Patalak et al. (2020). CONCLUSIONS: Beyond injury risk, the study is the first of its kind to provide mechanical loading values likely experienced during motorsports crash incidents with crash pulses developed from real-world data. Given the severity of the crash pulses, the simulated environments reinforce the need for the robust safety environment implemented by NASCAR.

Injury risk curves in far-side lateral motor vehicle crashes by AIS level, body region and injury code.

OBJECTIVE: The objective of this study was to develop injury risk curves as a function of change in vehicle velocity for occupants in far-side lateral motor vehicle crashes (MVCs) by AIS level, body region, and specific AIS codes that commonly occur in this crash mode. METHODS: The National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) years 2000-2015 database was queried, resulting in 4,495 non-weighted far-side crashes. For each case, occupant age, sex, and the following metadata were collected: vehicle model year, vehicle body type, lateral delta-v, normalized PDOF, multiple impacts, belt use, seat position, object contacted, striking vehicle body type, maximum crush extent and side airbag deployment. Multivariable logistic regression was used to develop risk curves for AIS 2+ through 5+ injuries, AIS 2+ injuries by body region (head, thorax, lower extremity), and for each of the 10 most frequent far-side AIS 2+ injuries. Significant covariates were determined by backwards elimination (p < 0.05). The full dataset and a subsampled dataset of only cases with side airbag deployment were used to develop risk curves. RESULTS: For AIS 2+ through 5+ injury, greater delta-V was associated with greater injury risk (OR's: 2.48-3.66 per 11.9 kph increase) and belt use was associated with lower risk (OR's: 0.04-0.36 compared to unbelted). Multiple impacts were significant predictors of increased AIS 3+, 4+ and 5+ injury risk (OR's: 2.56, 2.27 and 2.83 compared to single impact). For AIS 2+ body region injuries, lateral delta-V and maximum CDC extent were positively associated with increased head, thorax and lower extremity injury risk while belt use was associated with lower risk. Increased lateral delta-v, unbelted status, and greater maximum CDC extent frequently increased injury risk for the most common far-side injuries. Side airbag deployment was not a significant covariate for the injury risk models. CONCLUSIONS: The resulting risk models expand upon previous literature gaps to provide a more comprehensive view of contributors to injury risk for occupants in far-side MVCs. This study yields risk curves based on the latest available NASS-CDS data.

Physical Performance Measures Correlate with Head Impact Exposure in Youth Football.

PURPOSE: Head impact exposure (HIE) (i.e., magnitude and frequency of impacts) can vary considerably among individuals within a single football team. To better understand individual-specific factors that may explain variation in head impact biomechanics, this study aimed to evaluate the relationship between physical performance measures and HIE metrics in youth football players. METHODS: Head impact data were collected from youth football players using the Head Impact Telemetry System. Head impact exposure was quantified in terms of impact frequency, linear and rotational head acceleration, and risk-weighted cumulative exposure metrics (RWELinear, RWERotational, and RWECP). Study participants completed four physical performance tests: vertical jump, shuttle run, three-cone, and 40-yard sprint. The relationships between performance measures, and HIE metrics were evaluated using linear regression analyses. RESULTS: A total of 51 youth football athletes (ages, 9-13 yr) completed performance testing and received combined 13,770 head impacts measured with the Head Impact Telemetry System for a full season. All performance measures were significantly correlated with total number of impacts in a season, RWELinear-Season, and all RWE-Game metrics. The strongest relationships were between 40-yard sprint speed and all RWE-Game metrics (all P ≤ 0.0001 and partial R > 0.3). The only significant relationships among HIE metrics in practice were between shuttle run speed and total practice impacts and RWELinear-Practices, 40 yard sprint speed and total number of practice impacts, and three-cone speed and 95th percentile number of impacts/practice. CONCLUSIONS: Generally, higher vertical jump height and faster times in speed and agility drills were associated with higher HIE, especially in games. Physical performance explained less variation in HIE in practices, where drills and other factors, such as coaching style, may have a larger influence on HIE.

Lumbar Spine Response of Computational Finite Element Models in Multidirectional Spaceflight Landing Conditions.

The goals of this study are to compare the lumbar spine response variance between the hybrid III, test device for human occupant restraint (THOR), and global human body models consortium simplified 50th percentile (GHBMC M50-OS) finite element models and evaluate the sensitivity of lumbar spine injury metrics to multidirectional acceleration pulses for spaceflight landing conditions. The hybrid III, THOR, and GHBMC models were positioned in a baseline posture within a generic seat with side guards and a five-point restraint system. Thirteen boundary conditions, which were categorized as loading condition variables and environmental variables, were included in the parametric study using a Latin hypercube design of experiments. Each of the three models underwent 455 simulations for a total of 1365 simulations. The hybrid III and THOR models exhibited similar lumbar compression forces. The average lumbar compression force was 45% higher for hybrid III (2.2 ± 1.5 kN) and 51% higher for THOR (2.0 ± 1.6 kN) compared to GHBMC (1.3 ± 0.9 kN). Compared to hybrid III, THOR sustained an average 64% higher lumbar flexion moment and an average 436% higher lumbar extension moment. The GHBMC model sustained much lower bending moments compared to hybrid III and THOR. Regressions revealed that lumbar spine responses were more sensitive to loading condition variables than environmental variables across all models. This study quantified the intermodel lumbar spine response variations and sensitivity between hybrid III, THOR, and GHBMC. Results improve the understanding of lumbar spine response in spaceflight landings.

Development of a Concussion Risk Function for a Youth Population Using Head Linear and Rotational Acceleration.

Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions (n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82-0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s2 compared to 4412 ± 2326 rad/s2. These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

Head injury metric response in finite element ATDs and a human body model in multidirectional loading regimes.

Objective: The objective was to quantify head injury metric sensitivity of the 50th percentile male Hybrid III, THOR, and Global Human Body Models Consortium simplified occupant (GHBMC M50-OS) to changes in loading conditions in loading regimes that may be experienced by occupants of spaceflight vehicles or highly autonomous vehicles (HAVs) with nontraditional seating configurations.Methods: A Latin hypercube (LHD) design of experiments (DOE) was employed to develop boundary conditions for 455 unique acceleration profiles. Three previously validated finite element (FE) models of the Hybrid III anthropomorphic test device (ATD), THOR ATD, and GHBMC M50-OS were positioned in an upright 90°-90°-90° seat and with a 5-point belt. Acceleration pulses were applied to each of the three occupants in the ± X, +Y, and ± Z directions, with peak resultant acceleration magnitudes ranging from 5 to 20 G and times to peak ranging from 32.5 to 120.8 ms with duration 250 ms, resulting in 1,248 simulations. Head injury metrics included peak linear head acceleration, peak rotational head acceleration, head injury criteria (HIC15), and brain injury criteria (BrIC). Injury metrics were regressed against boundary condition parameters using 2nd order multiple polynomial regression, and compared between occupants using matched pairs Wilcoxon signed rank analysis.Results: Across the 416 matched-simulations that reached normal termination with all three models, HIC15 values ranged from 1.0-396.5 (Hybrid III), 1.2-327.9 (THOR), and 0.6-585.6 (GHBMC). BrIC ranged from 0.03-0.95 (Hybrid III), 0.03-1.21 (THOR), and 0.04-0.84 (GHBMC). Wilcoxon signed rank analysis demonstrated significant pairwise differences between each of the three occupant models for head injury metrics. For HIC15, the largest divergence between GHBMC and the ATDs was observed in simulations with components of combined underbody and rear impact loading. The three models performed most similarly with respect to BrIC output when loaded in a frontal direction. Both the GHBMC and the Hybrid III produced lower values of BrIC than the THOR on average, with the differences most pronounced in rear impact loading.Conclusion: In conclusion, observed differences between the occupant models' head injury metric output were quantified. Loading direction had a large effect on metric outcome and metric comparability across models, with frontal and rear impacts with low vertical acceleration tending to be the most similar. One explanation for these differences could be the differences in neck stiffness between the models that allowed more rotation in the GHBMC and THOR. Care should be taken when using ATDs as human volunteer surrogates in these low energy events.

Modeling Human Volunteers in Multidirectional, Uni-axial Sled Tests Using a Finite Element Human Body Model.

A goal of the Human Research Program at National Aeronautics and Space Administration (NASA) is to analyze and mitigate the risk of occupant injury due to dynamic loads. Experimental tests of human subjects and biofidelic anthropomorphic test devices provide valuable kinematic and kinetic data related to injury risk exposure. However, these experiments are expensive and time consuming compared to computational simulations of similar impact events. This study aimed to simulate human volunteer biodynamic response to unidirectional accelerative loading. Data from seven experimental studies involving 212 volunteer tests performed at the Air Force Research Laboratory were used to reconstruct 13 unique loading conditions across four different loading directions using finite element human body model (HBM) simulations. Acceleration pulses and boundary conditions from the experimental tests were applied to the Global Human Body Models Consortium (GHBMC) simplified 50th percentile male occupant (M50-OS) using the LS-Dyna finite element solver. Head acceleration, chest acceleration, and seat belt force traces were compared between the experimental and matched simulation signals using correlation and analysis (CORA) software and averaged into a comprehensive response score ranging from 0 to 1 with 1 representing a perfect match. The mean comprehensive response scores were 0.689 ± 0.018 (mean ± 1 standard deviation) in two frontal simulations, 0.683 ± 0.060 in four rear simulations, 0.676 ± 0.043 in five lateral simulations, and 0.774 ± 0.013 in two vertical simulations. The CORA scores for head and chest accelerations in these simulations exceeded mean scores reported in the original development and validation of the GHBMC M50-OS model. Collectively, the CORA scores indicated that the HBM in these boundary conditions closely replicated the kinematics of the human volunteers across all loading directions.

Multidirection Validation of a Finite Element 50th Percentile Male Hybrid III Anthropomorphic Test Device for Spaceflight Applications.

The use of anthropomorphic test devices (ATDs) for calculating injury risk of occupants in spaceflight scenarios is crucial for ensuring the safety of crewmembers. Finite element (FE) modeling of ATDs reduces cost and time in the design process. The objective of this study was to validate a Hybrid III ATD FE model using a multidirection test matrix for future spaceflight configurations. Twenty-five Hybrid III physical tests were simulated using a 50th percentile male Hybrid III FE model. The sled acceleration pulses were approximately half-sine shaped, and can be described as a combination of peak acceleration and time to reach peak (rise time). The range of peak accelerations was 10-20 G, and the rise times were 30-110 ms. Test directions were frontal (-GX), rear (GX), vertical (GZ), and lateral (GY). Simulation responses were compared to physical tests using the correlation and analysis (CORA) method. Correlations were very good to excellent and the order of best average response by direction was -GX (0.916±0.054), GZ (0.841±0.117), GX (0.792±0.145), and finally GY (0.775±0.078). Qualitative and quantitative results demonstrated the model replicated the physical ATD well and can be used for future spaceflight configuration modeling and simulation.

Computational modeling and analysis of thoracolumbar spine fractures in frontal crash reconstruction.

OBJECTIVE: This study aimed to reconstruct 11 motor vehicle crashes (6 with thoracolumbar fractures and 5 without thoracolumbar fractures) and analyze the fracture mechanism, fracture predictors, and associated parameters affecting thoracolumbar spine response. METHODS: Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM). The SVM was tuned to each case vehicle and the Total HUman Model for Safety (THUMS) Ver. 4.01 was scaled and positioned in a baseline configuration to mimic the documented precrash driver posture. The event data recorder crash pulse was applied as a boundary condition. For the 6 thoracolumbar fracture cases, 120 simulations to quantify uncertainty and response variation were performed using a Latin hypercube design of experiments (DOE) to vary seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Vertebral loads and bending moments were analyzed, and lumbar spine indices (unadjusted and age-adjusted) were developed to quantify the combined loading effect. Maximum principal strain and stress data were collected in the vertebral cortical and trabecular bone. DOE data were fit to regression models to examine occupant positioning and thoracolumbar response correlations. RESULTS: Of the 11 cases, both the vertebral compression force and bending moment progressively increased from superior to inferior vertebrae. Two thoracic spine fracture cases had higher average compression force and bending moment across all thoracic vertebral levels, compared to 9 cases without thoracic spine fractures (force: 1,200.6 vs. 640.8 N; moment: 13.7 vs. 9.2 Nm). Though there was no apparent difference in bending moment at the L1-L2 vertebrae, lumbar fracture cases exhibited higher vertebral bending moments in L3-L4 (fracture/nonfracture: 45.7 vs. 33.8 Nm). The unadjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 9 of the 11 cases (sensitivity = 1.0; specificity = 0.6). The age-adjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 10 of the 11 cases (sensitivity = 1.0; specificity = 0.8). The age-adjusted principal stress in the trabecular bone was an excellent indicator of fracture occurrence (sensitivity = 1.0; specificity = 1.0). A rearward seat track position and reclined seatback increased the thoracic spine bending moment by 111-329%. A more reclined seatback increased the lumbar force and bending moment by 16-165% and 67-172%, respectively. CONCLUSIONS: This study provided a computational framework for assessing thoracolumbar fractures and also quantified the effect of precrash driver posture on thoracolumbar response. Results aid in the evaluation of motor vehicle crash-induced vertebral fractures and the understanding of factors contributing to fracture risk.

Head Impact Exposure in Practices Correlates With Exposure in Games for Youth Football Players.

This study aimed to compare head impact exposures between practices and games in football players ages 9 to 14 years, who account for approximately 70% of all football players in the United States. Over a period of 2 seasons, 136 players were enrolled from 3 youth programs, and 49,847 head impacts were recorded from 345 practices and 137 games. During the study, individual players sustained a median of 211 impacts per season, with a maximum of 1226 impacts. Players sustained 50th (95th) percentile peak linear acceleration of 18.3 (46.9) g, peak rotational acceleration of 1305.4 (3316.6) rad·s-2, and Head Impact Technology Severity Profile of 13.7 (24.3), respectively. Overall, players with a higher frequency of head impacts at practices recorded a higher frequency of head impacts at games (P < .001, r2 = .52), and players who sustained a greater average magnitude of head impacts during practice also recorded a greater average magnitude of head impacts during games (P < .001). The youth football head impact data quantified in this study provide valuable insight into the player exposure profile, which should serve as a key baseline in efforts to reduce injury.

Numerical investigation of driver lower extremity injuries in finite element frontal crash reconstruction.

OBJECTIVE: Lower extremity injuries are the most frequent Abbreviated Injury Scale (AIS) 2 injury for drivers in frontal crashes. The objective was to reconstruct 11 real-world motor vehicle crashes (2 with AIS 2+ distal lower extremity injury and 9 without lower extremity injury) and to analyze the vehicle parameters and driver attributes that affect injury risk. METHODS: Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM) using a semi-automated optimization method. The SVM was tuned to each corresponding vehicle and the Total HUman Model for Safety (THUMS) Ver 4.01 was scaled and positioned in a baseline configuration to mimic the documented precrash driver posture. The event data recorder crash pulse was applied as the boundary condition for each case. Additionally, for the 2 cases with lower extremity injury, 120 simulations to quantify the uncertainty and response variation were performed varying the following parameters using a Latin hypercube design of experiment (DOE): seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Injury metrics implemented within THUMS were calculated from the femur, tibia, and ankle and cross-compared among the 11 baseline cases using tibia index and multiple injury risk functions. Kinetic and kinematic data from the 120-simulation DOE were analyzed and fit to regression models to examine any causal relationship between occupant positioning and lower extremity injury risk. RESULTS: Of the 11 real-world crashes, both cases with lower extremity injuries resulted in elevated tibia axial forces and resultant bending moments, compared to the 9 cases without lower extremity injury. The average tibia index of the 2 cases with distal lower extremity injury (left: 1.79; right: 1.19) was higher than that in the 9 cases without lower extremity injury (left: 1.16, P =.024; right: 0.82, P =.024). An increased risk of AIS 2+ tibia shaft (33.6%), distal tibia and hindfoot (20.0%), as well as ankle malleolar (14.5%) fracture was also observed for the injured compared to the noninjured cases. Rearward seat track position, reclined seat back angle, and reduced seat height were correlated with elevated tibia axial force and increased tibia index, imposing additional lower extremity injury risk. CONCLUSIONS: This study provides a computational framework for assessing lower extremity injuries and elucidates the effect of precrash driver posture on lower extremity injury risk while accounting for vehicle parameters and driver attributes. Results from the study aid in the evaluation of real-world injury data, the understanding of factors contributing to injury risk, and the prevention of lower extremity injuries.

Validation of a Finite Element 50th Percentile THOR Anthropomorphic Test Device in Multiple Sled Test Configurations.

Computational models of anthropomorphic test devices (ATDs) can be used in crash simulations to quantify the injury risks to occupants in both a cost-effective and time-sensitive manner. The purpose of this study was to validate the performance of a 50th percentile THOR finite element (FE) model against a physical THOR ATD in 11 unique loading scenarios. Physical tests used for validation were performed on a Horizontal Impact Accelerator (HIA) where the peak sled acceleration ranged from 8-20 G and the time to peak acceleration ranged from 40-110 ms. The directions of sled acceleration relative to the THOR model consisted of -GX (frontal impact), +GY (left-sided lateral impact), and +GZ (downward vertical impact) orientations. Simulation responses were compared to physical tests using the CORrelation and Analysis (CORA) method. Using a weighted method, the average response and standard error by direction was +GY (0.83±0.03), -GX (0.80±0.01), and +GZ (0.76±0.03). Qualitative and quantitative results demonstrated the FE model's kinetics and kinematics were sufficiently validated against its counterpart physical model in the tested loading directions.

Head Impact Exposure in Youth Football: Comparing Age- and Weight-Based Levels of Play.

Approximately 5,000,000 athletes play organized football in the United States, and youth athletes constitute the largest proportion with ∼3,500,000 participants. Investigations of head impact exposure (HIE) in youth football have been limited in size and duration. The objective of this study was to evaluate HIE of athletes participating in three age- and weight-based levels of play within a single youth football organization over four seasons. Head impact data were collected using the Head Impact Telemetry (HIT) System. Mixed effects linear models were fitted, and Wald tests were used to assess differences in head accelerations and number of impacts among levels and session type (competitions vs. practices). The three levels studied were levels A (n = 39, age = 10.8 ± 0.7 years, weight = 97.5 ± 11.8 lb), B (n = 48, age = 11.9 ± 0.5 years, weight = 106.1 ± 13.8 lb), and C (n = 32, age = 13.0 ± 0.5 years, weight = 126.5 ± 18.6 lb). A total of 40,538 head impacts were measured. The median/95th percentile linear head acceleration for levels A, B, and C was 19.8/49.4g, 20.6/51.0g, and 22.0/57.9g, respectively. Level C had significantly greater mean linear acceleration than both levels A (p = 0.005) and B (p = 0.02). There were a significantly greater number of impacts per player in a competition than in a practice session for all levels (A, p = 0.0005, B, p = 0.0019, and C, p < 0.0001). Athletes at lower levels experienced a greater percentage of their high magnitude impacts (≥ 80g) in practice, whereas those at the highest level experienced a greater percentage of their high magnitude impacts in competition. These data improve our understanding of HIE within youth football and are an important step in making evidence-based decisions to reduce HIE.