Weight loss in older age can cause bone loss. In older adults with overweight/obesity in a weight loss trial, 6-month hip bone strength increased with higher protein intake versus controls consuming the Recommended Dietary Allowance. However, greater weight loss was associated with greater 18-month hip bone mineral density loss. PURPOSE:Weight loss (WL) to treat obesity in older age can exacerbate bone loss. METHODS:This trial assessed the effects of higher protein intake on hip bone outcomes in 187 older adults with overweight/obesity participating in 6 months of active WL (caloric restriction + aerobic exercise) followed by a 12-month maintenance phase. Participants were randomized to either the Recommended Dietary Allowance for protein intake of 0.8 g protein/kg body weight/day (RecProt) or higher protein intake of 1.2 g protein/kg/day for the 6-month WL period only (6-mo HiProt) or the full 18-month period (18-mo HiProt). CT scans at baseline, 6 months, and 18 months were analyzed for hip volumetric bone mineral density (vBMD) and cortical thickness; bone strength was assessed via finite element modeling of a sideways fall. Areal (a)BMD was measured with hip dual-energy X-ray absorptiometry. Analyses examined 6-month and 18-month bone changes using analysis of covariance, and Spearman's correlations of WL vs. bone changes. RESULTS:Greater WL was associated with greater gains in hip bone strength (p = 0.007) at 6 months, but greater trabecular vBMD loss at 18 months (p = 0.011) and aBMD loss at 6 and 18 months (p < 0.001). Hip bone strength increased 3.8 ± 1.7% over 6 months in the 18-mo HiProt group vs. 0.5 ± 1.6% in the RecProt group (p = 0.02) despite similar 6-month WL across groups (-8.0 ± 5.0%); however, there were no differences between the other groups. Eighteen-month group differences were non-significant. CONCLUSION:Higher protein intake had a beneficial effect on hip bone strength in older adults with overweight/obesity undergoing a WL intervention over the short-term.

This study investigated sex-specific differences in thoracic injury prevalence, causation, and rib fracture patterns among seriously injured occupants in frontal motor vehicle collisions. Crash Injury Research and Engineering Network (CIREN) data from 2005 to 2022 included 793 front-seat occupants aged 16 years and older with Abbreviated Injury Scale 2+ thorax injury, representing 1802 thoracic injuries. Injuries were grouped as rib fracture, sternum fracture, hemo/pneumothorax, lung injury, heart injury, and other. A weighted scoring system captured contributions of involved physical components to each injury. Logistic and linear regression with generalized estimating equations assessed sex associations with injury presence and causation. Two models were estimated: a comprehensively adjusted model including demographic, crash, vehicle, restraint, and airbag deployment, and a simplified model adjusting for age, body mass index, delta-V, and occupant role. Among occupants with AIS 2+ thoracic injuries, sex-specific differences were observed in injury patterns and causation. Females were less likely than males to sustain lung injuries (OR = 0.70, p = 0.038) and more likely to sustain rib fractures (OR = 1.25, p = 0.006). Females had higher odds of rib fractures attributed to seatbelt loading in both models (Full: OR = 2.20, p = 0.005; Simplified: OR = 1.55, p = 0.021). Females were less likely than males to sustain lung injuries (OR = 0.17, p = 0.042) and hemo/pneumothoraces (OR = 0.15, p = 0.044) from instrument panel loading. Steering wheel, airbag, and other components showed no significant sex-specific associations with thoracic injury. Rib fracture patterns showed clusters along the seatbelt path in belted occupants and a more diffuse pattern in unbelted occupants, with minimal significant findings of differences between sexes. These findings contribute to the growing evidence of sex-specific injury patterns and may inform future research on injury prediction and prevention strategies. However, this dataset includes only occupants with AIS 2+ thoracic injuries and therefore cannot be extrapolated to the general population or to collisions outside those represented in the sample.

OBJECTIVE:Lap belt submarining increases risk of abdominal injuries. Seat parameters, restraint systems, crash severity (delta-V), and occupant size all influence submarining outcomes following vehicle crash. The objectives of this research were to 1. Identify which seat and restraint parameters have the greatest effect on lap belt submarining of small female and midsize male models in vehicle crash and 2. Determine if these findings were consistent between human body models and crash dummies. METHODS:800 simulations were conducted using GHBMC simplified occupant models (M50 THAN-OS v2.3 and F05 THAN-OS v2.3) and THOR ATD models (50 M v1.9.2 and 05 F v1.5.2) representing midsize male and small female occupants. The THAN-OS versions of the human models were sized to match the corresponding THOR dummies. All simulations were performed in a simplified sled environment incorporating an OEM seat model. Seven parameters identified in literature as influential to submarining were systematically varied in a design of experiments. These included seatback recline angle, seat cushion angle, buckle anchor position, knee bolster presence, seatbelt load-limiter, retractor/anchor pretensioner, and delta-V. Submarining was defined as the instant the lower edge of the lap belt passed over the ASIS and was identified through a python-based algorithm which was further verified through visual inspection. Following classification of submarining outcomes, univariate logistic regression was performed to evaluate the association between individual parameters and submarining occurrence. Multivariable logistic regression was then used to assess the independent effect of each parameter while controlling for all others. Odds ratios were calculated to quantify effect size, and statistical significance was assessed at α = 0.05. Wald chi-square statistics derived from multivariable models were used to rank the relative contribution of each parameter. Analyses were performed for all models combined and then stratified by model type and sex. RESULTS:In both univariate and multivariable analyses across all simulations, statistically significant associations with submarining were observed for seatback recline angle, knee bolster presence, seat cushion angle, delta-V, and anchor position. Based on Wald chi-square statistics, parameters ranked from greatest to least contribution to submarining response were anchor position, seat cushion angle, seatback recline angle, knee bolster presence, delta-V, pretensioning load, and load-limiting level. Differences in effect magnitude and significance were observed between model type and sex, indicating model/sex-dependent sensitivity to parameter variations; however, overall parameter influence on submarining remained largely consistent between models. CONCLUSIONS:Anchor position, seat cushion angle, and seatback recline angle were identified as the most influential parameters in altering the likelihood of lap belt submarining across both HBMs and ATDs. Importantly, it was found that both HBMs and ATDs indicated similar parameters that were linked to submarining likelihood. These findings support the design of future experimental tests to capture both submarining and non-submarining responses, and building increased confidence in both computational HBMs and physical surrogates.

OBJECTIVE:Bone mineral density (BMD) and muscle health influence an occupant's tolerance to motor vehicle crash (MVC), and these musculoskeletal factors can be used to design more effective countermeasures. CT imaging routinely acquired during trauma evaluation can be leveraged to obtain volumetric (v)BMD and muscle metrics, yet extracting measurements manually from CT is time-consuming and inconsistent, typically limiting it to single anatomical regions. In this retrospective observational study, we applied an existing AI-based CT segmentation tool to characterize the musculoskeletal status of MVC occupants. METHODS:An external cohort of 55 adults with CT scans including a bone calibration phantom was used to validate the automated segmentation of trunk muscle cross-sectional area (CSA) and an automated tissue-calibrated method for vBMD. Agreement with manual CSA and phantom-calibrated vBMD was assessed via correlation and Bland-Altman analyses. The validated automated pipeline was then applied to 851 CT scans from Crash Injury Research and Engineering Network (CIREN) cases collected between 2005-2023. The Data Analysis and Facilitation Suite (v3.11.3, Voronoi Health Analytics) software was used to measure lumbar spine (L1-L4), pelvis, femur head, femur neck and femur trochanter + shaft vBMD, as well as trunk muscle CSA and density. Sarcopenia was defined as a trunk muscle CSA divided by height squared <38.5 cm2/m2 for females and <52.4 cm2/m2 for males. Osteopenia was defined as lumbar spine vBMD <145 mg/cm3. These characteristics were examined in association to regional fracture count with abbreviated injury scale (AIS) severity and injury severity score (ISS) using negative binominal regression, including crash variables (delta-V, belt status, driver status, airbag deployment, principal direction of force, model year, curb weight) and occupant characteristics (age, sex, height, weight). RESULTS:In the validation cohort (64% female; ages 66 ± 4), automated and manual trunk muscle CSA measurements agreed (r = 0.996; p < 0.0001), with small average differences (-4.9 cm2). Automated tissue-calibrated lumbar vBMD closely matched phantom-calibrated values (r = 0.938, mean difference -0.21 mg/cm³), and femur regions showed similar agreement (correlation = 0.865-0.927; all p < 0.0001).In CIREN occupants (56% female; ages 47 ± 20), 31% had sarcopenia, 28% had osteopenia, and 14% osteosarcopenia according to the CT-based definitions. vBMD declined with age across all regions (all p < 0.0001). Lower vBMD was associated with higher ISS in the pelvis (p = 0.003), femur head (p < 0.0001), femur neck (p < 0.0001), and trochanter + shaft (p = 0.00087). Additionally, a 10 mg/cm³ higher femur head vBMD was associated with 1.6% fewer AIS 2 fractures (p-value = 0.005). CONCLUSIONS:Application of an AI-based segmentation platform to MVC CT scans demonstrated that compromised musculoskeletal tissue quality is common and associated with fractures and injury severity beyond traditional occupant and crash characteristics. This suggests that musculoskeletal profiling can inform MVC injury prevention, occupant protection design, and post-crash care strategies.

OBJECTIVES:The overarching objective of this study was to reconstruct five real-world pedestrian crashes using data from the Vulnerable Road User In-Depth Crash Investigation Study (VICIS) database, the Global Human Body Models Consortium (GHBMC) simplified pedestrian models, and morphed generic vehicle (GV) models reflecting U.S. vehicle front-end geometry to investigate pedestrian injury risks, compare simulated injury outcomes and contact kinematics with real-world observations, and evaluate the suitability of these simplified models for crash reconstruction. METHODS:Five real-world pedestrian crashes from VICIS were reconstructed based on injury distribution and test data availability. Cases included four males (ages 14, 48, 56, and 64) and one female (age 57). Vehicles included three sport utility vehicles (SUVs) and two sedans, impacting at an average speed of 47 kph (range: 16-65 kph). Sedan and SUV GVs were morphed using computer-aided design (CAD) models to match front-end geometry. The windshield was modeled as a three-layer structure with fracture-enabled outer glass layers. Morphed models were validated against Euro New Car Assessment Program (NCAP) headform, upper legform, and lower legform tests using correlation and analysis (CORA) ratings. The models were used to reconstruct crashes by applying initial velocity and scaling GHBMC pedestrian models to match the case pedestrian height and weight. The contact points from simulations were compared with real-world crash evidence. AIS2+ injuries from the cases were compared to reconstructed results using injury metrics and risk functions. RESULTS:The average ± SD CORA score for all pedestrian NCAP validation tests was 0.72 ± 0.1, indicating a good rating. Contact points from reconstructions closely matched real-world crashes. Brain injury criterion (BrIC) and cumulative strain damage measure (CSDM) injury risks (>90%) predicted cerebral injuries, while the Head Injury Criterion (HIC) injury risks remained low in two cases (<5%), underpredicting skull fractures. Chest deflection predicted thorax injury (injury risk >73%), whereas thoracic trauma index (TTI) risks were low (<50%). Tibia fractures from the cases were confirmed by injury risk estimations (>90%) using the revised tibia index (RTI). CONCLUSIONS:The GV-based pedestrian crash reconstruction framework demonstrated strong potential for real-world crash studies. CAD-based morphing enabled close matching of case vehicle front geometry, and material/structural tuning enhanced model responses aligned with physical vehicle data. The results of the reconstruction matched well with the actual crash data.

OBJECTIVE:The objective of this study is to examine the effects of seatback angle, seat rotation, and impact speed on occupant kinematics and injury risk in highly automated vehicles. METHODS:The study utilized the Global Human Body Models Consortium midsize male (M50-OS+B) simplified occupant model in a simplified vehicle model (SVM) to simulate frontal crashes. The M50-OS+B model was gravity-settled and belted into the driver and left rear passenger seat. To investigate the effects of seatback angle, seat rotation, and impact speed on occupant kinematics and injury risk in frontal crashes, a design of experiments (DOE) was conducted. The DOE incorporated four seatback angles (13°, 23°, 45°, and 57.5° about vertical), four seat rotation angles (0°, 25°, 45°, and 90°), three impact speeds (25, 35, and 45 kph), and four frontal crash type configurations. All four seatback angles were used with 0° seat rotation, whereas 13° seatback angle was used with the remaining seat rotation configurations because of cabin fit considerations. Injury risks were estimated for the head, neck, shoulder, thorax, pelvis, and lower extremities for both occupants for each simulation (n=588). RESULTS:Statistically significant differences between all the groups within each independent variable category were observed based on the analysis of variance. HIC-based head injury risk and chest injury risk decreased and femur force for the driver and tibia force for the passenger increased with an increase in seatback angles. The head injury risk increased with seat rotation. All the injury risks increased with an increase in impact speed. The driver airbag was able to safeguard the driver from head injuries for all seat rotations except at 90° of seat rotation. CONCLUSION:This is the first vehicle modeling study that collectively looked at the effects of seatback angle, seat rotation, and impact speed along with the interaction of occupants on the risk of injury in frontal crashes. The rear passenger experienced higher seatbelt loads than the driver. More reclined seats decreased head and chest injury risk, but increased driver femur injury risk and rear passenger tibia injury risk. Results underscore the necessity for additional anti-submarining mechanisms and driver airbag designs adapted for the anticipated occupant positions.

This study investigates the effect of PID controller gains, reaction time, and initial muscle activation values on active human model behavior while comparing three different control strategies. The controller gains and reaction delays were optimized using published experimental data focused on the upper extremity. The data describes the reaction of five male subjects in four tests based on two muscle states (relaxed and tensed) and two states of awareness (open and closed eye). The study used a finite element model of the left arm isolated from the Global Human Body Models Consortium (GHBMC) average male simplified occupant model for simulating biomechanical simulations. Major skeletal muscles of the arm were modeled as 1D beam elements and assigned a Hill-type muscle material. Angular position control, muscle length control, and a combination of both were used as a control strategy. The optimization process was limited to 4 variables; three Proportional-Integral-Derivative (PID) controller gains and one reaction delay time. The study assumed the relaxed and tensed condition require distinct sets of controller gains and initial activation and that the closed-eye simulations can be achieved by increasing the reaction delay parameter. A post-hoc linear combination of angle and muscle length control was used to arrive at the final combined control strategy. The premise was supported by variation in the controller gains depending on muscle state and an increase in reaction delay based on awareness. The CORA scores for open-eye relaxed, closed-eye relaxed, open-eye tensed, and closed-eye tensed was 0.95, 0.90, 0.95, and 0.77, respectively using the combined control strategy.

Objective Finite element (FE) reconstructions of motor vehicle crashes using human body models are effective tools for developing a better understanding of occupant kinematics and injuries in real-world lateral crash conditions, but current near-side reconstruction methods are limited by the paucity of full-scale FE vehicle models. The objective of this study was to validate a generic vehicle model equipped with left-side airbags and intrusion capability by simulating a series of near-side crash tests for a range of vehicles and assessing model accuracy using objective evaluation methods. Methods Moving deformable barrier crash tests were reconstructed for five common vehicle classifications (compact passenger, mid-size passenger, sport utility vehicle, pickup truck, and van) using an updated version of a previously developed simplified vehicle model. Unknown vehicle and intrusion properties (pretensioner force, seatback airbag pressure, curtain airbag pressure, door panel stiffness, ratio of dynamic-to-static intrusion, intrusion velocity, and intrusion scaling factor) were estimated by parameterizing them across 224 simulations per crash test using a Latin hypercube design of experiments. Model accuracy was assessed for 13 anthropomorphic test device signals using the Correlation and Analysis (CORA) objective rating method and injury metric comparisons. Results Maximum ratings of 0.69, 0.67, 0.52, 0.52, and 0.62 were achieved for the compact passenger, midsize passenger, sport utility vehicle, pickup truck, and van classifications, respectively. On average, the abdomen displayed the most accurate behavior (0.51 ± 0.12), followed by the thorax (0.50 ± 0.10) and head (0.50 ± 0.07). The pelvis displayed the least accurate behavior (0.46 ± 0.18) of any region. Reconstructions overpraedicted injury metrics in all cases. Conclusions All vehicles achieved “fair” biofidelity ratings and the compact passenger and midsize passenger vehicles achieved “good” biofidelity ratings, validating them for kinematic evaluations with vehicle-to-vehicle nearside crash reconstructions. Regression models were developed for injuries and CORA ratings and can be used to optimize vehicle parameters in future studies.

Muscle atrophy occurs with extended exposure to microgravity. This study quantified the overall muscle size, lean muscle area and fat infiltration changes pre- to post-flight that occur in the thoracic and lumbar spine with long-duration spaceflight. Pre- and post-flight magnetic resonance imaging (MRI) scans were obtained from 9 crewmembers on long-duration (≥6 months) International Space Station (ISS) missions. Muscle size was measured by the cross-sectional area (CSA) and lean muscle tissue by the functional cross-sectional area (FCSA). Muscle-fat infiltration (MFI) was measured by the mean pixel intensities of the MRI in fat and water phases. A mixed model with random subject effect was used to analyze pre- to post-flight changes. Significant decreases were seen in the quadratus lumborum muscle size (-1.8±0.6% per month, p=0.002) and lean muscle tissue content in the paraspinal muscles (-0.7±0.2% per month, p≤0.001). Fat infiltration increased significantly in the transversospinalis (+4.1±1.0% per month, p≤0.01) muscle. Treadmill exercise had a tendency to reduce fat content in the paraspinal and quadratus lumborum muscles, while counteracting muscle build-up only in the paraspinal muscles. Cycle ergometer exercise suggested benefits for the psoas muscle. Resistance training appeared to benefit lean muscle mass of most thoracolumbar muscles. Our findings highlight the need for countermeasures to prevent muscle atrophy and detrimental effects in muscle composition during long-duration spaceflight.

Extravehicular activities will play a crucial role in lunar exploration on upcoming Artemis missions and may involve astronauts operating a lunar terrain vehicle (LTV) in a standing posture. This study assessed kinematic response and injury risks using an active muscle human body model (HBM) restrained in an upright posture on the LTV by simulating dynamic acceleration pulses related to lunar surface irregularities. Linear accelerations and rotational displacements of 5 lunar obstacles (3 craters; 2 rocks) over 5 slope inclinations were applied across 25 simulations. All body injury metrics were below NASA’s injury tolerance limits, but compressive forces were highest in the lumbar (250–550N lumbar, tolerance: 5300N) and lower extremity (190–700N tibia, tolerance: 1350N) regions. There was a strong association between the magnitudes of body injury metrics and LTV resultant linear acceleration (ρ = 0.70–0.81). There was substantial upper body motion, with maximum forward excursion reaching 375 mm for the head and 260 mm for the chest. Our findings suggest driving a lunar rover in an upright posture for these scenarios is a low severity impact presenting low body injury risks. Injury metrics increased along the load path, from the lower body (highest metrics) to the upper body (lowest metrics). While upper body injury metrics were low, increased body motion could potentially pose a risk of injury from flail and occupant interaction with the surrounding vehicle, suit, and restraint hardware.

This study compared two morphing techniques (and their serial combination) to create subject-specific finite element models of 15 astronaut vertebrae. Surface deviations of the morphed models were compared against subject geometries extracted from medical images. The optimal morphing process yielded models with minimal difference in root-mean-square (RMS) deviation (C3, 0.52 +/- 0.14 mm; T3, 0.34 +/- 0.04 mm; L1, 0.59 +/- 0.16 mm) of the subject's vertebral geometry. <1% of model elements failed quality checks and compression simulations ran to completion. This research lays the foundation for the development of subject-specific finite element models to quantify musculoskeletal changes and injury risk from spaceflight.

The objective of the current study was to perform a preliminary validation of the Global Human Body Models Consortium (GHBMC) average male occupant models, simplified (M50-OS) and detailed (M50-O) and the 70YO aged model in Far-side impacts and compare the head kinematics against the PMHS responses published by Petit et al. (2019). The buck used to simulate the far-side impacts comprised a seat, headrest, center console plate, leg support plate, and footrest plate with rigid material properties. The three occupant models were gravity settled onto the rigid seat and belted with a 3-point seatbelt. Positioning details of the PMHS were followed in the model setup process. A deceleration pulse with ΔV of 8 m/s was applied. The far-side crash simulations were performed with and without the addition of a plexiglass cover around the setup similar to the experimental setup. The head kinematics were extracted from the models for comparison against the PMHS data. Peak head displacements in Y and Z axes from the three models were compared to the PMHS data in addition to the head rotation along X axes. The peak head displacement values for the M50-OS, M50-O, and M50-O 70YO aged models are 594.10 mm, 568.44 mm, and 567.90 mm along Y and 325.21 mm, 402.66 mm, and 375.92 mm respectively along Z when the plexiglass cover is included in the test. The peak head rotation values for the M50-OS, M50-O, and M50-O 70YO aged models are 95.64°, 122.15°, and 129.08° respectively when the plexiglass cover is included in the test. The three occupant models capture the general trend of the PMHS data. The detailed occupant models have higher head rotation compared to the simplified model because of the deformable structure of the spine and intervertebral discs modeled. These three occupant models can be used for further parametric studies in this condition to study the influence of restraint parameters.

Spinal injuries are a concern for automotive applications, requiring large parametric studies to understand spinal injury mechanisms under complex loading conditions. Finite element computational human body models (e.g. Global Human Body Models Consortium (GHBMC) models) can be used to identify spinal injury mechanisms. However, the existing GHBMC detailed models (with high computational time) or GHBMC simplified models (lacking vertebral fracture prediction capabilities) are not ideal for studying spinal injury mechanisms in large parametric studies. To overcome these limitations, a modular 50th percentile male simplified occupant model combining advantages of both the simplified and detailed models, M50-OS + DeformSpine, was developed by incorporating the deformable spine and 3D neck musculature from the detailed GHBMC model M50-O (v6.0) into the simplified GHBMC model M50-OS (v2.3). This new modular model was validated against post-mortem human subject test data in four rigid hub impactor tests and two frontal impact sled tests. The M50-OS + DeformSpine model showed good agreement with experimental test data with an average CORrelation and Analysis (CORA) score of 0.82 for the hub impact tests and 0.75 for the sled impact tests. CORA scores were statistically similar overall between the M50-OS + DeformSpine (0.79 ± 0.11), M50-OS (0.79 ± 0.11), and M50-O (0.82 ± 0.11) models (p > 0.05). This new model is computationally 6 times faster than the detailed M50-O model, with added spinal injury prediction capabilities over the simplified M50-OS model.

The objective of this study was to assess the ability of finite element human body models (FEHBMs) and Anthropometric Test Device (ATD) models to estimate occupant injury risk by comparing it with field-based injury risk in far-side impacts. The study used the Global Human Body Models Consortium midsize male (M50-OS+B) and small female (F05-OS+B) simplified occupant models with a modular detailed brain, and the ES-2Re and SID-IIs ATD models in the simulated far-side crashes. A design of experiments (DOE) with a total of 252 simulations was conducted by varying lateral ΔV (10-50kph; 5kph increments), the principal direction of force (PDOF 50°, 60°, 65°, 70°, 75°, 80°, 90°), and occupant models. Models were gravity-settled and belted into a simplified vehicle model (SVM) modified for far-side impact simulations. Acceleration pulses and vehicle intrusion profiles used for the DOE were generated by impacting a 2012 Camry vehicle model with a mobile deformable barrier model across the 7 PDOFs and 9 lateral ΔV's in the DOE for a total of 63 additional simulations. Injury risks were estimated for the head, chest, lower extremity, pelvis (AIS 2+; AIS 3+), and abdomen (AIS 3+) using logistic regression models. Combined AIS 3+ injury risk for each occupant was calculated using AIS 3+ injury risk estimations for the head, chest, abdomen, and lower extremities. The injury risk calculated using computational models was compared with field-based injury risk derived from NASS-CDS by calculating their correlation coefficient. The field-based injury risk was calculated using risk curves that were created based on real-world crash data in a previous study (Hostetler et al., 2020). Occupant age (40 years), seatbelt use (belted occupant), collision deformation classification, lateral ΔV, and PDOF of the crash event were used in these curves to estimate field injury risk. Large differences in the kinematics were observed between HBM and ATD models. ATD models tended to overestimate risk in almost every case whereas HBMs yielded better risk estimates overall. Chest and lower extremity risks were the least correlated with field injury risk estimates. The overall risk of AIS 3+ injury risk was the strongest comparison to the field data-based risk curves. The HBMs were still not able to capture all the variance but future studies can be carried out that are focused on investigating their shortfalls and improving them to estimate injury risk closer to field injury risk in far-side crashes.

Objective The objectives of this study were to evaluate computationally efficient small female (54.1 kg, 149.9 cm) and midsize male (78.4 kg, 174.9 cm) models with active muscles using volunteer sled test data in a frontal-oblique loading direction and check their response in crash mitigating maneuvers using field test data. Methods The Global Human Body Models Consortium small female (F05-OS+Active) and midsize male (M50-OS+Active) simplified occupant models with active musculature were used in this study. The data from a total of 48 previously published sled test experiments were used to simulate a total of 16 simulations. The experimental study recorded occupant responses of six small female and six midsize male volunteers (n = 12 total) in two muscle conditions (relaxed and braced) at two acceleration pulses representing pre-crash braking (1.0 g) and a low-speed impact (2.5 g). Each model's kinematics and reaction forces were compared with experimental data. Along with sled test simulations, both of these models were simulated in abrupt braking, lane change, and turn and brake events using literature data. A total of 36 field test simulations were carried out. A CORA analysis was carried out using reaction load and displacement time-history data for sled test simulations and head CG displacement time-history was used for field test simulations. Results The occupant peak forward and lateral excursion results of both active models reasonably matched the volunteer data in the low-speed sled test simulations for both pulse severities. The differences between the active and control models were statistically significant (p-value < 0.05) based on the results of Wilcoxon signed-rank tests using peak forward and lateral excursion data. The average CORA scores calculated for the sled test (sled test: M50-OS+Active= 0.543, male control= 0.471, F05-OS+Active= 0.621, female control= 0.505) and field test (M50-OS+Active= 0.836, male control= 0.466, F05-OS+Active= 0.832, female control= 0.787) simulations were higher for active models than control. Conclusions The responses of the F05-OS+Active and M50-OS+Active models were better than control models based on overall CORA scores calculated using both sled and field tests. The results highlight their ability to predict occupant kinematics in crash-mitigating maneuvers and low-speed impacts in the frontal, lateral and frontal-oblique directions.

Background: Rib fracture(s) occurs in 85% of blunt chest trauma cases. Increasing evidence supports that surgical intervention, particularly for multiple fractures, may improve outcomes. Thoracic morphology diversity across ages and sexes is important to consider in the design and use of surgical intervention devices in chest trauma. However, research on non-average thoracic morphology is lacking.Methods: The rib cage was segmented from patient computed tomography (CT) scans to create 3D point clouds. These point clouds were uniformly oriented and chest height, width, and depth were measured. Size categorization was determined by grouping each dimension into small, medium, and large tertiles. From small and large size combinations, subgroups were extracted to develop thoracic 3D models of the rib cage and surrounding soft tissue. Results: The study population included 141 subjects (48% male) ranging from age 10-80 with-20 subjects/age decade. Mean chest volume increased with age by 26% from the age groups 10-20 to 60-70, with 11% of this increase occurring between the youngest groups of 10-20 and 20-30. Across all ages, chest dimensions were-10% smaller in females and chest volume was highly variable (SD: & PLUSMN;3936.5 cm3). Representative thoracic models of four males (ages 16, 24, 44, 48) and three females (ages 19, 50, 53) were developed to characterize morphology associated with combinations of small and large chest dimensions.Conclusions: The seven models developed cover a broad range of non-average thoracic morphologies and can serve as a basis for informing device design, surgical planning, and injury risk assessments.

Active muscles play an important role in postural stabilization, and muscle-induced joint stiffening can alter the kinematic response of the human body, particularly that of the lower extremities, under dynamic loading conditions. There are few full-body human body finite element models with active muscles in a standing posture. Thus, the objective of this study was to develop and validate the M50-PS+Active model, an average-male simplified human body model in a standing posture with active musculature. The M50-PS+Active model was developed by incorporating 116 skeletal muscles, as one-dimensional beam elements with a Hill-type material model and closed-loop Proportional Integral Derivative (PID) controller muscle activation strategy, into the Global Human Body Models Consortium (GHBMC) simplified pedestrian model M50-PS. The M50-PS+Active model was first validated in a gravity standing test, showing the effectiveness of the active muscles in maintaining a standing posture under gravitational loading. The knee kinematics of the model were compared against volunteer kinematics in unsuited and suited step-down tests from NASA’s active response gravity offload system (ARGOS) laboratory. The M50-PS+Active model showed good biofidelity with volunteer kinematics with an overall CORA score of 0.80, as compared to 0.64 (fair) in the passive M50-PS model. The M50-PS+Active model will serve as a useful tool to study the biomechanics of the human body in vehicle–pedestrian accidents, public transportation braking, and space missions piloted in a standing posture.

As obesity rates climb, it is important to study its effects on motor vehicle safety due to differences in restraint interaction and biomechanics. Previous studies have shown that an abdominal seatbelt sign (referred hereafter as seatbelt sign) sustained from motor vehicle crashes (MVCs) is associated with abdominal trauma when located above the anterior superior iliac spine (ASIS). This study investigates whether placement of the lap belt causing a seatbelt sign is associated with abdominal organ injury in occupants with increased body mass index (BMI). We hypothesized that higher BMI would be associated with a higher incidence of superior placement of the lap belt to the ASIS level, and a higher incidence of abdominal organ injury.A retrospective data analysis was performed using 230 cases that met inclusion criteria (belted occupant in a frontal collision that sustained at least one abdominal injury) from the Crash Injury Research and Engineering Network (CIREN) database. Computed tomography (CT) scans were rendered to visualize fat stranding to determine the presence of a seatbelt sign. 146 positive seatbelt signs were visualized. ASIS level was measured by adjusting the transverse slice of the CT to the visualized ASIS level, which was used to determine seatbelt sign location as superior, on, or inferior to the ASIS.Obese occupants had a significantly higher incidence of superior belt placement (52%) vs on-ASIS placement (24%) compared to their normal (27% vs 67%) BMI counterparts (p < 0.001). Notable trends included obese occupants with superior placement having less abdominal organ injury incidence than those with on-ASIS belt placement (42% superior placement vs 55% on-ASIS). In non-obese occupants, there was a higher incidence of abdominal organ injury with superior lap belt placement compared to on-ASIS placement counterparts (Normal BMI: 62% vs 41%, Overweight: 57% vs 43%).In CIREN occupants with abdominal injury, those with obesity are more prone to positioning the lap belt superior to the ASIS, though the impact on abdominal injury incidence remains a key point for continued exploration into how occupant BMI affects crash safety and belt design.

OBJECTIVE:The objective of this study was to implement active muscles in a computationally efficient small female finite element model (54.1 kg, 149.9 cm) suitable for predicting occupant response during precrash braking and low-speed frontal sled tests. We further calibrate and compare its results against an average male model (78.4 kg, 174.9 cm) using the same developmental approach. METHODS:The active female model (F05-OS + Active) was developed by adding active skeletal muscle elements (n = 232) to the Global Human Body Models Consortium (GHBMC) 5th percentile female simplified occupant model (F05-OS v2.3). The muscle properties and physiological cross-sectional area (PCSA) for each muscle were taken from the M50-OS + Active v2.3 model but PCSAs were mass scaled to a 5th percentile female. A total of 8 simulations were conducted; 2 acceleration pulses (1.0 g and 2.5 g), 2 models (F05-OS + Active and M50-OS + Active), and 2 muscle states (activation and control; e.g., no activation). Each model's kinematics and reaction forces were compared with experimental data. Occupant responses of 6 5th percentile female and 6 50th percentile male volunteers (n = 12 total) were used. The data depict occupant response in precrash braking and low-speed frontal sled tests in a rigid test buck. All procedures were reviewed and approved by the Virginia Tech institutional review board. Each volunteer was in a relaxed state before the applied acceleration. RESULTS:The occupant peak forward excursion results of both active models reasonably match the volunteer data for both pulse severities. The differences between active and control models were found to be significant by Wilcoxon signed-rank test (p < .05). The reaction loads of the active and control models lie within the experimental corridors. CONCLUSIONS:To the authors' knowledge, this study is the first to concurrently calibrate and compare equivalently developed computational models of females and males in precrash and low-speed impacts. The modeling approach is capable of capturing the varied kinematics observed in the relaxed condition, which may be an important factor in studies focused on the effects of low-g vehicle dynamics on the occupant position. Finally, the computationally efficient modeling approach is imperative given the long duration (>500 ms) of the events simulated.