Modular incorporation of deformable spine and 3D neck musculature into a simplified human body finite element model

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.

A simulation-based study for optimizing proportional-integral-derivative controller gains for different control strategies of an active upper extremity model using experimental data

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.

Preliminary validation of the GHBMC average male occupant models and 70YO aged model in far-side impact

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.

Assessment of finite element human body and ATD models in estimating injury risk in far-side impacts using field-based injury risk

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.

Comparison of morphing techniques to develop subject-specific finite element models of vertebrae

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.

Response of small female and midsize male models with active musculature in pre-crash maneuvers and low-speed impacts

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.

COMPARTMENTAL FEMUR CORTICAL THICKNESS IN OLDER ADULTS DIFFERS BY DEMOGRAPHICS AND PHYSICAL FUNCTION

Previous studies have examined the relationship between cortical bone properties and fracture risk in older populations, but they have yet to examine how these properties change within the femur. Most hip fractures are classified by their location: femoral neck, intertrochanteric, or subtrochanteric fractures. Since cortical thickness can vary throughout the femur, a quantitative method of examining thickness by region was developed using a cortical mapping approach applied to computed tomography (CT) scans. Subject-specific finite element (FE) models of proximal femurs were created from baseline CT scans of 107 older adults (ages 60 – 85; 70% White; 72% Female) with obesity as classified by BMI (33.8 ± 4 kg/m2). An existing FE model was morphed to the segmented geometry of each subject’s proximal femur. A nearest neighbor search assigned cortical thickness values to the nearest finite element model node. Cortical thickness was grouped into four femoral compartments: femoral head, femoral neck, intertrochanteric and subtrochanteric regions. Pairwise paired t-tests indicated that cortical thickness differed between femoral compartments (p &lt; 0.05). Multivariate regression models showed greater cortical thicknesses in femoral head, neck, and intertrochanteric regions in African Americans compared to Whites (p &lt; 0.05). Additionally, these models suggest an association between cortical thickness and physical function assessments, such as the timed up-and-go test and leg muscle strength test. Since cortical thickness is not constant throughout the femur, future studies can use the framework developed here to assess each compartment individually and investigate the relationships between cortical thickness, demographics, and functional assessments.

Implementation and calibration of active small female and average male human body models using low-speed frontal sled tests

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.

Body mass index influence on lap belt position and abdominal injury in frontal motor vehicle crashes

OBJECTIVE

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.

METHODS

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.

RESULTS

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%).

CONCLUSIONS

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.

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.

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.

Validation of a simplified human body model in relaxed and braced conditions in low-speed frontal sled tests

Objective: The goal of this study was to implement active musculature into the Global Human Body Models Consortium (GHBMC) average male simplified occupant model (M50-OS v2) and validate its performance in low-speed frontal crash scenarios.Methods: Volunteer and postmortem human subjects (PMHS) data from low-speed frontal sled tests by Beeman et al., including 2.5 and 5.0 g acceleration pulses, were used to simulate events in LS-DYNA. All muscles were modeled as 1D beam elements and assigned a Hill-type muscle material. From the output of proportional-integral-derivative (PID) controllers, the activation level for each muscle was calculated using a sigmoid function, representing the firing rate of motor neurons. The PID controller attempts to preserve the initial posture of the model. Percentage muscle contribution for all skeletal muscles was precalculated using the M50-OS with active muscles (M50-OS + Active). The M50-OS + Active employs varying levels of neural delays to represent volunteer relaxed and braced conditions, taken from literature. Braced condition experiments were simulated using elevated joint angle set values for the PID controller. The M50-OS + Active model was used to simulate 2 muscle conditions (relaxed and braced) at 2 pulse severities (2.5 and 5.0 g). A control set of simulations was conducted to compare the effect of adding active muscle. Ten whole-body simulations were conducted.Results: The results from volunteer simulations showed a strong dependence of reaction loads and kinematics on muscle activation. Compared to baseline, M50-OS, at 5.0 g acceleration, 33.3% and 7.6% decreases were observed in the overall head kinematics of the M50-OS + Active for the braced and relaxed conditions, respectively. Regarding the anterior direction, similar reductions in overall kinematics were observed for both volunteer test conditions. In comparison to control simulations in which no active muscle was implemented, objective evaluation scores increased markedly at both speeds for the braced condition. Little to no gain was found in the relaxed condition.Conclusions: The results justify the need for use of an active human body model for predicting low-speed frontal kinematics, particularly in the braced condition. Head kinematics were reduced when using active modeling for all simulations (braced and relaxed).