Human Body Finite Element Model Research Articles

Simulating Pelvis Kinematics from Belt and Seat Loading in Frontal Car Crash Scenarios: Important Boundary Conditions that Influence the Outcome.

The risk of submarining during automotive crashes, defined by the lap belt sliding off the pelvis to load the abdomen, is predicted to increase in future autonomous vehicles as greater variation in seating position is enabled. Biofidelic tools are required to efficiently design and evaluate new and/or improved safety systems. This study aims to evaluate the pelvis response sensitivity to variations in boundary conditions that directly influence the pelvis loads, deemed important for the submarining outcome, to facilitate a more precise comparison between finite element human body models (FE-HBMs) and post-mortem human subjects (PMHSs). A parameter study, using a one-variable-at-a-time analysis (low/high) of belt friction, seat friction, seat stiffness, and (on/off) for added belt bending stiffness, was performed using a state-of-the-art FE-HBM in four different test scenarios; one stationary, two sleds with upright occupant posture, and one sled with reclined occupant posture. In the stationary scenario, both belt friction and belt bending stiffness influenced the belt folding behavior, which consequently affected the belt-to-pelvis angle at submarining. In the sled scenarios, only seat friction was found to influence the pelvis kinematics and submarining outcome, with the most biofidelic response resulting from both the low (0.2) and high (0.5) friction coefficient depending on the scenario. To reduce uncertainty in boundary conditions affecting the external pelvis loads and increase confidence in FE-HBM to PMHS comparisons, it is recommended that future experiments evaluate the PMHS to seat friction coefficient and that new belt modeling methods that accurately capture belt folding when interacting with soft tissues are developed.

Effects of loading processes on contact forces when simulating static seating with a finite element human body model

Seat interface forces, particularly shear forces, play an essential role in predicting the risk of pressure ulcers and seating discomfort. When a finite element human body model (HBM) is used for static seating simulation, the most common loading method is to put the model in a position close to the desired final posture and then ‘drop’ it from just above the seat by applying the gravity (DROP). This does not represent how people sit in a seat. In addition, high coefficients of friction (COF) are often used to prevent sliding, which may lead to unrealistically high tangential forces. This study aims to investigate the effects of the loading process and the COF on seating simulations with a HBM. We propose a new loading approach called ‘drop and rotate’ (D&R) to better mimic people sitting on a seat. With the trunk more flexed than the desired posture, the model is dropped to establish the contact between the buttocks and thighs, and the seat pan first, and then between the back and the backrest by rotating the hip. Simulations were performed using a recently developed and validated adult male model in two different seat configurations. Results show that the proposed D&R method was less sensitive to COF and gave a better prediction of contact forces, especially on the seat pan. However, its computational time is higher than the DROP method. The study highlights the importance of the loading process when simulating static seating.

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 hierarchicallyvalidated 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.

Influence of muscle activation on lumbar injury under a specific +Gz load

PurposeThe present study aimed to analyze the influence of muscle activation on lumbar injury under a specific +Gz load. MethodsA hybrid finite element human body model with detailed lumbar anatomy and lumbar muscle activation capabilities was developed. Using the specific +Gz loading acceleration as input, the kinematic and biomechanical responses of the occupant's lower back were studied for both activated and deactivated states of the lumbar muscles. ResultsThe results indicated that activating the major lumbar muscles enhanced the stability of the occupant's torso, which delayed the contact between the occupant's head and the headrest. Lumbar muscle activation led to higher strain and stress output in the lumbar spine under +Gz load, such as the maximum Von Mises stress of the vertebrae and intervertebral discs increased by 177.9% and 161.8%, respectively, and the damage response index increased by 84.5%. ConclusionIn both simulations, the occupant's risk of lumbar injury does not exceed 10% probability. Therefore, the activation of muscles could provide good protection for maintaining the lumbar spine and reduce the effect of acceleration in vehicle travel direction.

A First Step Toward a Family of Morphed Human Body Models Enabling Prediction of Population Injury Outcomes.

The injury risk in a vehicle crash can depend on occupant specific factors. Virtual crash testing using finite element human body models (HBMs) to represent occupant variability can enable the development of vehicles with improved safety for all occupants. In this study, it was investigated how many HBMs of different sizes that are needed to represent a population crash outcome through a metamodel. Rib fracture risk was used as an example occupant injury outcome. Morphed HBMs representing variability in sex, height, and weight within defined population ranges were used to calculate population variability in rib fracture risk in a frontal and a side crash. Two regression methods, regularized linear regression with second-order terms and Gaussian process regression (GPR), were used to metamodel rib fracture risk due to occupant variability. By studying metamodel predictive performance as a function of training data, it was found that constructing GPR metamodels using 25 individuals of each sex appears sufficient to model the population rib fracture risk outcome in a general crash scenario. Further, by utilizing the known outcomes in the two crashes, an optimization method selected individuals representative for population outcomes across both crash scenarios. The optimization results showed that 5-7 individuals of each sex were sufficient to create predictive GPR metamodels. The optimization method can be extended for more crashes and vehicles, which can be used to identify a family of HBMs that are generally representative of population injury outcomes in future work.

Prediction of pedestrian injuries in motorcycle-pedestrian crashes using THUMS FE-HBM

This study focuses on the high fatality rates associated with motorcycles as a mode of transport in India, surpassing trucks and cars. Over the last decade, motorcycle-related fatalities have seen a staggering increase of 232%. The Finite Element-Human Body Models (FE-HBM) have been validated for occupants and pedestrians in car crashes. However, the performance against motorcycle impact is lacking in the literature. The primary objective of this research is to evaluate the THUMS model for injury prediction in motorcycle-pedestrian impact scenarios using a finite element motorcycle model of a widely used two wheeler in India. The motorcycle model is initially validated against a rigid wall, after which it is utilised to predict injuries in real-life motorcycle-pedestrian crash scenarios. Through multi-body simulations, crucial pre-crash parameters such as pedestrian orientation, offset and speed are estimated for five actual motorcycle-pedestrian crashes. Subsequently, finite element simulations are conducted to validate the model’s accuracy in predicting pedestrian injuries. The study closely predicts the occurrence and location of fractures in long bones using strain-based criteria in four out of five cases.

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.

Virtual Assessment of a Representative Torso Airbag under the Fall from Height Impact Conditions

A fall from height is the main cause of serious injuries and fatalities in occupational and work-related accidents, especially construction. Falls from scaffolds, ladders, or roofs are very frequent accident scenarios. Especially for those falls from a height of 1 m to 6 m, the use of wearable smart airbags has been proposed to mitigate possible torso injuries. In this study, a virtual assessment of such an inflatable protector was conducted using numerical simulations and finite element human body models in order to determine its impact-protection performance under realistic impact conditions and identify its possible limitations. The findings obtained from the simulation study showed a significant protective effect provided by the airbag, mitigating a multiple rib fracture scenario and reducing the risk of internal organ injuries for those falling from four meters of height or less. The use case analyzed in this research demonstrates the suitability of using a virtual environment not only to evaluate current protectors but also to develop new protector devices, which could improve occupational safety.

Investigations on tram-pedestrian impacts by application of virtual testing with human body models

BackgroundIn Austria around 100 trams are involved in accidents with pedestrians every year. Since the service lives of trams are very high, the probabilities are also high that each tram on the network will be involved in an accident of this kind at least once, highlighting the need of protective designs of tram fronts. However, due to lack of studies in this area, this is still a challenging task.PurposeThe aim of this study is to show the applicability and the usability of virtual testing involving HBMs in tram front design studies to improve passive safety in general.MethodologyIn this study, the impact of pedestrians with a tram was investigated using a generic tram front model in a basic version and a conceptually improved version, respectively, and detailed finite element human body models (HBM). To consider gender-differences and to avoid designs that unintentionally favour only particular groups of the population, the study simulations were carried out with a male and a female 50th percentile finite element human body model (VIVA+). The risk for head, chest, femur and tibia injuries were analysed as the simulation result, since these body areas were identified based on field data to be most relevant in accidents involving pedestrians and trams. Collision scenarios are evaluated for a wide parameter variation in impact location and speed, respectively.FindingsThe results show a reduction in head injury risk for both the female and the male HBM at different speeds and impact locations for impact with the enhanced version of the tram front. Depending on the gender of the HBM, the considered improvement shows different effects for each body region, with a greater reduction in the likelihood of head injury for the female model, and a greater reduction in the likelihood of thoracic injury for the male model. These differences are due to the considered anthropomorphic variations. A reduction for the risk of femur injuries can be achieved in all cases using the modified tram front. The study showcases the application of detailed human body models for tram pedestrian impact analyses in the context of pedestrian safety and in particular for tram front improvements. It was shown that even a minor modification of the tram front with softer front skirt attachments leads to remarkable benefits with respect to injury criteria in all investigated crash scenarios. The presented research goes beyond current technical recommendations and shows the benefit of virtual testing including HBMs and considering a wide variety of impact speeds, anthropometries and injury assessments, respectively.

A comparative analysis of dimensionality reduction surrogate modeling techniques for full human body finite element impact simulations

Fast-running surrogate computational models (simpler computational models) have been successfully used to replace time-intensive finite element models. However, it is unclear how well they perform in accurately and efficiently replicating complex, full human body finite element models. Here we survey several surrogate modeling techniques and assess their accuracy in predicting full strain fields of tissues of interest during a highly dynamic behind armor blunt trauma impact to the liver. We found that coupling dimensionality reduction on the high-dimensional output space (principal component analysis or autoencoders) with machine learning techniques (Gaussian Process Regression or multi-output neural networks) provides a framework capable of accurately and efficiently replacing complex full human body models. It was found that these surrogate models can successfully predict the strain fields (<10% average strain error) of select tissues during a nonlinear impact event but careful consideration should be given to element parsing and modeling technique.

Investigation of Potential Injury Patterns and Occupant Kinematicsin Frontal Impact with PMHS in Reclined Postures.

The reality of the autonomous vehicle in a near future is growing and is expected to induce significant change inthe occupant posture with respect to a standard driving posture. The delegated driving would allow sleeping and/or resting in a seatwith a reclined posture. However, the data in the literature are rare on the body kinematics, human tolerance, and injury types insuch reclined postures. The current study aims at increasing the knowledge in the domain and providing useful data to assess therelevance of the standard injury assessment tools such as anthropomorphic test devices or finite element human body models. For that purpose, a test series of three male Post-Mortem Human Subjects (PMHS) were performed in frontal impact at a 13.4 m/sdelta V. The backseat inclination was 58 degrees with respect to the vertical axis. The semi-rigid seat developed by Uriot et al.(2015) was used with a stiffer seat ramp. The restraint was composed of a lap belt equipped with two 3.5 kN load limiters, and ofa shoulder belt equipped of a 4 kN load limiter on the upper anchorage placed in the vicinity of the shoulder. The belts, the semi-rigid seat, and the footrest were equipped with force sensors. The rotations of the seat pan and of the seat ramp were also measured. The PMHS were instrumented with multi-axis accelerometers and Y angular velocity sensors attached to the head, thorax (T1 andT12 vertebrae), and sacrum. Strain gauges were glued onto the anterior face of the L1 to L5 lumbar vertebrae and onto the anteriorface of the iliac wings. To estimate the pelvis kinematics, a rigid support equipped with targets was fixed onto the femur shaft. Prior to test, X-ray imagery was performed to exhibit the initial curvature of the lumbar spine. After the tests, an in-depth necropsywas done, with a specific attention to the lumbar spine. In the chosen test conditions, no lap-belt submarining was observed for the three PMHS. One PMHS sustained an AIS2 pelvic ringfracture and another one sustained an AIS4 injury with complete separation of the left and right sacroiliac joints. Lumbar discruptures and vertebral fractures were observed for the three PMHS (AIS 2 and AIS3 coding). The number of separated rib fractureswere very different from one PMHS to another (0, 6 and 33). Response corridors for the external forces and kinematics were builtand are presented in the paper. The results are discussed by comparing with existing data for which the backseat was in standardposture.

Personalization of human body models and beyond via image registration.

Finite element human body models (HBMs) are becoming increasingly important numerical tools for traffic safety. Developing a validated and reliable HBM from the start requires integrated efforts and continues to be a challenging task. Mesh morphing is an efficient technique to generate personalized HBMs accounting for individual anatomy once a baseline model has been developed. This study presents a new image registration-based mesh morphing method to generate personalized HBMs. The method is demonstrated by morphing four baseline HBMs (SAFER, THUMS, and VIVA+ in both seated and standing postures) into ten subjects with varying heights, body mass indices (BMIs), and sex. The resulting personalized HBMs show comparable element quality to the baseline models. This method enables the comparison of HBMs by morphing them into the same subject, eliminating geometric differences. The method also shows superior geometry correction capabilities, which facilitates converting a seated HBM to a standing one, combined with additional positioning tools. Furthermore, this method can be extended to personalize other models, and the feasibility of morphing vehicle models has been illustrated. In conclusion, this new image registration-based mesh morphing method allows rapid and robust personalization of HBMs, facilitating personalized simulations.

Can we reposition finite element human body model like dummies?

Rapidly repositioning finite element human body models (FE-HBMs) with high biofidelity is an important but notorious problem in vehicle safety and injury biomechanics. We propose to reposition the FE-HBM in a dummy-like manner, i.e., through pose parameters prescribing joint configurations. Skeletons are reconfigured along the trajectories inferred from model-specific bone geometries. We leverage differential geometry to steer equidistant moves along the congruent articulated bone surfaces. Soft tissues are subsequently adapted to reconfigured skeletons through a series of operations. The morph-contact algorithm allows the joint capsule to slide and wrap around the repositioned skeletons. Nodes on the deformed capsule are redistributed following an optimization-based approach to enhance element regularity. The soft tissues are transformed accordingly via thin plate spline. The proposed toolbox can reposition the Total Human Body Model for Safety (THUMS) in a few minutes on a whole-body level. The repositioned models are simulation-ready, with mesh quality maintained on a comparable level to the baseline. Simulations of car-to-pedestrian impact with repositioned models exhibiting active collision-avoidance maneuvers are demonstrated to illustrate the efficacy of our method. This study offers an intuitive, effective, and efficient way to reposition FE-HBMs. It benefits all posture-sensitive works, e.g., out-of-position occupant safety and adaptive pedestrian protection. Pose parameters, as an intermediate representation, join our method with recently prosperous perception and reconstruction techniques of the human body. In the future, it is promising to build a high-fidelity digital twin of real-world accidents using the proposed method and investigate human biomechanics therein, which is of profound significance in reshaping transportation safety studies in the future.

Analysis of lumbar spine injury with different back inclinations under whole-body vibration: A finite element study based on whole human body models

Whole-body vibration was found to be a cause of low back pain. Different back inclinations might change the forces on the lumbar spine, resulting in different responses to the vibration. The aim of this study was to investigate the effects of back inclinations on the lumbar spine from the perspective of analysing the internal loads and deformations on the intervertebral discs. Whole human body finite element models at 90°, 95°, 100°, 105°, 110° and 115° inclinations were used to provide a whole-body condition when predicting the behaviour of the lumbar spine. Von Mises stress on the annulus fibrosus, intradiscal pressure, and intervertebral disc height were extracted. The Risk Factors were calculated to evaluate the spinal injury risk under long-term vibration conditions. The results showed that the internal loads and deformations on the intervertebral disc decreased and then increased with the increase of the inclination, and the responses were lower at the 95° and 100° inclinations. The Risk Factors at different inclinations at the 3 Hz load were 0.61, 0.49, 0.53, 0.58, 0.58, and 0.69, respectively, at the 7 Hz load were 0.97, 0.66, 0.71, 0.86, 0.87, and 0.97, respectively, which also showed that injury risk was at a lower level at 95° and 100° inclinations. This study found a relationship between injury risk and back inclination. Occupational drivers are advised to choose a back inclination between 95° and 100° to reduce the possible adverse effects of whole-body vibration during the working condition.

Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models.

Introduction: Chest deformation has been proposed as the best predictor of thoracic injury risk in frontal impacts. Finite Element Human Body Models (FE-HBM) can enhance the results obtained in physical crash tests with Anthropometric Test Devices (ATD) since they can be exposed to omnidirectional impacts and their geometry can be modified to reflect specific population groups. This study aims to assess the sensitivity of two thoracic injury risk criteria (PC Score and Cmax) to several personalization techniques of FE-HBMs. Methods: Three 30° nearside oblique sled tests were reproduced using the SAFER HBM v8 and three personalization techniques were applied to this model to evaluate the influence on the risk of thoracic injuries. First, the overall mass of the model was adjusted to represent the weight of the subjects. Second, the model anthropometry and mass were modified to represent the characteristics of the post-mortem human subjects (PMHS). Finally, the spine alignment of the model was adapted to the PMHS posture at t = 0ms, to conform to the angles between spinal landmarks measured in the PMHS. The following two metrics were used to predict three or more fractured ribs (AIS3+) of the SAFER HBM v8 and the effect of personalization techniques: the maximum posterior displacement of any studied chest point (Cmax), and the sum of the upper and lower deformation of selected rib points (PC score). Results: Despite having led to statistically significant differences in the probability of AIS3+ calculations, the mass-scaled and morphed version provided, in general, lower values for injury risk than the baseline model and the postured version being the latter, which exhibited the better approximation to the PMHS tests in terms of probability of injury. Additionally, this study found that the prediction of AIS3+ chest injuries based on PC Score resulted in higher probability values than the prediction based on Cmax for the loading conditions and personalization techniques analyzed within this study. Discussion: This study could demonstrate that the personalization techniques do not lead to linear trends when they are used in combination. Furthermore, the results included here suggest that these two criteria will result in significantly different predictions if the chest is loaded more asymmetrically.

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.

Numerical investigation of THUMS (Total human model for safety) lower extremity FE model for under-body blast loading

The lower extremity being closest to the detonation point, is the most injured anatomical location due to blast loading. A numerical investigation is a cost-effective and time-efficient solution to the blast experiments involving safety concerns and ethical issues. A finite element human body model (HBM) closely approximates a human body's geometry and inertial property, which can be leveraged to study blast loading patterns and injury mechanisms. This study investigated the THUMS lower extremity finite model response in UBB (Under-body blast) loading. The lower extremity model response was evaluated numerically by recreating the experimental loading from literature and comparing the response from experimental data. Biofidelity of the lower extremity FE model was predicted using Correlation and Analysis (CORA) ratings which suggested a good match between numerical response and experimental data.

Assessment of Finite Element Human Body and ATD Models in Estimating Injury Risk in Far-Side Impacts Using Field-Based Injury Risk

Assessment of Finite Element Human Body and ATD Models in Estimating Injury Risk in Far-Side Impacts Using Field-Based Injury Risk

Effect of whole-body vibration at different frequencies on the lumbar spine: A finite element study based on a whole human body model.

Many previous studies have found that occupational drivers commonly suffered from low back pain, and low back pain and degeneration of the intervertebral disc might be associated with vibration conditions. However, the biomechanical mechanisms of whole-body vibration that caused pain and injury were not clear. In this study, a validated whole human body finite element model was used, and vibration loads at frequencies of 3, 5, 7 and 9 Hz were loaded to evaluate the frequency effects on the spine. The results showed that the responses of the spine were strong at the 5 Hz vibration load. Vibration loads would produce alternating stresses and bulges in the annulus fibrosus and change the direction of the pressure in the nucleus pulposus. The posterior region of the intervertebral disc showed greater stress fluctuations than the anterior region. The Risk Factors showed that long-term exposure to whole-body vibrations at 5 and 7 Hz might have greater adverse effects on the spine. The findings of this study confirmed that vibrations near the resonance frequency of the human body would cause more injuries to the spine than other frequencies. Alternating stress and bulge might cause fatigue and the degeneration of the intervertebral disc, which might be the mechanisms of spinal injury caused by whole-body vibration, and the posterior regions of the intervertebral disc were more susceptible to degeneration. Some appropriate measures should be taken to reduce the adverse effects of whole-body vibration on spinal health.