Exercise quantification from single camera view markerless 3D pose estimation.

Sports physiotherapists and coaches are tasked with evaluating the movement quality of athletes across the spectrum of ability and experience. However, the accuracy of visual observation is low and existing technology outside of expensive lab-based solutions has limited adoption, leading to an unmet need for an efficient and accurate means to measure static and dynamic joint angles during movement, converted to movement metrics useable by practitioners. This paper proposes a set of pose landmarks for computing frequently used joint angles as metrics of interest to sports physiotherapists and coaches in assessing common strength-building human exercise movements. It then proposes a set of rules for computing these metrics for a range of common exercises (single and double drop jumps and counter-movement jumps, deadlifts and various squats) from anatomical key-points detected using video, and evaluates the accuracy of these using a published 3D human pose model trained with ground truth data derived from VICON motion capture of common rehabilitation exercises. Results show a set of mathematically defined metrics which are derived from the chosen pose landmarks, and which are sufficient to compute the metrics for each of the exercises under consideration. Comparison to ground truth data showed that root mean square angle errors were within 10° for all exercises for the following metrics: shin angle, knee varus/valgus and left/right flexion, hip flexion and pelvic tilt, trunk angle, spinal flexion lower/upper/mid and rib flare. Larger errors (though still all within 15°) were observed for shoulder flexion and ASIS asymmetry in some exercises, notably front squats and drop-jumps. In conclusion, the contribution of this paper is that a set of sufficient key-points and associated metrics for exercise assessment from 3D human pose have been uniquely defined. Further, we found generally very good accuracy of the Strided Transformer 3D pose model in predicting these metrics for the chosen set of exercises from a single mobile device camera, when trained on a suitable set of functional exercises recorded using a VICON motion capture system. Future assessment of generalization is needed.

Forward dynamics computational modelling of a cyclist fall with the inclusion of protective response using deep learning-based human pose estimation.

Single bicycle crashes, i.e., falls and impacts not involving a collision with another road user, are a significantly underestimated road safety problem. The motions and behaviours of falling people, or fall kinematics, are often investigated in the injury biomechanics research field. Understanding the mechanics of a fall can help researchers develop better protective gear and safety measures to reduce the risk of injury. However, little is known about cyclist fall kinematics or dynamics. Therefore, in this study, a video analysis of cyclist falls is performed to investigate common kinematic forms and impact patterns. Furthermore, a pipeline involving deep learning-based human pose estimation and inverse kinematics optimisation is created for extracting human motion from real-world footage of falls to initialise forward dynamics computational human body models. A bracing active response is then optimised for using a genetic algorithm. This is then applied to a case study of a cyclist fall. The kinematic forms characterised in this study can be used to inform initial conditions for computational modelling and injury estimation in cyclist falls. Findings indicate that protective response is an important consideration in fall kinematics and dynamics, and should be included in computational modelling. Furthermore, the novel reconstruction pipeline proposed here can be applied more broadly for traumatic injury biomechanics tasks. The tool developed in this study is available at https://kevgildea.github.io/KinePose/.

Development of a biofidelic computational model of human pelvis for predicting biomechanical responses and pelvic fractures.

BACKGROUND AND OBJECTIVE: The pelvis, a crucial structure for human locomotion, is susceptible to injuries resulting in significant morbidity and disability. This study aims to introduce and validate a biofidelic computational pelvis model, enhancing our understanding of pelvis injury mechanisms under lateral loading conditions. METHODS: The Finite Element (FE) pelvic model, representing a mid-sized male, was developed with variable cortical thickness in pelvis bones. Material properties were determined through a synthesis of existing constitutive models, parametric studies, and multiple validations. Comprehensive validation included various tests, such as load-displacement assessments of sacroiliac joints, quasi-static and dynamic lateral compression on the acetabulum, dynamic side impacts on the acetabulum and iliac wing using defleshed pelvis, and lateral impacts by a rigid plate on the full body's pelvis region. RESULTS: Simulation results demonstrated a reasonable correlation between the pelvis model's overall response and cadaveric testing data. Predicted fracture patterns of the isolated pelvis exhibited fair agreement with experimental results. CONCLUSIONS: This study introduces a credible computational model, providing valuable biomechanical insights into the pelvis' response under diverse lateral loading conditions and fracture patterns. The work establishes a robust framework for developing and enhancing the biofidelity of pelvis FE models through a multi-level validation approach, stimulating further research in modeling, validation, and experimental studies related to pelvic injuries. The findings are expected to offer critical perspectives for predicting, preventing, and mitigating pelvic injuries from vehicular accidents, contributing to advancements in clinical research on medical treatments for pelvic fractures.

Development and Mechanical Analysis of Human Liver Model During Impact.

Liver injury is one of the most severe traffic trauma. The development of accurate liver finite element model is beneficial for improving the biofidelity and validity in crash simulations, aiming to analyze the injury in accidents. 12 human liver finite element models in the current research were constructed from high resolution CT data of a Chinese male 50th percentile human subject, including the main structures like left lobe, right lobe, capsule, parenchyma and falciform ligament. The simulations based on Nava et al. experiment were conducted to validate the models and make comparisons of modeling method accuracy. The results demonstrated that the larger deviation happened to the tetra models due to the stiffer algorithm compared to the hex models, which were more sensitive to element size. The existence of capsule had significant effects on the liver mechanical responses, reducing the liver tissue pressure. Shell elements were more suitable for modeling the capsule.

Finite element brain deformation in adolescent soccer heading.

Finite element (FE) modeling provides a means to examine how global kinematics of repetitive head loading in sports influences tissue level injury metrics. FE simulations of controlled soccer headers in two directions were completed using a human head FE model to estimate biomechanical loading on the brain by direction. Overall, headers were associated with 95th percentile peak maximum principal strains up to 0.07 and von Mises stresses up to 1450 Pa, and oblique headers trended toward higher values than frontal headers but below typical injury levels. These quantitative data provide insight into repetitive loading effects on the brain.

Abnormal L5-S1 Facet Joint Orientation as a Harbinger of Degenerative Spondylolisthesis: A Case Report.

Degenerative spondylolisthesis is a common cause of low back pain and resultant disability in the adult population. The causes of degenerative spondylolisthesis are not entirely understood, though a combination of anatomic and lifestyle factors likely contributes to the development of this pathology. Here, we report a case of a 38-year-old female presenting with low back pain and right lower extremity radiculopathy, found to have degenerative L5-S1 spondylolisthesis, which we postulate developed in part due to the sagittal orientation of her L5-S1 facet joints bilaterally.

Effectiveness of Wearable Protection Equipment for Seated Pedestrians.

This study used finite element models to investigate the efficacy of seated pedestrian protection equipment in vehicle impacts. The selected safety equipment, a lap belt, an airbag vest, and a bicycle helmet, were chosen to mitigate the underlying biomechanical causes of seated pedestrian injuries reported in the literature. The impact conditions were based on the three most dangerous impact scenarios from a previous seated pedestrian impact study. Serious injury (AIS 3+) risks were compared with and without protective equipment. A 50th percentile male occupant model and two generic vehicle models, the family car (FCR) and sports utility vehicle (SUV), were used to simulate vehicle collisions. Three impact conditions were run with every combination of protective equipment (n = 24). The helmet reduced head and brain injury risks from the vehicle-head and ground-head contacts. The airbag reduced the head injury risk in the FCR vehicle-head contact but increased the brain injury risks in the SUV impacts from increased whiplash. The lap belt increased head injury risks for both the FCR and the SUV impacts because it created a stronger FCR vehicle-head contact and SUV ground-head contact. When the belt and airbag were used together the head injury risks dramatically decreased because the pedestrian body impacted the ground arm or leg first and slowly rolled onto the ground which resulted in softer ground-head contacts and in two instances, no ground-head contact. Only the helmet proved effective in all impact conditions. Future testing must be completed before recommending the belt or airbag for seated pedestrians.

Biofidelity Assessment of the WIAMan Thorax by a Comparative Study With Hybrid III, THOR, and PMHS in Frontal Sled Testing.

The Warrior Injury Assessment Manikin (WIAMan) anthropomorphic test device (ATD) has been originally developed to predict and prevent injuries for occupants in military vehicles, in an underbody blast environment. However, its crash performance and biofidelity of the thoracic region have not been explored. The aim of this study was to determine and evaluate the WIAMan thoracic responses in a typical frontal sled test. The 40 kph frontal sled tests were conducted to quantify the WIAMan thoracic kinematics, chest deflection, and belt loads. Comparative biofidelities of the WIAMan thorax and other surrogates, including postmortem human surrogates (PMHSs), Hybrid III, and test device for human occupant restraint (THOR) ATDs, were assessed under comparable testing conditions. The similarities and differences between WIAMan and the other surrogates were compared and analyzed, including the motion of bilateral shoulders and T1, time histories of chest deflections, and belt loads. The CORrelation and Analysis (CORA) ratings were used to evaluate the correlations of thoracic responses between the ATDs and PMHS. Compared to the PMHS and THOR, the WIAMan experienced a similar level of left shoulder forward excursions. Larger chest deflection was exhibited in WIAMan throughout the whole duration of belt compression. Differences were found in belt loads between subject types. Overall, WIAMan had slightly lower CORA scores but showed comparable overall performance. The overall thoracic responses of WIAMan under the frontal sled test were more compliant than HIII, but still reasonable compared with PMHS and THOR. Comprehensive systematic studies on comparative biofidelity of WIAMan and other surrogates under different impact conditions are expected in future research.

A Review of Cyclist Head Injury, Impact Characteristics and the Implications for Helmet Assessment Methods.

Head injuries are common for cyclists involved in collisions. Such collision scenarios result in a range of injuries, with different head impact speeds, angles, locations, or surfaces. A clear understanding of these collision characteristics is vital to design high fidelity test methods for evaluating the performance of helmets. We review literature detailing real-world cyclist collision scenarios and report on these key characteristics. Our review shows that helmeted cyclists have a considerable reduction in skull fracture and focal brain pathologies compared to non-helmeted cyclists, as well as a reduction in all brain pathologies. The considerable reduction in focal head pathologies is likely to be due to helmet standards mandating thresholds of linear acceleration. The less considerable reduction in diffuse brain injuries is likely to be due to the lack of monitoring head rotation in test methods. We performed a novel meta-analysis of the location of 1809 head impacts from ten studies. Most studies showed that the side and front regions are frequently impacted, with one large, contemporary study highlighting a high proportion of occipital impacts. Helmets frequently had impact locations low down near the rim line. The face is not well protected by most conventional bicycle helmets. Several papers determine head impact speed and angle from in-depth reconstructions and computer simulations. They report head impact speeds from 5 to 16 m/s, with a concentration around 5 to 8 m/s and higher speeds when there was another vehicle involved in the collision. Reported angles range from 10° to 80° to the normal, and are concentrated around 30°-50°. Our review also shows that in nearly 80% of the cases, the head impact is reported to be against a flat surface. This review highlights current gaps in data, and calls for more research and data to better inform improvements in testing methods of standards and rating schemes and raise helmet safety.

Computational Seated Pedestrian Impact Design of Experiments with Ultralight Wheelchair.

Pedestrians who use wheelchairs (seated pedestrians) report higher mortality rates than standing pedestrians in vehicle-to-pedestrian collisions but the cause of this mortality is poorly understood. This study investigated the cause of seated pedestrian serious injuries (AIS 3+) and the effect of various pre-collision variables using finite element (FE) simulations. An ultralight manual wheelchair model was developed and tested to meet ISO standards. The GHBMC 50th percentile male simplified occupant model and EuroNCAP family car (FCR) and sports utility vehicle (SUV) were used to simulate vehicle collisions. A full factorial design of experiments (n = 54) was run to explore the effect of pedestrian position relative to the vehicle bumper, pedestrian arm posture, and pedestrian orientation angle relative to the vehicle. The largest average injury risks were at the head (FCR: 0.48 SUV: 0.79) and brain (FCR: 0.42 SUV: 0.50). The abdomen (FCR: 0.20 SUV: 0.21), neck (FCR: 0.08 SUV: 0.14), and pelvis (FCR: 0.02 SUV: 0.02) reported smaller risks. 50/54 impacts reported no thorax injury risk, but 3 SUV impacts reported risks ≥ 0.99. Arm (gait) posture and pedestrian orientation angle had larger effects on most injury risks. The most dangerous arm posture examined was when the hand was off the wheelchair handrail after wheel propulsion and the two more dangerous orientations were when the pedestrian faced 90° and 110° away from the vehicle. Pedestrian position relative to the vehicle bumper played little role in injury outcomes. The findings of this study may inform future seated pedestrian safety testing procedures to narrow down the most concerning impact scenarios and design impact tests around them.

A Research on Accident Reconstruction of Bus-Two-Wheeled Vehicle Based on Vehicle Damage and Human Head Injury.

The problem of large calculation models in bus-two-wheeled vehicle traffic accidents (TA) leads to the difficulty of balancing the calculation efficiency and accuracy, as well as difficulties in accident reconstruction. Herein, two typical accidents were reconstructed, based on the rigid-flexible coupled human model (HM) and the Facet vehicle model, and the vehicle damage conditions and the human head biomechanical injury were analyzed. The simulation results showed that the physical process of the human-vehicle collision was basically consistent with the accident video, the windshield fracture was consistent with the actual vehicle report, and the human biomechanical injury characteristics were also consistent with the autopsy report, which verified the feasibility of the simulation model, and provides a basis and reference for forensic identification and for traffic police to deal with accident disputes.

Cerebral hemorrhage caused by shaking adult syndrome? Evidence from biomechanical analysis using 3D motion capture and finite element models.

The present study combined three-dimensional (3D) motion capture with finite element simulation to reconstruct a real shaking adult syndrome (SAS) case and further explore the injury biomechanics of SAS. The frequency at which an adult male can shake the head of another person, head-shaking amplitude, and displacement curves was captured by the VICON 3D motion capture system. The captured shaking frequency and shaking curve were loaded on the total human model for safety (THUMS) head to simulate the biomechanical response of brain injury when a head was shaken in anterior-posterior, left-right, and left anterior-right posterior directions at frequencies of 4 Hz (Hz), 5 Hz, 6 Hz, and 7 Hz. The biomechanical response of the head on impact in the anterior, posterior, left, left anterior, and right posterior directions at the equivalent velocity of 6 Hz shaking was simulated. The violent shaking frequency of the adult male was 3.2-6.8 Hz; head shaking at these frequencies could result in serious cerebral injuries. SAS-related injuries have obvious directionality, and sagittal shaking can easily cause brain injuries. There was no significant difference between the brain injuries caused by shaking in the simulated frequency range (4-7 Hz). Impact and shaking at an equivalent velocity could cause brain injuries, though SAS more commonly occurred due to the cumulative deformation of brain tissue. Biomechanical studies of SAS should play a positive role in improving the accuracy of forensic identification and reducing this form of abuse and torture in detention or places of imprisonment.

A validated lower extremity model to investigate the effect of stabilizing knee components in pedestrian collisions.

Lower extremity injuries account for over 50% of pedestrian orthopedic injuries in car-to-pedestrian collisions. Pedestrian finite element models are useful tools for studying pedestrian safety, but current models use simplified knee models that exclude potentially important stabilizing knee components. The effect of these stabilizing components in pedestrian impacts is currently unknown. The goal of this study was to develop a detailed lower-extremity model to investigate the effect of these stabilizing components on pedestrian biomechanics. In this study the Global Human Body Model Consortium male 50th percentile pedestrian model lower body was updated to include various stabilizing knee components, enhance geometric anatomical accuracy of previously modeled soft tissue structures, and update hard and soft tissue material models. The original and updated models were compared across 13 validation tests and the updated model reported significantly (p = 0.01) larger CORA scores (0.73 ± 0.15) than the original model (0.56 ± 0.20). To investigate the effect of the new stabilizing knee components the updated model had its stabilizing components severed. The severed and intact models were impacted by the EuroNCAP SUV and family car models at 30 and 40 km/h. The intact and severed models reported nearly identical head impact times, wrap around distances, and lower-extremity injury outcomes in all four impacts, but the stabilizing components reduced the varus knee angle of the secondarily impacted leg by up to 4.9°. The stabilizing components may prevent secondary impacted leg injuries in lower intensity impacts but overall had little effect on pedestrian biomechanical outcomes.

Incorporating neck biomechanics in helmet testing: Evaluation of commercially available WaveCel helmets.

BACKGROUND: Cycling helmets often incorporate elements aimed to dissipate rotational energies, which is widely acknowledged to play a key role in concussion mechanics. In this study, we investigated the mechanics of an oblique helmet test protocol that induced helmet rotation while using it to evaluate the effectiveness of three helmet models: two standard expanded polystyrene helmets and a commercially-available helmet equipped with a liner designed to mitigate linear and rotational energies. METHODS: Helmets equipped with WaveCel were tested against two expanded polystyrene helmet models through guided drops using a Hybrid III (HIII) head-and-neck surrogate. The three helmet models were tested across four impact conditions (n = 5) of different speeds and impact surface angles. FINDINGS: Across all tests, a similar sequence of head motion was observed - first a flexion phase followed by an extension phase. The extension phase lacked evidence of biofidelity and was likely attributable to the energy stored in the neckform during the flexion phase; it was therefore neglected from analysis. Results showed WaveCel reduced the probability of AIS2 head injury across all tests (3 to 27% reductions in 4.8 m/s impacts; 36 to 37% reductions in 6.2 m/s impacts). INTERPRETATION: The two-phased response of the HIII suggests that boundary condition selection can influence results and should thus be reported in studies using similar methods. While this protocol involved both axial and tangential impact components and were thus representative of real-world collisions, the efficacy of WaveCel should be further investigated through additional laboratory studies and tracking real-world cycling injury statistics.

The finite element method-based pattern recognition approach for the classification of patient-specific gunshot injury.

Violence related injuries and deaths mostly caused by firearms are a major problem throughout the world. Understanding the factors that control the extent of hard-soft tissue wound patterns using computer imaging techniques, numerical methods, and machine learning algorithms may help physicians to diagnose and treat those injuries more properly. Here, we investigate the use of computational results coupled with the pattern recognition algorithms to develop an approach for forensic applications. Initially, computer tomography (CT) images of the patient whose leg was shot by a 9 × 19 parabellum bullet are used to construct the FE models of that patient's femoral bone and the surrounding soft tissues. Then, Hounsfield units-based material properties are assigned to elements of the bone. To simulate the full range of loading conditions encountered in ballistic events, a constitutive model that captures the strain-rate dependent response is implemented. The entrance pathway vector of the bullet is directed in accordance with the patient's wound and the simulations are deployed for the cases having various inlet velocities such as 150, 200, 250, 300, and 350 m/s. Once the FE results for each case are obtained, they are processed with supervised machine learning algorithms to classify the wound and inlet velocity correspondence. The results demonstrate that they can be diagnosed with a percent accuracy of 97.3, 97.5, and 98.3 for the decision tree (DT), k-nearest neighbors (kNN) and support vector machine (SVM) classifier, respectively. This approach may provide a useful framework in classifying the wound type, predicting the bullet impact velocity and its firing distance.

The relationship between road traffic collision dynamics and traumatic brain injury pathology.

Road traffic collisions are a major cause of traumatic brain injury. However, the relationship between road traffic collision dynamics and traumatic brain injury risk for different road users is unknown. We investigated 2065 collisions from Great Britain's Road Accident In-depth Studies collision database involving 5374 subjects (2013-20). Five hundred and ninety-five subjects sustained a traumatic brain injury (20.2% of 2940 casualties), including 315 moderate-severe and 133 mild-probable injuries. Key pathologies included skull fracture (179, 31.9%), subarachnoid haemorrhage (171, 30.5%), focal brain injury (168, 29.9%) and subdural haematoma (96, 17.1%). These results were extended nationally using >1 000 000 police-reported collision casualties. Extrapolating from the in-depth data we estimate that there are ∼20 000 traumatic brain injury casualties (∼5000 moderate-severe) annually on Great Britain's roads, accounting for severity differences. Detailed collision investigation allows vehicle collision dynamics to be understood and the change in velocity (known as delta-V) to be estimated for a subset of in-depth collision data. Higher delta-V increased the risk of moderate-severe brain injury for all road users. The four key pathologies were not observed below 8 km/h delta-V for pedestrians/cyclists and 19 km/h delta-V for car occupants (higher delta-V threshold for focal injury in both groups). Traumatic brain injury risk depended on road user type, delta-V and impact direction. Accounting for delta-V, pedestrians/cyclists had a 6-times higher likelihood of moderate-severe brain injury than car occupants. Wearing a cycle helmet during a collision was protective against overall and mild-to-moderate-to-severe brain injury, particularly skull fracture and subdural haematoma. Cycle helmet protection was not due to travel or impact speed differences between helmeted and non-helmeted cyclist groups. We additionally examined the influence of the delta-V direction. Car occupants exposed to a higher lateral delta-V component had a greater prevalence of moderate-severe brain injury, particularly subarachnoid haemorrhage. Multivariate logistic regression models created using total delta-V value and whether lateral delta-V was dominant had the best prediction capabilities (area under the receiver operator curve as high as 0.95). Collision notification systems are routinely fitted in new cars. These record delta-V and automatically alert emergency services to a collision in real-time. These risk relationships could, therefore, inform how routinely fitted automatic collision notification systems alert the emergency services to collisions with a high brain injury risk. Early notification of high-risk scenarios would enable quicker activation of the highest level of emergency service response. Identifying those that require neurosurgical care and ensuring they are transported directly to a centre with neuro-specialist provisions could improve patient outcomes.

A Potentially Dangerous Industrial Projectile Lodged in the Leg of a Steel Factory Worker.

Penetrating injuries due to fragments energized by an explosive event are life/limb-threatening and are associated with poor clinical and functional outcomes. Penetrating injuries are commonly inflicted in attacks with explosive devices. The extremities, especially the leg, are the most commonly affected body areas, presenting a high risk of infection, slow recovery, and the threat of amputation. This report presents a case of a young factory worker who sustained an injury to the leg with a foreign body lodged near the neuro-vascular bundle. A 44-year-old gentleman sustained a projectile injury while working in a stainless steel factory from the rula (steel rolling) machine with a foreign body getting lodged in the leg in March 2019. He was initially managed with wound care and didn't report any functional impairment. Gradually patient developed numbness and claudication symptoms of the foot over the next couple of years. He was subsequently operated on in 2021 for removal of the stainless steel foreign body encased in dystrophic calcification close to the tibial nerve and posterior tibial vessels. Interestingly the entry point of the foreign body was on the anterolateral aspect of the leg. The foreign body was removed using the postero-lateral approach to the tibia with careful dissection close to the neurovascular bundle. At a follow-up of 3 months, the patient is symptom-free with significant improvement of limb function. The authors propose that the foreign body crossed the interosseous membrane to get lodged close to the posterior tibial neurovascular bundle. In such a scenario, the patient was extremely lucky to have survived an amputation or significant functional injury of the limb. Proper protective equipment is needed not only for the torso but also for extremities to protect industrial workers from such limb-threatening injuries. Moreover, primary care physicians should be sensitised for the proper management of such injuries.

The Lack of Sex, Age, and Anthropometric Diversity in Neck Biomechanical Data.

Female, elderly, and obese individuals are at greater risk than male, young, and non-obese individuals for neck injury in otherwise equivalent automotive collisions. The development of effective safety technologies to protect all occupants requires high quality data from a range of biomechanical test subjects representative of the population at risk. Here we sought to quantify the demographic characteristics of the volunteers and post-mortem human subjects (PMHSs) used to create the available biomechanical data for the human neck during automotive impacts. A systematic literature and database search was conducted to identify kinematic data that could be used to characterize the neck response to inertial loading or direct head/body impacts. We compiled the sex, age, height, weight, and body mass index (BMI) for 999 volunteers and 110 PMHSs exposed to 5,431 impacts extracted from 63 published studies and three databases, and then compared the distributions of these parameters to reference data drawn from the neck-injured, fatally-injured, and general populations. We found that the neck biomechanical data were biased toward males, the volunteer data were younger, and the PMHS data were older than the reference populations. Other smaller biases were also noted, particularly within female distributions, in the height, weight, and BMI distributions relative to the neck-injured populations. It is vital to increase the diversity of volunteer and cadaveric test subjects in future studies in order to fill the gaps in the current neck biomechanical data. This increased diversity will provide critical data to address existing inequities in automotive and other safety technologies.

Evaluation and Validation of Thorax Model Responses: A Hierarchical Approach to Achieve High Biofidelity for Thoracic Musculoskeletal System.

As one of the most frequently occurring injuries, thoracic trauma is a significant public health burden occurring in road traffic crashes, sports accidents, and military events. The biomechanics of the human thorax under impact loading can be investigated by computational finite element (FE) models, which are capable of predicting complex thoracic responses and injury outcomes quantitatively. One of the key challenges for developing a biofidelic FE model involves model evaluation and validation. In this work, the biofidelity of a mid-sized male thorax model has been evaluated and enhanced by a multi-level, hierarchical strategy of validation, focusing on injury characteristics, and model improvement of the thoracic musculoskeletal system. At the component level, the biomechanical responses of several major thoracic load-bearing structures were validated against different relevant experimental cases in the literature, including the thoracic intervertebral joints, costovertebral joints, clavicle, sternum, and costal cartilages. As an example, the thoracic spine was improved by accurate representation of the components, material properties, and ligament failure features at tissue level then validated based on the quasi-static response at the segment level, flexion bending response at the functional spinal unit level, and extension angle of the whole thoracic spine. At ribcage and full thorax levels, the thorax model with validated bony components was evaluated by a series of experimental testing cases. The validation responses were rated above 0.76, as assessed by the CORA evaluation system, indicating the model exhibited overall good biofidelity. At both component and full thorax levels, the model showed good computational stability, and reasonable agreement with the experimental data both qualitatively and quantitatively. It is expected that our validated thorax model can predict thorax behavior with high biofidelity to assess injury risk and investigate injury mechanisms of the thoracic musculoskeletal system in various impact scenarios. The relevant validation cases established in this study shall be directly used for future evaluation of other thorax models, and the validation approach and process presented here may provide an insightful framework toward multi-level validating of human body models.

Development and multi-level validation of a computational model to predict traumatic aortic injury.

Traumatic aortic injury (TAI) is one of the leading causes of fatalities in blunt impact. However, there is no consensus on the injury mechanism of TAI in traffic accidents, mainly due to the complexity of occurrence scenarios and limited real-world crash data relevant to TAI. In this study, a computational model of the aorta with nonlinear mechanical characteristics and accurate morphology was developed and integrated within a thorax finite element model that included all major anatomical structures. To maximize the model's capability for predicting TAI, a multi-level process was presented to validate the model comprehensively. At the component level, the in vitro aortic pressurization testing was simulated to mimic the aortic burst pressure. Then, a sled test of a truncated cadaver was modeled to evaluate aorta response under posterior acceleration. The frontal chest pendulum impact was utilized to validate the performance of the aorta within full body model under direct chest compression. A parametric study was implemented to determine an injury tolerance for the aorta under these different loading conditions. The simulated peak pressure before aortic rupture was within the range of the experimental burst pressure. For the sled test, the simulated chest deflection and cross-sectional pressure of the aorta were correlated with the experimental measurement. No aorta injury was observed in simulated results of both sled test and chest pendulum impact, which matched the experimental findings. The present model will be a useful tool for understanding the TAI mechanisms, evaluating injury tolerance, and developing prevention strategies for aortic injuries.