Body Model Research Articles

A biomechanical model of a vehicle passenger in the sagittal plane

Musculoskeletal biomechanical models have wide applications in ergonomics, rehabilitation, and injury estimation. Their use can be extended to enable quantitatively explaining and estimating ride comfort for a vehicle's passenger. A biomechanical model of the upper body in the sagittal plane is constructed, which allows for curved motion to simulate the propagation of disturbance energy within a seated passenger aboard a moving vehicle. The dynamic predictions of the model are validated against experimental results within the literature. Frequency responses show that within the vehicular frequency range, the L4L5 and the L5S1 discs in the lower lumbar region are susceptible to the highest vibration transmission. It was also found that vibration transmission is maximized at around 4.5 Hz. The model provides analytical and geometric intuition into the motion of the various segments of the upper body using a few simple geometric assumptions and can be employed to develop a quantitative ride-comfort metric, such that the most comfortable ride would be that which would induce the least internal motion within the passenger model.

Precision black body model at a temperature range of 200–450 K: metrological assurance for optical-electronic equipment for remote sensing of the Earth in the infrared range of the spectrum

Precision black body model at a temperature range of 200–450 K: metrological assurance for optical-electronic equipment for remote sensing of the Earth in the infrared range of the spectrum

Comparative Analysis of Convolutional Neural Network Architectures for Automated Knee Segmentation in Medical Imaging: A Performance Evaluation

Abstract Segmentation of anatomical components is a major step in creating accurate and realistic 3D models of the human body, which are used in many clinical applications, including orthopedics. Recently, many deep learning approaches have been proposed to solve the problem of manual segmentation, which is time-consuming and operator-dependent. In the present study, SegResNet has been adapted from other domains, such as brain tumors, for knee joints, in particular, to segment the femoral bone from magnetic resonance images. This algorithm has been compared to the well-known U-Net in terms of evaluation metrics, such as the Dice similarity coefficient and Hausdorff distance. In the training phase, various combinations of hyperparameters, such as epochs and learning rates, have been tested to determine which combination produced the most accurate results. Based on their comparable results, both U-Net and SegResNet performed well in accurately segmenting the femur. Dice similarity coefficients of 0.94 and Hausdorff distances less than or equal to 1 mm indicate that both models are effective at capturing anatomical boundaries in the femur. According to the results of this study, SegResNet is a viable option for automating the creation of 3D femur models. In the future, the performance and applicability of SegResNet in real-world settings will be further validated and tested using a variety of datasets and clinical scenarios.

Biomechanical Response of Head Surrogate With and Without the Helmet.

Measurements of brain deformations under injurious loading scenarios are actively sought. In this work, we report experimentally measured head kinematics and corresponding dynamic, two-dimensional brain simulant deformations in head surrogates under a blunt impact, with and without a helmet. Head surrogates used in this work consisted of skin, skull, dura, falx, tentorium, and brain stimulants. The head surrogate geometry was based on the global human body models consortium's head model. A base head surrogate consisting of skin-skull-brain was considered. In addition, the response of two other head surrogates, skin-skull-dura-brain, and skin-skull-dura-brain-falx-tentorium, was investigated. Head surrogate response was studied for sagittal and coronal plane rotations for impactor velocities of 1 and 3 m/s. Response of head surrogates was compared against strain measurements in PMHS. The strain pattern in the brain simulant was heterogenous, and peak strains were established within ∼30 ms. The choice of head surrogate affect the spatiotemporal evolution of strain. For no helmet case, peak MPS of ∼50-60% and peak MSS of ∼35-50% were seen in brain simulant corresponding to peak rotational accelerations of ∼5000-7000 rad/s2. Peak head kinematics and peak MPS have been reduced by up to 75% and 45%, respectively, with the conventional helmet and by up to 90% and 85%, respectively, with the helmet with antirotational pads. Overall, these results provide important, new data on brain simulant strains under a variety of loading scenarios-with and without the helmets.

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.

Lower Extremity Injury Risk Curve Development for a Human Body Model in the Underbody Blast Environment.

Computational human body models (HBMs) provide the ability to explore numerous candidate injury metrics ranging from local strain based criteria to global combined criteria such as the Tibia Index. Despite these efforts, there have been relatively few studies that focus on determining predicted injury risk from HBMs based on observed postmortem human subjects (PMHS) injury data. Additionally, HBMs provide an opportunity to construct risk curves using measures that are difficult or impossible to obtain experimentally. The Global Human Body Models Consortium (GHBMC) M50-O v 6.0 lower extremity was simulated in 181 different loading conditions based on previous PMHS tests in the underbody blast (UBB) environment and 43 different biomechanical metrics were output. The Brier Metric Score were used to determine the most appropriate metric for injury risk curve development. Using survival analysis, three different injury risk curves (IRC) were developed: "any injury," "calcaneus injury," and "tibia injury." For each injury risk curve, the top three metrics selected using the Brier Metric Score were tested for significant covariates including boot use and posture. The best performing metric for the "any injury," "calcaneus injury" and "tibia injury" cases were calcaneus strain, calcaneus force, and lower tibia force, respectively. For the six different injury risk curves where covariates were considered, the presence of the boot was found to be a significant covariate reducing injury risk in five out of six cases. Posture was significant for only one curve. The injury risk curves developed from this study can serve as a baseline for model injury prediction, personal protective equipment (PPE) evaluation, and can aid in larger scale testing and experimental protocols.

Translational medical bioengineering research of traumatic brain injury among Chinese and American pedestrians caused by vehicle collision based on human body finite element modeling

Based on the average human body size in China and the THUMS AM50 finite element model of the human body, the Kriging interpolation algorithm was used to model the Chinese 50th percentile human body, and the biological fidelity of the model was verified. We built three different types of passenger vehicle models, namely, sedan, sports utility vehicle (SUV), and multi-purpose vehicle (MPV), and used mechanical response analysis and finite element simulation to compare and analyze the dynamic differences and head injury differences between the Chinese 50th percentile human body and the THUMS AM50 model during passenger vehicle collisions. The results showed that there are obvious differences between the Chinese mannequin and THUMS in terms of collision time, collision position, invasion speed, and angle. When a sedan collided with the mannequins, the skull damage to the Chinese human body model was more severe, and when a sedan or SUV collided, the brain damage to the Chinese human body was more severe. The abovementioned results suggest that the existing C-NCAP pedestrian protection testing regulations may not provide the best protection for Chinese human bodies, and that the regulations need to be improved by combining collision damage mechanisms and the physical characteristics of Chinese pedestrians. This thorough investigation is positioned to shed light on the fundamental biomechanics and injury mechanisms at play. Furthermore, the amalgamation of clinically rooted translational and engineering research in the realm of traumatic brain injury has the potential to establish a solid foundation for discerning preventive methodologies. Ultimately, this endeavor holds the potential to introduce effective strategies aimed at preventing and safeguarding against traumatic brain injuries.

Long-term exposure to high perceived temperature and risk of mortality among patients with chronic kidney disease

Health risks due to climate change are emerging, particularly from high-temperature exposure. The perceived temperature is an equivalent temperature based on the complete heat budget model of the human body. Therefore, we aimed to analyze the effect of perceived temperature on overall mortality among patients with chronic kidney disease. In total, 32,870 patients with chronic kidney disease in Seoul participated in this retrospective study (2001–2018) at three medical centers. The perceived temperature during the summer season was calculated using meteorological factors, including the air temperature near the automated weather station, dew point temperature, wind velocity, and total cloud amount. We assessed the association between perceived temperature using Kriging spatial interpolation and mortality in patients with CKD in the time-varying Cox proportional hazards model that was adjusted for sex, age, body mass index, hypertension, diabetes mellitus, estimated glomerular filtration rate, smoking, alcohol consumption, and educational level. During the 6.14 ± 3.96 years of follow-up, 3863 deaths were recorded. In multivariable analysis, the average level of perceived temperature and maximum level of perceived temperature demonstrated an increased risk of overall mortality among patients with chronic kidney disease. The concordance index for mortality of perceived temperature was higher than temperature, discomfort index, and heat index. When stratified by age, diabetes mellitus, and estimated glomerular filtration rate, patients with chronic kidney disease with young age (age <65 years) showed higher hazard ratio for mortality (interaction P = 0.049). Moreover, the risk of death in the winter and spring seasons was more significant compared to that of the summer and autumn seasons. Therefore, long-term exposure to high perceived temperature during summer increases the risk of mortality among patients with chronic kidney disease.

A quasi-static model of a thermoelastic body reinforced by a thin thermoelastic inclusion

The problem of description of quasi-static behavior is studied for a planar thermoelastic body incorporating an inhomogeneity, which geometrically is a strip with a small cross-section. This problem contains a small positive parameter δ describing the thickness of the inhomogeneity, i.e., the size of the cross-section. Relying on the variational formulation of the problem, we investigate the behavior of solutions as δ tends to zero. As the result, by the version of the method of formal asymptotic expansions, we derive a closed limit model in which the inhomogeneity is thin (of zero width). After this, using the Galerkin method and the classical techniques of derivation of energy estimates, we prove existence, uniqueness, and stability of a weak solution to this model.

Borehole transient electromagnetic response calculation and experimental study in coal mine tunnels

Water damage seriously threatens the safe production of coal mines, so it is necessary to carry out advanced detection to determine the hydrogeological situation, and the preliminary survey often involves the drilling of on-site drill holes in the tunnel. The use of directional drill holes, combined with advanced geophysical prospecting technology, enables advanced water disaster detection with long distance and high precision and is independent of the tunnel environment influence. The transient electromagnetic method (TEM) is highly sensitive to low-resistivity anomalies and plays a crucial role in water damage detection. To address the size limitation of borehole detection, in this study, a small rectangular multi-turn loop borehole advanced detection method was developed (borehole TEM, BTEM) to detect low-resistivity anomalies within 10 m of the borehole in the radial direction. To satisfy the size requirements for borehole detection and the detection distance, a small rectangular multi-turn loop device with a width of 6 cm and a length of 50 cm was designed. To resolve the issue of self-inductance and mutual inductance enhancement caused by multi-turn coils, a uniform full-space low-resistivity abnormal body model was established using the Ansys Maxwell software, and we analyzed the vertical magnetic field component of the rectangular multi-turn small loop at different time points and the transient electromagnetic response of the different turns. Then, we determined the appropriate parameters for the transmitting and receiving device. The developed method was applied to several different experimental scenarios to obtain the electrical distribution of the anomalous body in front of the device, and the measured data were inverted and interpreted to obtain the apparent resistivity-depth profile. The results demonstrate that the inversion results align well with the actual situation, confirming the effectiveness of the BTEM. This research offers a potential solution for borehole advance detection and provides a solid theoretical foundation for further studies.

NekMesh: An open-source high-order mesh generation framework

High-order spectral element simulations are now becoming increasingly popular within the computational modelling community, as they offer the potential to deliver increased accuracy at reduced cost compared to traditional low-order codes. However, to support accurate, high-fidelity simulations in complex industrial applications, there is a need to generate curvilinear meshes which robustly and accurately conform to geometrical features. This is, at present, a key challenge within the mesh generation community, with only a few open-source tools able to generate curvilinear meshes for complex geometries. We present NekMesh: an open-source mesh generation package which is designed to enable the generation of valid, high-quality curvilinear meshes of complex, three-dimensional geometries for performing high-order simulations. We outline the software architecture adopted in NekMesh, which uses a pipeline of processing modules to provide a flexible, CAD-independent high-order mesh processing tool, capable of both generating meshes for a wide range of use cases, as well as post-processing linear meshes from a range of input formats for use with high-order simulations. A number of examples in various application areas are presented, with a particular emphasis on challenging aeronautical and fluid dynamics test cases. Program summaryProgram title: NekMesh (version 5.4.0)CPC Library link to program files:https://doi.org/10.17632/d82hjm4v6r.1Licensing provisions: MITProgramming language: C++External routines/libraries: Boost, TinyXML, OpenCASCADE, Triangle, TetGen, HDF5Nature of problem: NekMesh is a high-order mesh generation framework with the goal of providing a robust framework to automate the process of generating valid meshes for complex three-dimensional CAD geometries.Solution method: Energy minimisation, solid body models and other techniques based around high-order finite element methods.Additional comments including restrictions and unusual features: The supplied cases require a system with 16384 MB of RAM for the automotive example and 32768 MB of RAM for the variational optimisation example.

A remark on hard body fluids: density versus packing fraction and excluded volume

Various hard body fluids are used as a reference term in molecular-based equations of state. Originally, these models were obtained either intuitively (as rigid geometrical objects) or by speculative physical considerations (e.g. pseudo-hard bodies). Considering a proper perturbation theory for molecular fluids, these n-site fused-hard-sphere models descend from the complex force field by a well-defined procedure but may also differ in dependence on the used additional approximations. As individual bodies, they are geometrical objects but their mutual interaction may be more complex including also non-additive hard sphere site-site interactions. The properties of such bodies may be expressed as a function of the number density, packing fraction or the overall excluded volume and these different scalings may also lead to even qualitatively different physical conclusions. This becomes particularly important when properties of different fluids are to be compared. This problem is discussed and exemplified by considering both convex body models and hard body models descending from realistic force fields with a specific focus on water and lower alcohols.

SpasticSim: a synthetic data generation method for upper limb spasticity modelling in neurorehabilitation

In neurorehabilitation, assessment of functional problems is essential to define optimal rehabilitation treatments. Usually, this assessment process requires distinguishing between impaired and non-impaired behavior of limbs. One of the common muscle motor disorders affecting limbs is spasticity, which is complicated to quantify objectively due to the complex nature of motor control. Thus, the lack of heterogeneous samples of patients constituting an acceptable amount of data is an obstacle which is relevant to understanding the behavior of spasticity and, consequently, quantifying it. In this article, we use the 3D creation suite Blender combined with the MBLab add-on to generate synthetic samples of human body models, aiming to be as sufficiently representative as possible to real human samples. Exporting these samples to OpenSim and performing four specific upper limb movements, we analyze the muscle behavior by simulating the six degrees of spasticity contemplated by the Modified Ashworth Scale (MAS). The complete dataset of patients and movements is open-source and available for future research. This approach advocates the potential to generate synthetic data for testing and validating musculoskeletal models.

Effects of multiple hydraulic punching for ultra-deep buried high ground stress powdered coal seam with low permeability

The high ground stress and poor gas permeability of the ultra-deep buried highland stress coal seam make it difficult for conventional unloading and permeability-increasing techniques, such as fracturing or cutting, to achieve the goal of coal seam pressure relief. This article proposes a multi-stage hydraulic punching permeability increasing scheme for the M1-7∼M1-9 gas drainage project of the powdered coal seam with highland stress (44.42 MPa) in tunnel No. 2 of Zhaotong, and studies the effect of cavity formation and gas changes caused by multiple hydraulic punching through theoretical analysis and numerical simulation methods. The gas drainage effect after multiple hydraulic punching was also monitored on-site and systematically compared with natural gas drainage and single hydraulic punching permeability-increasing techniques to determine the optimal solution for multi-stage hydraulic punching. Using the COMSOL numerical simulation software, a coal body model was established based on theoretical analysis. Boundary pressures, ideal gas pressures, and high-pressure water flow pressures were set as boundary conditions to simulate the process of hydraulic punching. The theoretical analysis and numerical simulation were then used to guide on-site experiments. The research results shows that for ultra-deep buried highland stress powdered coal seams, natural gas drainage efficiency is extremely low, and the initial effect of single hydraulic punching permeability increasing is significant, but the fast decay rate of short gas is still due to the time that the cavity formed by hydraulic punching exists. Multiple hydraulic punching effectively alleviates the gas decay rate, and the gas drainage efficiency can reach three times and 22 times that of single hydraulic punching and natural drainage techniques, respectively. When the hydraulic punching interval period is five days and the hydraulic punching frequency is three times, the gas drainage effect is optimal. Multiple hydraulic punching permeability-increasing technologies can provide reference for gas extraction in similar low permeability coal seams with highland stress. The research holds great significance in promoting efficient gas extraction and ensuring the safety construction of gas tunnels.

Mechanical response of human thoracic spine ligaments under quasi-static loading: An experimental study

PurposeThis study aimed to investigate the geometrical and mechanical properties of human thoracic spine ligaments subjected to uniaxial quasi-static tensile test. MethodsFour human thoracic spines, obtained through a body donation program, were utilized for the study. The anterior longitudinal ligament (ALL), posterior longitudinal ligament (PLL), capsular ligament (CL), ligamenta flava (LF), and the interspinous ligament and supraspinous ligament complex (ISL + SSL), were investigated. The samples underwent specimen preparation, including dissection, cleaning, and reinforcement, before being immersed in epoxy resin. Uniaxial tensile tests were performed using a custom-designed mechanical testing machine equipped with an environmental chamber (T = 36.6 °C; humidity 95%). Then, the obtained tensile curves were averaged preserving the characteristic regions of typical ligaments response. ResultsGeometrical and mechanical properties, such as initial length and width, failure load, and failure elongation, were measured. Analysis of variance (ANOVA) revealed significant differences among the ligaments for all investigated parameters. Pairwise comparisons using Tukey's post-hoc test indicated differences in initial length and width. ALL and PLL exhibited higher failure forces compared to CL and LF. ALL and ISL + SSL demonstrated biggest failure elongation. Comparisons with other studies showed variations in initial length, failure force, and failure elongation across different ligaments. The subsystem (Th1 – Th6 and Th7 – Th12) analysis revealed increases in initial length, width, failure force, and elongation for certain ligaments. ConclusionsVariations of both the geometric and mechanical properties of the ligaments were noticed, highlighting their unique characteristics and response to tensile force. Presented results extend very limited experimental data base of thoracic spine ligaments existing in the literature. The obtained geometrical and mechanical properties can help in the development of more precise human body models (HBMs).

Brain Material Properties and Integration of Arachnoid Complex for Biofidelic Impact Response for Human Head Finite Element Model.

Finite element head models offer great potential to study brain-related injuries; however, at present may be limited by geometric and material property simplifications required for continuum-level human body models. Specifically, the mechanical properties of the brain tissues are often represented with simplified linear viscoelastic models, or the material properties have been optimized to specific impact cases. In addition, anatomical structures such as the arachnoid complex have been omitted or implemented in a simple lumped manner. Recent material test data for four brain regions at three strain rates in three modes of loading (tension, compression, and shear) was used to fit material parameters for a hyper-viscoelastic constitutive model. The material model was implemented in a contemporary detailed head finite element model. A detailed representation of the arachnoid trabeculae was implemented with mechanical properties based on experimental data. The enhanced head model was assessed by re-creating 11 ex vivo head impact scenarios and comparing the simulation results with experimental data. The hyper-viscoelastic model faithfully captured mechanical properties of the brain tissue in three modes of loading and multiple strain rates. The enhanced head model showed a high level of biofidelity in all re-created impacts in part due to the improved brain-skull interface associated with implementation of the arachnoid trabeculae. The enhanced head model provides an improved predictive capability with material properties based on tissue level data and is positioned to investigate head injury and tissue damage in the future.

Material Properties of Fiber Bundles of the Superficial Medial Collateral Ligament of the Knee Joint.

The superficial medial collateral ligament (sMCL) of the human knee joint has functionally separate anterior and posterior fiber bundles. The two bundles are alternatively loaded as the knee flexion angle changes during walking. To date, the two bundles are usually not distinguished in knee ligament simulations because there has been little information about their material properties. In this study, we conducted quasi-static tensile tests on the sMCL of matured porcine stifle joints and obtained the material properties of the anterior bundle (AB), posterior bundle (PB), and whole ligament (WL). AB and PB have similar failure stress but different threshold strain, modulus, and failure strain. As a result, we recommend assigning different material properties (i.e., modulus and failure strain) to the two fiber bundles to realize biofidelic ligament responses in human body models. However, it is often inconvenient to perform tensile tests on AB and PB. Hence, we proposed a microstructural model-based approach to predict the material properties of AB and PB from the test results of WL. Such obtained modulus values of AB and PB had an error of 2% and 0.3%, respectively, compared with those measured from the tests. This approach can reduce the experimental cost for acquiring the needed mechanical property data for simulations.

On a Model of an Elastic Body Fully Immersed in a Viscous Incompressible Fluid with Small Data

On a Model of an Elastic Body Fully Immersed in a Viscous Incompressible Fluid with Small Data

A novel low trigger voltage low leakage SCR for low-voltage ESD protection

Reducing trigger voltage has always been a research hotspot in low-voltage electrostatic discharge (ESD) protection applications for integrated circuit. Thus, a novel low trigger voltage low leakage silicon-controlled rectifier (LTVLLSCR) for low-voltage ESD protection has been proposed. The proposed device uses a PMOS connected with the SCR to reduce the trigger voltage and the PMOS gate can be applied with the supply voltage to further reduce the trigger voltage and the leakage current. The operating principle and the physical mechanism of the proposed device were discussed by the Human Body Model simulation. The ESD characteristics of the proposed device were verified in 55 nm CMOS process. The experimental results demonstrate that the trigger voltage of the proposed device can reach a minimum of 2.86 V with an external bias, and the leakage current at 25 °C is about 1 nA which can be reduced by 13% with an external bias. With lower trigger voltage, lower leakage, smaller ESD design window and good ESD robustness, the LTVLLSCR is very suitable for 1 V low voltage applications.

Predicting occupant head displacements in evasive maneuvers; tuning and comparison of a rotational based and a translational based neck muscle controller.

Objective: Real-life car crashes are often preceded by an evasive maneuver, which can alter the occupant posture and muscle state. To simulate the occupant response in such maneuvers, human body models (HBMs) with active muscles have been developed. The aim of this study was to implement an omni-directional rotational head-neck muscle controller in the SAFER HBM and compare the bio-fidelity of the HBM with a rotational controller to the HBM with a translational controller, in simulations of evasive maneuvers. Methods: The rotational controller was developed using an axis-angle representation of head rotations, with x, y, and z components in the axis. Muscle load sharing was based on rotational direction in the simulation and muscle activity recorded in three volunteer experiments in these directions. The gains of the rotational and translational controller were tuned to minimize differences between translational and rotational head displacements of the HBM and volunteers in braking and lane change maneuvers using multi-objective optimizations. Bio-fidelity of the model with tuned controllers was evaluated objectively using CORrelation and Analysis (CORA). Results: The results indicated comparable performance for both controllers after tuning, with somewhat higher bio-fidelity for rotational kinematics with the translational controller. After tuning, good or excellent bio-fidelity was indicated for both controllers in the loading direction (forward in braking, and lateral in lane change), with CORA scores of 0.86-0.99 and 0.93-0.98 for the rotational and translational controllers, respectively. For rotational displacements, and translational displacements in the other directions, bio-fidelity ranged from poor to excellent, with slightly higher average CORA scores for the HBM with the translational controller in both braking and lane changing. Time-averaged muscle activity was within one standard deviation of time-averaged muscle activity from volunteers. Conclusion: Overall, the results show that when tuned, both the translational and rotational controllers can be used to predict the occupant response to an evasive maneuver, allowing for the inclusion of evasive maneuvers prior to a crash in evaluation of vehicle safety. The rotational controller shows potential in controlling omni-directional head displacements, but the translational controller outperformed the rotational controller. Thus, for now, the recommendation is to use the translational controller with tuned gains.