Biomechanical Human Model Research Articles

Impact responses and injury analyses of a three-year-old occupant seating in forward and rearward facing CRSs using different computational models

To investigate the reliability and necessity of utilising a human biomechanical model in automotive safety, the frontal collision simulation test was conducted employing the TUST IBMs 3YO model and the Q3 dummy model. The kinematic and biomechanical injury parameters of the occupants were comparatively analysed. The results indicate consistent trends in acceleration changes between the two computational models. Variations in neck structure resulted in a 25% to 28% difference in the peak values of neck injury parameters. Differences in spine structure and materials made the spine angle change trends of the Q3 model more sensitive to the type of child restraint system (CRS). The human biomechanical model allows for the evaluation of occupant injury risk from multiple perspectives. Therefore, employing an advanced computational model of the human body with higher biofidelity provides a more reliable and effective method for investigating injury mechanisms and developing protective countermeasures for child occupants.

Development of a Biomechanical Human Model for Safety Analysis of the Operators of Self-Propelled Mining Machines

Development of a Biomechanical Human Model for Safety Analysis of the Operators of Self-Propelled Mining Machines

The Effectiveness of Swiveling Seats in Protecting Reclined Occupants in Highly Autonomous Driving Environments during Frontal Crashes

High-tilt reclined seats are one of the most popular configurations in highly automated vehicles; however, current restraint systems cannot protect out-of-position occupants in this type of seat. To reduce the risk of injury to reclined occupants, this study proposes a swiveling seat driven by occupant inertia and rotated in the sagittal plane during impact. The effectiveness of the swiveling seat was evaluated based on kinematics and injury to a human biomechanical model in a frontal sled test. A simulation matrix was constructed to design and optimize various safety devices, including the belt, pre-tensioner, knee constraint, and rotation stiffness for the swiveling seat. The results showed that (1) submarining occurred when the reclined occupant was on a fixed seat with a normal three-point belt during impact; (2) a fixed seat with a dynamic locking tongue and passenger lap pretension prevented the submarining, but produced a high lumbar force of 5359 N, which was higher than the spine injury criterion; and (3) the proposed swiveling seat with a matched restraint system could prevent submarining and produce lumbar force of 1787 N. The results demonstrated that the swiveling seat has high potential for occupant protection in intelligent driving scenarios.

Simulating human walking: a model-based reinforcement learning approach with musculoskeletal modeling.

Recent advancements in reinforcement learning algorithms have accelerated the development of control models with high-dimensional inputs and outputs that can reproduce human movement. However, the produced motion tends to be less human-like if algorithms do not involve a biomechanical human model that accounts for skeletal and muscle-tendon properties and geometry. In this study, we have integrated a reinforcement learning algorithm and a musculoskeletal model including trunk, pelvis, and leg segments to develop control modes that drive the model to walk. We simulated human walking first without imposing target walking speed, in which the model was allowed to settle on a stable walking speed itself, which was 1.45 m/s. A range of other speeds were imposed for the simulation based on the previous self-developed walking speed. All simulations were generated by solving the Markov decision process problem with covariance matrix adaptation evolution strategy, without any reference motion data. Simulated hip and knee kinematics agreed well with those in experimental observations, but ankle kinematics were less well-predicted. We finally demonstrated that our reinforcement learning framework also has the potential to model and predict pathological gait that can result from muscle weakness.

Multi-segment, spatial biomechanical model of a human body

This paper presents issues related to selected human biomechanical models that have been and are being used to analyze human body motion, human interaction with the environment, vehicles, machines. The process of building a multi-segment human biomechanical model in Matlab-Simmechanics environment was presented. Anthropometric parameters of real human segments are introduced in the model. The selected exemplary movements that a human can perform, are presented using model. Results of simulations performed to obtain selected kinematic and dynamic data associated with these movements are shown. They indicate the tremendous analytical potential of these kind of models in various scientific aspects such as medicine, sports, and technology.

A study of biomechanical model of seated human body exposed to vertical vibrations

This paper presents a human biomechanical model with 4 degrees of freedom of a human body in a car seat with backrest exposed to vertical vibrations. The proposed model has been analysed for five various values of radian frequency as numerical input data, and the results were compared with the results obtained for similar models in the published literature. In the biodynamic analyses the model was simplified to linear system to reduce the complexity of analytical and numerical simulations.

Neuro-fuzzy control of sit-to-stand motion using head position tracking

Based on the clinical evidence that head position measured by the multisensory system contributes to motion control, this study suggests a biomechanical human-central nervous system modeling and control framework for sit-to-stand motion synthesis. Motivated by the evidence for a task-oriented encoding of motion by the central nervous system, we propose a framework to synthesize and control sit-to-stand motion using only head position trajectory in the high-level-task-control environment. First, we design a generalized analytical framework comprising a human biomechanical model and an adaptive neuro-fuzzy inference system to emulate central nervous system. We introduce task-space training algorithm for adaptive neuro-fuzzy inference system training. The adaptive neuro-fuzzy inference system controller is optimized in the number of membership functions and training cycles to avoid over-fitting. Next, we develop custom human models based on anthropometric data of real subjects. Using the weighting coefficient method, we estimate body segment parameter. The subject-specific body segment parameter values are used (1) to scale human model for real subjects and (2) in task-space training to train custom adaptive neuro-fuzzy inference system controllers. To validate our modeling and control scheme, we perform extensive motion capture experiments of sit-to-stand transfer by real subjects. We compare the synthesized and experimental motions using kinematic analyses. Our analytical modeling-control scheme proves to be scalable to real subjects’ body segment parameter and the task-space training algorithm provides a means to customize adaptive neuro-fuzzy inference system efficiently. The customized adaptive neuro-fuzzy inference system gives 68%–98% improvement over general adaptive neuro-fuzzy inference system. This study has a broader scope in the fields of rehabilitation, humanoid robotics, and virtual characters’ motion planning based on high-level-task-control scheme.

Study on Passenger Comfort Based on Human–Bus–Road Coupled Vibration

Nowadays, the comfort of drivers and passengers is drawing more and more attention. The interaction between vehicles and the asphalt road can cause coupled vibration and reduce the comfort of passengers. Therefore, the research on human–vehicle–road coupled vibration and the comfort of passengers is of great importance. In this paper, the three-dimensional human–bus–road coupled vibration system is established, including the bus model, the parallel biomechanical human model with 2 degrees-of-freedom (DOF), and road surface roughness condition. The proposed coupled model was then used to study the dynamic response of the system and the comfort evaluation of the human body. In the comfort evaluation, the annoyance rate based method was proposed to consider the randomness of passenger vibration, the difference of the psychosensory vibration, and the fuzziness of evaluation indicators. Compared to the fuzzy evaluation based on the ISO 2631 standard, the proposed annoyance rate based method gives a quantitative evaluation of human comfort. Not only the degree of comfort can be evaluated, but the percentage of people feeling uncomfortable can also be obtained. Finally, parametric studies were conducted to investigate the effects of road surface roughness, interlayer bonding condition, bus weight, bus speed, and sitting position. It is found that the road surface roughness has the most significant effect on human comfort.

Using Wearable Sensors to Capture Posture of the Human Lumbar Spine in Competitive Swimming

Motion capture based on wearable inertial sensors is a promising technique for swimmers' training. To apply motion capture techniques properly, a swimming motion evaluation method based on inertial motion capture technology is proposed. Our proposed method uses a multisensor data fusion algorithm for swimmers’ attitude estimation, and the swimming posture is reconstructed in combination with a human biomechanical model. Furthermore, a comparative experiment between our proposed motion capture system and the NDI motion tracking system shows that our system performs reliably and accurately, and the estimation errors are well controlled. In addition, the accuracy of the orientation estimation algorithm ranges from $\text{1.65}^{\circ }$ to $\text{3.66}^{\circ }$ . The system can capture swimmers’ lumbar spine in four competitive swimming styles. A kinematic analysis of lumbar spine movement indicates that the patterns of swimmers’ lumbar spine movement can be used to evaluate training performance and provide quantitative data for swimmers.

Dynamic reaction of a human on vibrations by analysis of a single-dimensional biomechanical model

The article presents the concepts of the assessment of harmfulness of vibrations generated from various sources. Domestic and foreign standard procedures were discussed, including ISO proposals. It has been pointed out that all procedures can be considered as indirect ones, that they refer to vibrations affecting humans, and not those resulting from the dynamic response induced in individual human organs. The same applies to the criteria for determining the loss of life in communication collisions. It was pointed out that in the literature we find attempts of a direct approach, the essence of which is to study the dynamic reaction of individual human organs inscribed in the one or twodimensional model. The results of own tests of a person subjected to intensive oscillatory procedures were presented in order to identify the stiffness model proposed to assess the harmfulness of industrial type vibrations. It has been shown that two-dimensional models can be suitable here. Keywords: harmful effect of vibrations, human biomechanical models, one-dimensional model C.M. Harris, model identification, differential solution.

Directional and sectional ride comfort estimation using an integrated human biomechanical-seat foam model

In the methodology of objective measurement of ride comfort, application of a Human Biomechanical Model (HBM) is valuable for Whole Body Vibration (WBV) analysis. In this study, using a computational Multibody System (MBS) approach, development of a 3D passive HBM for a seated human is considered. For this purpose, the existing MBS-based HBMs of seated human are briefly reviewed first. The Equations of Motion (EoM) for the proposed model are then obtained and the simulation results are shown and compared with idealised ranges of experimental results suggested in the literature. The human-seat interaction is established using a nonlinear vibration model of foam with respect to the sectional behaviour of the seat foam. The developed system is then used for ride comfort estimation offered by a ride dynamic model. The effects of human weight, road class, and vehicle speed on the vibration of the human body segments in different directions are studied. It is shown that the there is a high correlation (more than 99.2%) between the vibration indices of the proposed HBM-foam model and the corresponding ISO 2631 WBV indices. In addition, relevant ISO 2631 indices that show a high correlation with the directional vibration of the head are identified.

Predictive model of the prostate motion in the context of radiotherapy: A biomechanical approach relying on urodynamic data and mechanical testing

In this paper, a biomechanical approach relying on urodynamic data and mechanical tests is proposed for an accurate prediction of the motion of the pelvic organs in the context of the prostate radiotherapy. As a first step, an experimental protocol is elaborated to characterize the mechanical properties of the bladder and rectum wall tissues; uniaxial tensile tests are performed on porcine substrates.In a second step, the parameters of Ogden-type hyperelastic constitutive models are identified; their relevance in the context of the implementation of a human biomechanical model is verified by means of preliminary Finite Elements (FE) simulations against human urodynamic data.In a third step, the identified constitutive equations are employed for the simulations of the motion and interactions of the pelvic organs due to concomitant changes of the distension volumes of the urinary bladder and rectum. The effectiveness of the developed biomechanical model is demonstrated in investigating the motion of the bladder, rectum and prostate organs; the results in terms of displacements are shown to be in good agreement with measurements inherent to a deceased person, with a relative error close to 6%.

Development of a human biomechanical model and its application in vehicle safety

The invention of automobiles has brought great progress and convenience to mankind. However, There are enormous personnel casualties and economic loss arising from traffic accidents every year. In this paper, CT (computed tomography) and MRI (magnetic resonance imaging) image of the human skeleton and internal organs were used to construct the three-dimensional human body finite element biomechanical model. The mechanical properties of the biological tissues in this model were based on test data found in the literature. The model was validated against cadaver responses to frontal and side impact. The predicted model response and injuries reasonably agreed with the experimental data. Simulation study on the collision between steering wheel and chest was performed, and the biomechanical response and the deformation pattern of the human body was obtained, from which the rib fracture and visceral injury mechanism can be reconstructed. The predicted model response reasonably agreed with that the thoracic injury in real-world crashes, and the model can further be used to evaluate thoracic injury in real-world crashes.

Development and validation of a human biomechanical model for rib fracture and thorax injuries in blunt impact

From 1990 to approximately 50,000–120,000 people die annually of road traffic accidents in China. Traffic accidents are the main cause of death of Chinese adults aged 15–45 years. This study aimed to determine the biomechanical response and injury tolerance of the human body in traffic accidents. The subject was a 35-year-old male with a height of 170 cm, weight of 70 kg and Chinese characteristics at the 50th percentile. Geometry was generated by computed tomography and magnetic resonance imaging. A human-body biomechanical model was then developed. The model featured in great detail the main anatomical characteristics of skeletal tissues, soft tissues and internal organs, including the head, neck, shoulder, thoracic cage, abdomen, spine, pelvis, pleurae and lungs, heart, aorta, arms, legs, and other muscle tissues and skeletons. The material properties of all tissues in the human body model were obtained from the literature. Material properties were developed in the LS-DYNA code to simulate the mechanical behaviour of the biological tissues in the human body. The model was validated against cadaver responses to frontal and side impact. The predicted model response reasonably agreed with the experimental data, and the model can further be used to evaluate thoracic injury in real-world crashes. We believe that the transportation industry can use numerical models in the future to simultaneously reduce physical testing and improve automotive safety.

Biomechanical model-based displacement estimation in micro-sensor motion capture

In micro-sensor motion capture systems, the estimation of the body displacement in the global coordinate system remains a challenge due to lack of external references. This paper proposes a self-contained displacement estimation method based on a human biomechanical model to track the position of walking subjects in the global coordinate system without any additional supporting infrastructures. The proposed approach makes use of the biomechanics of the lower body segments and the assumption that during walking there is always at least one foot in contact with the ground. The ground contact joint is detected based on walking gait characteristics and used as the external references of the human body. The relative positions of the other joints are obtained from hierarchical transformations based on the biomechanical model. Anatomical constraints are proposed to apply to some specific joints of the lower body to further improve the accuracy of the algorithm. Performance of the proposed algorithm is compared with an optical motion capture system. The method is also demonstrated in outdoor and indoor long distance walking scenarios. The experimental results demonstrate clearly that the biomechanical model improves the displacement accuracy within the proposed framework.

Generating Real-Time Responsive Balance Recovery Animation

We propose a novel Biomechanics-based Responsive Balance Recovery (BRBR) technique for synthesizing realistic balance recovery animations. First, our BRBR technique is based on a simplified human biomechanical model of keeping balance, so as to interactively respond to contact forces in the environment. Then, we employ the Principal Component Analysis (PCA) to reduce the dimensions of the mocap (motion capture) database to ensure the search for the most qualified return-to segment in real-time. Finally, empirical results from three cases validate the approach.

Human Movement Reconstruction from Video Shot by a Single Stationary Camera

One of the key techniques in the research of human motion analysis is the reconstruction of human spatial motion, which utilizes the anatomic points positions that can uniquely define the position and orientation of all anatomical segments. In this paper, upon the basis of Direct Linear Transform (DLT) and a human biomechanical model, the method to reconstruct human motion from an image sequence shot by a single stationary camera was described. In this method, the Lagrange Multiplier Method was used to minimize the difference between the actual and reconstructed length of limbs. This approach here is more comprehensive than previous methods that utilized cost functions to select results from feasible solutions. To examine this method, a practical human motion measured by a motion analysis system was selected and reconstructed. The spatial positions of joints were predicted with an average R2 of 0.9722 and mean residual error of 0.0022 m. This approach presented here provides a simple way to reconstruct the human spatial motion only utilizing a single camera.

A 3D Biomechanical Human Model for Numerical Simulation of Garment–Body Dynamic Mechanical Interactions During Wear

This paper presents a 3-dimensional biomechanical model of human body that consists of three layers different mechanical properties, namely the skin, soft tissue and bone. Based on the theory of contact mechanics and analyzing the contact characteristics between the deformable human body and a garment, we simulate the dynamic mechanical interactions between the two by considering the garment as an elastic shell with large deformation. The contact between human body and garment is modeled as a dynamic sliding interface. A finite element method is used in the time domain for deriving a numerical solution of the dynamic contact problem. Using a numerical computing method, we can compute the 3D distribution of the pressure, stress and deformation in the garment and the human body, and visualize them in color contour plots. We implement the numerical computation of the model by using commercial finite element software on a Pentium III PC computer with an example of wearing tight-fitting trousers from foot to waist. The predicted pressure is close to the magnitude of the measurements from subjective evaluation experiments of garment pressure, indicating that the model is able to predict and simulate garment pressure during wear with reasonable accuracy. The numerical computational results show that the model can provide a comprehensive description of the mechanical interactions involved in the contact interface such as garment deformation, garment pressure, human body deformation and inner pressure of the skin due to its deformation.

Owas Revised: Biomechanical Calculations and time Aspects of Loading

A 3-D biomechanical human model using OWAS codes of working postures as input was developed. The output gives biomechanical load on the shoulder and low back as a function of time. This new approach enables the simple postural observations to be analyzed in a biomechanical way with concerning the different body parts simultaneously in sequential time.

Hazardous waste worker education: Long term effects : T. H. McQuiston, P. Coleman, N. B. Wallerstein, A. C. Marcus, J. S. Morawetz & D. W. Ortlieb, Journal of Occupational Medicine, 36(12), 1310–1323

In the methodology of objective measurement of ride comfort, application of a Human Biomechanical Model (HBM) is valuable for Whole Body Vibration (WBV) analysis. In this study, using a computational Multibody System (MBS) approach, development of a 3D passive HBM for a seated human is considered. For this purpose, the existing MBS-based HBMs of seated human are briefly reviewed first. The Equations of Motion (EoM) for the proposed model are then obtained and the simulation results are shown and compared with idealised ranges of experimental results suggested in the literature. The human-seat interaction is established using a nonlinear vibration model of foam with respect to the sectional behaviour of the seat foam. The developed system is then used for ride comfort estimation offered by a ride dynamic model. The effects of human weight, road class, and vehicle speed on the vibration of the human body segments in different directions are studied. It is shown that the there is a high correlation (more than 99.2%) between the vibration indices of the proposed HBM-foam model and the corresponding ISO 2631 WBV indices. In addition, relevant ISO 2631 indices that show a high correlation with the directional vibration of the head are identified.