Search Results

Pulmonary contusion (PC) is the most common thoracic soft tissue injury following non-penetrating blunt trauma and has been associated with mortality rates as high as 25%. This study is part of an ongoing effort to develop finite element-based injury criteria for PC. The aims of this study are twofold. The first is to investigate the use of computed tomography (CT) to quantify the volume of pathologic lung tissue in a prospective study of PC. The second is to use a finite element model (FEM) of the lung to investigate several mathematical predictors of contusion to determine the injury metric that best matches the spatial distribution of contusion obtained from the CT analysis. PC is induced in-situ utilizing male Sprague Dawley rats (n = 24) through direct impact to the right lung at 5.0 m•s-1. Force versus deflection data are collected and used for model validation and optimization. CT scans are taken at 24 hours, 48 hours, 1 week, and 1 month postcontusion.

This study outlines a protocol for image data collection acquired from human volunteers. The data set will serve as the foundation of a consolidated effort to develop the next generation full-body Finite Element Analysis (FEA) models for injury prediction and prevention. The geometry of these models will be based off the anatomy of four individuals meeting extensive prescreening requirements and representing the 5th and 50th percentile female, and the 50th and 95th percentile male. Target values for anthropometry are determined by literature sources. Because of the relative strengths of various modalities commonly in use today in the clinical and engineering worlds, a multi-modality approach is outlined. This approach involves the use of Computed Tomography (CT), upright and closed-bore Magnetic Resonance Imaging (MRI), and external anthropometric measurements.

The reach capability of drivers is currently represented in vehicle design practice in two ways. The SAE Recommended Practice J287 presents maximum reach capability surfaces for selected percentiles of a generic driving population. Driver reach is also simulated using digital human figure models. In typical applications, a family of figure models that span a large range of the target driver population with respect to body dimensions is positioned within a digital mockup of the driver's workstation. The articulated segments of the figure model are exercised to simulate reaching motions and driver capabilities are calculated from the constraints of the kinematic model. Both of these current methods for representing driver reach are substantially limited. The J287 surfaces are not configurable for population characteristics, do not provide the user with the ability to adjust accommodation percentiles, and do not provide any guidance on the difficulty of reaches that are attainable.

Over 2.4 million eye injuries occur each year in the US, with over 30,000 patients left blind as a result of the trauma. The majority of these injuries occur in automobile crashes, military operations and sporting activities. This paper presents a nonlinear finite element model of the eye and the results of 22 experiments using human eyes to validate for globe rupture injury prediction. The model of the human eye consists of the cornea, sclera, lens, ciliary body, zonules, aqueous humor and vitreous body. Lagrangian membrane elements are used for the cornea and sclera, Lagrangian bricks for the lens, ciliary, and zonules, and Eulerian brick elements comprise the aqueous and vitreous. Nonlinear, isotropic material properties of the sclera and cornea were gathered from uniaxial tensile strip tests performed up to rupture. Dynamic modeling was performed using LS-Dyna.

Cyclical stepping (gait) has been studied extensively. Some of these results are reflected in the straight and curved path step-following algorithms in commercial digital human modeling (DHM) implementations. With the aid of these algorithms, DHM users define start, intermediate, and end path points and the software generates a walking-like motion along the path. Most of these algorithms have substantial limitations, among them that the figures exhibit “foot skate,” meaning that the kinematic constraint of foot contact with the ground is not respected. Turning is accomplished by pivoting the entire figure, rather than through realistic lower-extremity motions. The simulation of the non-cyclical stepping motions accompanying manual material handling pickup and delivery tasks requires manual manikin manipulation. This paper proposes a paradigm for the simulation of stepping behavior in digital human models based on a model of foot placements and motions.

The ASPECT program was conducted to develop new Automotive Seat and Package Evaluation and Comparison Tools. This paper presents a summary of the objectives, methods, and results of the program. The primary goal of ASPECT was to create a new generation of the SAE J826 H-point machine. The new ASPECT manikin has an articulated torso linkage, revised seat contact contours, a new weighting scheme, and a simpler, more user-friendly installation procedure. The ASPECT manikin simultaneously measures the H-point location, seat cushion angle, seatback angle, and lumbar support prominence of a seat, and can be used to make measures of seat stiffness. In addition to the physical manikin, the ASPECT program developed new tools for computer-aided design (CAD) of vehicle interiors. The postures and positions of hundreds of vehicle occupants with a wide range of body size were measured in many different vehicle conditions.

A new approach to driver seat-position modeling is presented. The equations of the Seating Accommodation Model (SAM) separately predict parameters of the distributions of male and female fore/aft seat position in a given vehicle. These distributions are used together to predict specific percentiles of the combined male-and-female seat-position distribution. The effects of vehicle parameters-seat height, steering-wheel-to-accelerator pedal distance, seat-cushion angle, and transmission type-are reflected in the prediction of mean seat position. The mean and standard deviation of driver population stature are included in the prediction for the mean and standard deviation of the seat-position distribution, respectively. SAM represents a new, more flexible approach to predicting fore/aft seat-position distributions for any driver population in passenger vehicles. Model performance is good, even at percentiles in the tails of the distribution.

Industrial tasks performed by standing workers are among those most commonly simulated using digital human models. Workers often walk, turn, and take acyclic steps as they perform these tasks. Current h uman modeling tools lack the capability to simulate these whole body motions accurately. Most models simulate walking by replaying joint angle trajectories corresponding to a general gait pattern. Turning is simulated poorly if at all, and violations of kinematic constraints between the feet and ground are common. Moreover, current models do not accurately predict foot placement with respect to loads and other hand targets, diminishing the utility of the associated ergonomic analyses. A new approach to simulating stepping and walking in task-oriented activities is proposed. Foot placements and motions are predicted from operator and task characteristics using empirical models derived from laboratory data and validated using field data from an auto assembly plant.

The development of a new carrier route vehicle for the U.S. Postal Service began with the design of the vehicle interior from an operator-centered perspective. A task analysis of the postal worker while driving and while performing mail-handling operations guided the layout of the vehicle interior. The Jack™ human modeling software was used, along with SAE Recommended Practices and other tools, to create a vehicle environment that will accommodate a large percentage of the operator population. The challenges of designing for this unique work environment provided a good opportunity to evaluate the relative strengths and weaknesses of the available human factors tools, including the Jack™ digital human figure model. This paper describes the development of the vehicle interior, discusses some lessons learned, and concludes with recommendations for increased functionality and improved integration of vehicle interior design tools.

Human body finite element models (FEMs) are a valuable tool in the study of injury biomechanics. However, the traditional model development process can be time-consuming. Scaling and morphing an existing FEM is an attractive alternative for generating morphologically distinct models for further study. The objective of this work is to use a radial basis function to morph the Global Human Body Models Consortium (GHBMC) average male model (M50) to the body habitus of a 95th percentile male (M95) and to perform validation tests on the resulting model. The GHBMC M50 model (v. 4.3) was created using anthropometric and imaging data from a living subject representing a 50th percentile male. A similar dataset was collected from a 95th percentile male (22,067 total images) and was used in the morphing process. Homologous landmarks on the reference (M50) and target (M95) geometries, with the existing FE node locations (M50 model), were inputs to the morphing algorithm.

Most current applications of digital human figure models for ergonomic assessments of manual tasks focus on the analysis of a static posture. Tools available for static analysis include joint-specific strength, calculation of joint moments, balance maintenance capability, and low-back compression or shear force estimates. Yet, for many tasks, the inertial loads due to acceleration of body segments or external objects may contribute significantly to internal body forces and tissue stresses. Due to the complexity of incorporating the dynamics of motion into analysis, most commercial software packages used for ergonomic assessment do not have the capacity to include dynamic effects. Thus, commercial human modeling packages rarely provide an opportunity for the user to determine if a static analysis is sufficient.

Assessments of reach capability using human figure models are commonly performed by exercising each joint of a kinematic chain, terminating in the hand, through the associated ranges of motion. The result is a reach envelope determined entirely by the segment lengths, joint degrees of freedom, and joint ranges of motion. In this paper, the validity of this approach is assessed by comparing the reach envelopes obtained by this method to those obtained in a laboratory study of men and women. Figures were created in the Jack human modeling software to represent the kinematic linkages of participants in the laboratory study. Maximum reach was predicted using the software's kinematic reach-envelope generation methods and by interactive manipulation. Predictions were compared to maximum reach envelopes obtained experimentally. The findings indicate that several changes to the normal procedures for obtaining maximum reach envelopes for seated tasks are needed.

A new method of predicting automobile occupant posture is presented. The Cascade Prediction Model approach combines multiple independent predictions of key postural degrees of freedom with inverse kinematics guided by data-based heuristics. The new model, based on posture data collected in laboratory mockups and validated using data from actual vehicles, produces accurate posture predictions for a wide range of passenger car interior geometries. Inputs to the model include vehicle package dimensions, seat characteristics, and occupant anthropometry. The Cascade Prediction Model was developed to provide accurate posture prediction for use with any human CAD model, and is applicable to many vehicle design and safety assessment applications.

In the mid 1970s, UMTRI investigated the biomechanical properties of the head and neck using 180 “normal” adult subjects selected to fill eighteen subject groups based on age (young, mid-aged, older), gender, and stature (short, medium, and tall by gender). Lateral-view radiographs of the subjects’ cervical spines and heads were taken with the subjects seated in a simulated automotive neutral posture, as well as with their necks in full-voluntary flexion and full-voluntary extension. Although the cervical spine and lower head geometry were previously measured manually and documented, new technologies have enabled computer digitization of the scanned x-ray images and a more comprehensive and detailed analysis of the variation in cervical spine and lower head geometry with subject age, stature, and gender. After scanning the radiographic images, 108 skeletal landmarks on the cervical vertebrae and 10 head landmarks were digitized.

Development and validation of crash test dummies and computational models that are capable of predicting the risk of injury to all parts of the knee-thigh-hip (KTH) complex in frontal impact requires knowledge of the force transmitted from the knee to the hip under knee impact loading. To provide this information, the knee impact responses of whole and segmented cadavers were measured over a wide range of knee loading conditions. These data were used to develop and help validate a computational model, which was used to estimate force transmitted to the cadaver hip. Approximately 250 tests were conducted using five unembalmed midsize male cadavers. In these tests, the knees were symmetrically impacted with a 255-kg padded impactor using three combinations of knee-impactor padding and velocity that spanned the range of knee loading conditions produced in FMVSS 208 and NCAP tests. Each subject was tested in four conditions.

Reliable, accurate data on vehicle occupant characteristics could be used to personalize the occupant experience, potentially improving both satisfaction and safety. Recent improvements in 3D camera technology and increased use of cameras in vehicles offer the capability to effectively capture data on vehicle occupant characteristics, including size, shape, posture, and position. In previous work, the body dimensions of standing individuals were reliably estimated by fitting a statistical body shape model (SBSM) to data from a consumer-grade depth camera (Microsoft Kinect). In the current study, the methodology was extended to consider seated vehicle occupants. The SBSM used in this work was developed using laser scan data gathered from 147 children with stature ranging from 100 to 160 cm and BMI from 12 to 27 kg/m2 in various sitting postures.

Recent research in the ASPECT (Automotive Seat and Package Evaluation and Comparison Tools) program has led to the development of a new method for automobile driver posture prediction, known as the Cascade Model. The Cascade Model uses a sequential series of regression functions and inverse kinematics to predict automobile occupant posture. This paper presents an alternative method for driver posture prediction using data-guided kinematic optimization. The within-subject conditional distributions of joint angles are used to infer the internal cost functions that guide tradeoffs between joints in adapting to different vehicle configurations. The predictions from the two models are compared to in-vehicle driving postures.

This paper presents the results of dynamic material tests and computational modelling that elucidate the effects of regional rib mechanical properties on thoracic fracture patterns. First, a total of 80 experiments were performed using small cortical bone samples from 23 separate locations on the rib cages of four cadavers (2 male, 2 female). Each specimen was subjected to dynamic three-point bending resulting in an average strain rate of 5 ± 1.5 strain/s. Test coupon modelling was used to verify the test setup. Regional variation was defined by location as anterior, lateral, or posterior as well as by rib level 1 through 12. The specimen stiffness and ultimate stress and strain were analyzed by location and rib level. Second, these material properties were incorporated into a human body computational model. The rib cage was partitioned into anterior, lateral, and posterior segments and the material properties were varied by location using an elastic-plastic material model.

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test.

Pulmonary contusion is the most commonly identified thoracic soft tissue injury in an automobile crash and after blunt chest trauma and affects 10-17% of all trauma admissions. The mortality associated with pulmonary contusions is significant and is estimated to be 10-25%. Thus, there is a need to develop a finite element model based injury metric for pulmonary contusion for the purpose of predicting outcome. This will enable current and future finite element models of the lung to incorporate an understanding of how stress and strain may be related to contusion injuries. This study utilizes 14 impacts onto male Sprague-Dawley rats. In 5 of these tests, a calibrated weight (46 g) is dropped from a height of 44 cm directly onto the lungs of intubated, anesthetized rats in situ. Contused volume is estimated from MicroPET scans of the lung and normalized on the basis of liver uptake of 18F-FDG.