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Accurate representation of working postures is critical for ergonomic assessments with digital human models because posture has a dominant effect on analysis outcomes. Most current digital human modeling tools require manual manipulation of the digital human to simulate force-exertion postures or rely on optimization procedures that have not been validated. Automated posture prediction based on human data would improve the accuracy and repeatability of analyses. The effects of hand force location, magnitude, and direction on whole-body posture for standing tasks were quantified in a motion-capture study of 20 men and women with widely varying body size. A statistical analysis demonstrated that postural variables critical for the assessment of body loads can be predicted from the characteristics of the worker and task.

A PC based interactive program was developed to simulate the unfolding and deploying process of a driver side airbag in the sagittal plane. The airbag was represented by a series of nodes. The maximum allowable stretch was less or equal to one between any two nodes. We assumed that the airbag unfolding was pivoted about folded points. After the completion of the unfolding process the airbag would begin to deploy. During the deploying process, two parameters were used to determine the nodal priority of the inflation. The first parameter was the distance between the instantaneous and final positions of a node. Nodes with longer distances to travel will have to move faster. We also considered the distance between the current nodal position and the gas inlet location. For a node closer to the gas inlet, we assumed that the deploying speed was faster. A graphical procedure was used to calculate the area of the airbag.

Digital human modeling (DHM) progress worldwide will be much faster and cohesive if the diverse community now developing simulations has a global blueprint for DHM, and is able to work together efficiently. DHM developers and users can save time by building on each other's work. This paper highlights a panel discussion on DHM goals and strategic plans for the next decade to begin formulating the international blueprint. Four subjects are chosen as the starting points: (1) moving DHM into the public safety and internet arenas, (2) role of DHM in computer assisted surgery and automotive safety, (3) DHM in defense applications, and (4) DHM to improve workplace ergonomics.

This study identified the mechanical properties of ten cadaveric lumbar spines and two Hybrid III lumbar spines. Eight tests were performed on each specimen: tension, compression, anterior shear, posterior shear, left lateral shear, flexion, extension and left lateral bending. Each test was run at a displacement rate of 100 mm/sec. The maximum displacements were selected to approximate the loading range of a 50 km/h Hybrid III dummy sled test and to be non-destructive to the specimens. Load, linear displacement and angular displacement data were collected. Bending moment was calculated from force data. Each mode of loading demonstrated consistent characteristics. The load-displacement curves of the Hybrid III lumbar spine demonstrated an initial region of high stiffness followed by a region of constant stiffness.

A three-dimensional finite element model of a human neck has been developed in an effort to study the mechanics of cervical spine while subjected to impacts. The neck geometry was obtained from MRI scans of a 50th percentile male volunteer. This model, consisting of the vertebrae from C1 through T1 including the intervertebral discs and posterior elements, was constructed primarily of 8-node brick elements. The vertebrae were modeled using linear elastic-plastic materials, while the intervertebral discs were modeled using linear viscoelastic materials. Sliding interfaces were defined to simulate the motion of synovial facet joints. Anterior and posterior longitudinal ligaments, facet joint capsular ligaments, alar ligaments, transverse ligaments, and anterior and posterior atlanto-occipital membranes were modeled as nonlinear bar elements or as tension-only membrane elements. A previously developed head and brain model was also incorporated.

This study begins the exploration of the relationship between shoulder external moments and perceived exertion levels for submaximal delivery tasks. Twenty subjects were recorded while performing hand load movement tasks to specified targets. After each exertion, subjects were asked to rate the effort required to perform the task. The recorded motion profiles were processed using a biomechanical upper extremity model, from which resultant external shoulder moments were calculated. Average resultant shoulder moments, stratified by exertion level, were also calculated. Several individual subject moment/exertion profiles showed identifiable trends. It was demonstrated that while no strong relationships exist for individual task exertion effort prediction based on resultant shoulder moments, there is a general trend in the overall data sample, as is shown by a high correlation between mean integrated resultant shoulder moment by exertion level and exertion levels.

Simulation of human motions in virtual environments is an essential component of human CAD (Computer-aided Design) systems. In our earlier SAE papers, we introduced a novel motion simulation approach termed Memory-based Motion Simulation (MBMS). MBMS utilizes existing motion databases and predicts novel motions by modifying existing ‘root’ motions through the use of the motion modification algorithm. MBMS overcomes some limitations of existing motion simulation models, as 1) it simulates different types of motions on a single, unified framework, 2) it simulates motions based on alternative movement techniques, and 3) like real humans, it can learn new movement skills continually over time. The current study evaluates the prediction accuracy of MBMS to prove its utility as a predictive tool for computer-aided ergonomics. A total of 627 whole-body one-handed load transfer motions predicted by the algorithm are compared with actual human motions obtained in a motion capture experiment.

Workstation design is one of the most essential components of proactive ergonomics, and digital human models have gained increasing popularity in the analysis and design of current and future workstations (Chaffin 2001). Using digital human technology, it is possible to simulate interactions between humans and current or planned workstations, and conduct quantitative ergonomic analyses based on realistic human postures and motions. Motion capture has served as the primary means by which to acquire and visualize human motions in a digital environment. However, motion capture only provides motions for a specific person performing specific tasks. Albeit useful, at best this allows for the analysis of current or mocked-up workstations only. The ability to subsequently modify these motions is required to efficiently evaluate alternative design possibilities and thus improve design layouts.

Although biomechanics models can predict the stress on the musculoskeletal system, they cannot predict how the muscle load associated with exertion is perceived. The short-term goal of the present study was to model the perception of effort in lifting and reaching tasks. The long-term goal is to determine the correlation between objective and subjective measures of effort and use this information to predict fatigue or the risk of injury. Lifting and reaching tasks were performed in seated and standing situations. A cylindrical object and a box were moved with one hand and two hands, respectively, from a home location to shelves distributed in the space around the subject. The shoulder and torso effort required to perform these tasks were rated on a ten point visual analog scale.

Interference between physical objects in the workspace and the moving human body may cause serious problems, including errors in manual operation, physical damage and trauma from the collision, and increased biomechanical stresses due to movement reorganization for avoiding the obstacles. Therefore, a computer algorithm to detect possible collisions and simulate human motions to avoid obstacles will be an important tool for computer-aided ergonomics and optimization of system design in the early stage of a design process. In the present study, we present a method of modifying motions for obstacle avoidance when the object intrudes near the center of the planned motion. We take the motion modification approach, as we believe that for a certain class of obstacle avoidance problems, a person would modify a pre-planned motion that would result in a collision to a new one that is collision-free, as opposed to organizing a totally unique motion pattern.

Lower extremity injuries in frontal automotive crashes usually occur with footwell intrusion where both the knee and foot are constrained. In order to identify factors associated with tibial shaft injury, a series of numerical simulations were conducted using a finite element model of the whole human body. These simulations demonstrated that tibial mid-shaft injuries in frontal crashes could be caused by an abrupt change in velocity and a high rate of footwell intrusion.

A nonlinear foam was added to a previously created three-dimensional finite element model of the Hybrid III dummy chest which consisted of six steel ribs, rib damping material, the sternum, a spine box and a pendulum. Two standard calibration pendulum impact tests for a Hybrid III dummy chest were used to validate the new model. An explicit finite element analysis code PAM-CRASH was utilized to simulate the dynamic process. At impact velocities of 6.7 m/s and 4.3 m/s, the force and deflection time history as well as the force-deflection plots showed good agreement between model predictions and calibration data. Peak strains also agreed well with experimental data.

Auto racing has been in vogue from the time automobiles were first built. With the dawn of modern cars came higher engine capacities; the speeds involved in these races and crashes increased as well. However, the advent of passive restraint systems such as the helmet, HANS (Head and Neck Support device), multi-point harness system, roll cage, side and frontal crush zones, racing seats, fire retardant suits, and soft-wall technology, have greatly improved the survivability of the drivers in high-speed racing crashes. Three left lateral crashes from Begeman and Melvin (2002), Case #LAS12, #IND14 and #99TX were used as inputs to the Wayne State Human Body Model (WSHBM) in a simulated racing buck. Twelve simulations with delta-v, six-point harness and shoulder pad as design variables were analyzed for the average maximum principal strain (AMPS) in the aorta. The average AMPS for the high-speed crashes were 0.1551±0.0172 while the average maximum pressure was 110.50±4.25 kPa.

The potential of digital human modeling to improve the design of products and workspaces has been limited by the time-consuming manual manipulation of figures that is required to perform simulations. Moreover, the inaccuracies in posture and motion that result from manual procedures compromise the fidelity of the resulting analyses. This paper presents a new approach to the control of human figure models and the analysis of simulated tasks. The new methods are embodied in an algorithmic framework developed in the Human Motion Simulation (HUMOSIM) laboratory at the University of Michigan. The framework consists of an interconnected, hierarchical set of posture and motion modules that control aspects of human behavior, such as gaze or upper-extremity motion. Analysis modules, addressing issues such as shoulder stress and balance, are integrated into the framework.

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.

This paper describes and illustrates two different approaches used to predict population strength capabilities. One approach uses statistical regression models to predict maximum acceptable weight or force capabilities as a function of population attributes (e.g., anthropometry, gender and standardized strength scores). A second approach relies on a biomechanical concept stating that the maximum force one can produce in a given posture and for a given type of exertion is a function of the minimum relative strength produced by one's muscles at a particular joint. This latter approach has resulted in a specific static strength prediction model which has been implemented in software produced by the Center for Ergonomics at the University of Michigan. The software allows the simulation of a large variety of manual exertions. This paper describes the status of the two different approaches and implications and requirements for future human simulation and modeling systems.

A three-dimensional finite element model of the Hybrid III dummy head-neck complex was created to simulate the Amended Part 572 Head-Neck Pendulum Compliance Test, of the Code of Federal Regulations. The model consisted of a rigid head and five circular aluminum disks joined together by butyl elastomer rubber. Contact surfaces were defined to allow the anterior neck to separate upon an application of extension moments. Two mounting positions, one for flexion and the other one for extension, were used to simulate the head-neck calibration tests. An explicit finite element code PAM-CRASH was utilized to simulate the model dynamic responses. Simulation results were compared to experimental data obtained from First Technology Safety Systems Inc. Model predictions agreed well in both flexion and extension. This model can be used to study the head-neck biomechanics of the existing dummy as well as in the development of new dummies.

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.

Vehicle motions can adversely affect the ability of a driver or occupant to quickly and accurately push control buttons located in many advanced vehicle control, navigation and communications systems. A pilot study was conducted using the U.S. Army Tank Automotive and Armaments Command (TACOM) Ride Motion Simulator (RMS) to assess the effects of vertical ride motion on the kinematics of reaching. The RMS was programmed to produce 0.5 g and 0.8 g peak-to-peak sinusoidal inputs at the seat-sitter interface over a range of frequencies. Two participants performed seated reaching tasks to locations typical of in-vehicle controls under static conditions and with single-frequency inputs between 0 and 10 Hz. The participants also held terminal reach postures during 0.5 to 32 Hz sine sweeps. Reach kinematics were recorded using a 10-camera VICON motion capture system. The effects of vertical ride motion on movement time, accuracy, and subjective responses were assessed.

A research effort was initiated to establish an empirical data base and to develop predictive models of normal human in-vehicle seated reaching motions while driving. A driving simulator was built, in which a variety of targets were positioned at typical locations a driver would possibly reach. Reaching motions towards these targets were performed by demographically representative subjects and measured by a state-of-the-art motion analysis system. This paper describes the experiment conducted to collect the movement data, and the new techniques that are being developed to process, analyze, and model the data. Some initial findings regarding the role of torso assistive motion, the effect of speed used in completing a motion on multi-segment dynamic postures, and illustrative results from kinematic modeling are presented.