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The Human Motion Simulation Framework is a hierarchical set of algorithms for physical task simulation and analysis. The Framework is capable of simulating a wide range of tasks, including standing and seated reaches, walking and carrying objects, and vehicle ingress and egress. In this paper, model predictions for the terminal postures of standing object transfer tasks are compared to data from 20 subjects with a wide range of body dimensions. Whole body postures were recorded using optical motion capture for one-handed and two-handed object transfers to target destinations at three angles from straight ahead and three heights. The hand and foot locations from the data were input to the HUMOSIM Framework Reference Implementation (HFRI) in the Jack human modeling software. The whole-body postures predicted by the HFRI were compared to the measured postures using a set of measures selected for their importance to ergonomic analysis.

Posture and external loads such as hand forces have a dominant effect on ergonomic analysis outcomes. Yet, current digital human modeling tools used for proactive ergonomics analysis lack validated models for predicting postures for standing hand-force exertions. To address this need, the effects of hand magnitude and direction on whole-body posture for standing static hand-force exertion tasks were quantified in a motion-capture study of 19 men and women with widely varying body size. The objective of this work was to identify postural behaviors that might be incorporated into a posture-prediction algorithm for standing hand-force tasks. Analysis of one-handed exertions indicates that, when possible, people tend to align their bodies with the direction of force application, converting potential cross-body exertions into sagittal plane exertions. With respect to the hand-force plane, pelvis position is consistent with a postural objective of reducing rotational trunk torques.

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.

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 person's ability to perform a task is often limited by their ability to maintain balance. This is particularly true in lateral work performed in seated environments. For a truck driver operating the shift lever of a manual transmission, excessive shift forces can necessitate pulling on the steering wheel with the other hand to maintain balance, creating a potentially unsafe condition. An analysis of posture and balance in truck shifter operation was conducted using balance limits to define the acceptable range of shifter locations. The results are dependent on initial driver position, reach postures, and shoulder strength. The effects of shifter force direction and magnitude were explored to demonstrate the application of the analysis method. This methodology can readily be applied to other problems involving hand-force exertions in seated environments.

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.

For many industrial tasks (push, pull, lift, carry, etc.), restrictions on grip locations and visibility constrain the hand and head positions and help to define feasible postures. In contrast, foot locations are often minimally constrained and an ergonomics analyst can choose several different stances in selecting a posture to analyze. Also, because stance can be a critical determinant of a biomechanical assessment of the work posture, the lack of a valid method for placing the feet of a manikin with respect to the task compromises the accuracy of the analysis. To address this issue, foot locations and orientations were captured in a laboratory study of sagittal plane and asymmetric manual load transfers. A pilot study with four volunteers of varying anthropometry approached a load located on one of three shelves and transferred the load to one of six shelves.

In many task analyses using digital human figure models, only the terminal or apparently most stressful posture is analyzed. For reaches from a seated position, this is generally the posture with the hand or hands at the target. However, depending on the characteristics of the tasks and the people performing them, analyzing only the terminal posture could be misleading. This possibility was examined using data from a study of the reaching behavior of people with spinal cord injury. Participants performed two-handed forward reaching tasks. These reaches were to three targets located in the sagittal plane. The terminal postures did not differ significantly between those with spinal cord injury and those without. However, motion analysis demonstrated that they employed distinct strategies, particularly in the initial phase of motion.

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.

The SAE Controls Reach Study provided the opportunity to obtain a considerable amount of driver work space data in addition to hand and foot reach. A side-view film recording was made of each test subject assuming a driving attitude and looking straight ahead. Of concern were locations for the driver's eyes, top of head, back of head, knee, and seat. These data were combined with other data previously reported to develop tools that will aid the designer in describing space and comfort requirements for seated drivers and passengers in automotive packages. Fixed-seat eye ellipses, head locations, shin-knee locations, and preferred seat positions are described.