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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.

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.

Eight whole fresh-frozen cadavers (6 female, 2 male) that were elderly and/or female were laterally impacted using UMTRI's dual-sled side-impact test facility. Cadavers were not excluded on the basis of old age or bone diseases that affect tolerance. A thinly padded, multi-segment impactor was used that independently measured force histories applied to the shoulder, thorax, abdomen, greater trochanter, iliac wing, and femur of each PMHS. Impactor plates were adjusted vertically and laterally toward the subject so that contact with body regions occurred simultaneously and so that each segment contacted the same region on every subject. This configuration minimized the effects of body shape on load sharing between regions. Prior to all tests, cadavers were CT scanned to check for pre-existing skeletal injuries. Cadavers were excluded if they had pre-existing rib fractures or had undergone CPR.

Lateral impact tests were performed using seven male post-mortem human subjects (PMHS) to characterize the force-deflection response of contacted body regions, including the lower abdomen. All tests were performed using a dual-sled, side-impact test facility. A segmented impactor was mounted on a sled that was pneumatically accelerated into a second, initially stationary sled on which a subject was seated facing perpendicular to the direction of impact. Positions of impactor segments were adjusted for each subject so that forces applied to different anatomic regions, including thorax, abdomen, greater trochanter, iliac wing, and thigh, could be independently measured on each PMHS. The impactor contact surfaces were located in the same vertical plane, except that the abdomen plate was offset 5.1 cm towards the subject.

Seat comfort is driven in part by the fit between the sitter and seat. Traditional anthropometric data provide little information about the size and shape of the torso that can be used for backrest design. This study introduces a methodology for using three-dimensional computer models of the human torso based on a statistical analysis of body shapes for conducting automated fit assessments. Surface scan data from 296 men and 417 women in a seated posture were analyzed to create a body shape model that can be adjusted to a range of statures, body shape, and postures spanning those typical of vehicle occupants. Finite-element models of two auto seat surface were created, along with custom software that generates body models and postures them in the seat. A simple simulation technique was developed to rapidly assess the fit of the torso relative to the seat back.

Digital human models (DHM) are now widely used to assess worker tasks as part of manufacturing simulation. With current DHM software, the simulation engineer or ergonomist usually makes a manual estimate of the likely worker standing location with respect to the work task. In a small number of cases, the worker standing location is determined through physical testing with one or a few workers. Motion capture technology is sometimes used to aid in quantitative analysis of the resulting posture. Previous research has demonstrated the sensitivity of work task assessment using DHM to the accuracy of the posture prediction. This paper expands on that work by demonstrating the need for a method and model to accurately predict worker standing location. The effect of standing location on work task posture and the resulting assessment is documented through three case studies using the Siemens Jack DHM software.

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.

Contact between the knees and knee bolster commonly occurs in frontal collisions. The contact region on the bolster and the knee anatomy involved are related to the pre-crash positioning of the knees. The location of the distal (or infra-) patella was recorded on volunteers of widely varying stature after they had selected a comfortable driving position in mockups of three vehicles representing a large variation in size and shape: sedan, crossover SUV, and full-size pickup. On average, the right knees were grouped more tightly and were located more forward and lower than the left knees. On average, the knees were positioned 200 mm from the knee bolster for all subjects. The range of distance separating the distal patellae (within subject knee-to-knee distance) varied from 184–559 mm for all subjects for the three vehicles.

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.

Very little experimental research has focused on the kinematics, dynamics, and injuries of rear-seated occupants. This study seeks to develop a baseline response for rear-seated post mortem human surrogates (PMHS) in frontal crashes. Three PMHS sled tests were performed in a sled buck designed to represent the interior rear-seat compartment of a contemporary midsized sedan. All occupants were positioned in the right-rear passenger seat and subjected to simulated frontal crashes with an impact speed of 48 km/h. The subjects were restrained by a standard, rear seat, 3-point seat belt. The response of each subject was evaluated in terms of whole-body kinematics, dynamics, and injury. All the PMHS experienced excessive forward translation of the pelvis resulting in a backward rotation of the torso at the time of maximum forward excursion.

The ease of getting into and out of passenger cars and light trucks is a critical component of customer acceptance and product differentiation. In commercial vehicles, the health and safety of drivers is affected by the design of the steps and handholds they use to get into and out of the cab. Ingress/egress assessment appears to represent a substantial application opportunity for digital human models. The complexity of the design space and the range of possible biomechanical and subjective measures of interest mean that developing useful empirical models is difficult, requiring large-scale subject testing with physical mockups. Yet, ingress and egress motions are complex and strongly affected by the geometric constraints and driver attributes, posing substantial challenges in creating meaningful simulations using figure models.

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.

Digital human modeling has traditionally focused on the physical aspects of humans and the environments in which they operate. As the field moves towards modeling dynamic and more complex tasks, cognitive and perceptual aspects of the human's performance need to be considered. Cognitive modeling of complex tasks such as driving has commonly avoided the complexity of physical simulation of the human, distilling motor performance to motion execution times. To create a more powerful and flexible approach to the modeling of human/machine interaction, we have integrated a physical architecture of human motion (the Human Motion Simulation Ergonomics Framework—HUMOSIM) with a computational cognitive architecture (the Queueing network model human processor—QN–MHP). The new system combines the features of the two separate architectures and provides new capabilities that emerge from their integration.

The outcomes of crash tests can be influenced by the initial posture and position of the anthropomorphic test devices (ATDs) used to represent human occupants. In previous work, positioning procedures for ATDs representing adult drivers and rear-seat passengers have been developed through analysis of posture data from human volunteers. The present study applied the same methodology to the development of positioning procedures for ATDs representing six-year-old and ten-year-old children sitting on vehicle seats and belt-positioning boosters. Data from a recent study of 62 children with body mass from 18 to 45 kg were analyzed to quantify hip and head locations and pelvis and head angles for both sitter-selected and standardized postures. In the present study, the 6YO and 10YO Hybrid-III ATDs were installed using FMVSS 213 procedures in six test conditions used previously with children.

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.

The initial positioning of anthropomorphic test devices (ATDs) can influence the outcomes of crash tests. Current procedures for positioning ATDs in rear seats are not based on systematic studies of passenger postures. This paper compares the postures of three side-impact ATDs to the postures of 24 men and women in three vehicle rear seats and 16 laboratory conditions. When positioned using current procedures, the locations of the ES-2 and SID-HIII ATD heads are generally rearward of those observed with similar-size passengers. The SID-IIs head locations matched the expected locations of heads of passengers of similar size more closely. As the seat back angle was increased, people reclined less than the ATDs. Based on these findings, a new ATD positioning procedure for rear seats was developed. The primary objective of the new procedure is to place the ATD head in the location that is most likely for people of similar size.

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.