In the design process of products and production systems, the activity to systematically evaluate initial alternative design concepts is an important step. The digital human modeling (DHM) tools include several different types of assessment methods in order to evaluate product and production systems. Despite this, and due to the fact that a DHM tool in essence is a computer-supported design and analysis tool, none of the DHM tools provide the functionality to, in a systematic way, use the results generated in the DHM tool to compare design concepts between each other. The aim of this paper is to illustrate how a systematic concept evaluation method is integrated in a DHM tool, and to exemplify how it can be used to systematically assess design alternatives. Pugh´s method was integrated into the IPS software with LUA scripting to systematically compare design concepts. Four workstation layout concepts were generated by four engineers. The four concepts were systematically evaluated with two methods focusing on human well-being and two methods focusing on system performance and cost. The result is very promising. The demonstrator illustrates that it is possible to perform a systematic concept evaluation based on human well-being, overall system performance, and other parameters, where some of the data is automatically provided by the DHM tool and other data manually. The demonstrator can also be used to evaluate only one design concept, where it provides the software user and the decision maker with an objective and visible overview of the success of the design proposal from the perspective of several evaluation methods.
Human safety and sitting comfort in the car depend on a complex set of interactions between the human body, its clothing, and the automotive environment in the meaning of sit elements, belt, solid parts, and air. The design of any functional clothing requires elastic human body models, too, but the detailed FEM models for car crash simulations are unnecessarily accurate, computationally intensive, and not practicable for the clothing development process. For correct simulation of the mechanical interaction, full-scale FEM models of humans with enough suitable accuracy and complexity are required. This work presents the development steps and current state of an algorithm for automatic solid FEM mesh generator for human bodies, based on 3D scan data. The data from the 3D scanner is used for two purposes: (a) for detection of the main sizes of the bones of the human body and (b) the surface mesh is used as a basis for the building of the inner solid layers of the skin, inner soft structures, and the bones. The automatically created solid mesh can then be used for the evaluation of the mechanical interaction between the human body, its clothing, and the environment within commercial or open-source FEM software. The model does not accurately build the interaction within the human body (between bones, muscles, and skin), but allows evaluation of the mechanical interactions and the sitting comfort for different body types and sizes in significantly reduced time.
The ergonomic evaluation of several production tasks is still manual filling of evaluation sheets where the results might differ even with the same dataset. To improve this manual process, motion capture (MOCAP) systems, such as intrusive (inertial sensor-based) and non-intrusive (vision-based) systems, have been intensively tested over the years for precise data collection and analysis. This study combines the strengths of two different MOCAP systems, an AI-based vision system and an inertial sensor-based system, for the human motion posture evaluation on an automotive production use case. For the experiments, a few workstations were selected and used throughout. First, an AI-based vision system with multiple algorithms and cameras was evaluated. Second, inertial sensor-based systems were evaluated. Later, an AI-based vision system and an inertial sensor-based system were combined and evaluated. The results have shown that the AI-based vision system has provided better performance with a minimal number of cameras when combined with a few inertial sensors.
This paper presents an early-design methodology to quantify vision obstruction caused by halo-type cockpit safety equipment introduced into Formula One (F1) racing in 2018. The halo is a curved bar that surrounds the driver's head over the cockpit opening and offers additional protection to drivers. However, the halo's introduction has raised concerns over vision-obstruction-related issues due to its vertical and horizontal bars (pillar-like elements) sitting in front of the cockpit. This study assesses vision obstructions by exploring the driver's forward field of view based on the coverage zone analysis. This research utilizes digital manikins inserted in a digital F1 racecar mockup to assess the effects of halo concept variants on vision obstruction. The preliminary results showed that the vision obstruction was not only affected by the halo geometry and size but also the orientation of the F1 car in different racetrack segments. The methodology discussed in this study is critical for other early-stage product design and development challenges, where designers demand "quick-and-dirty" ergonomics evaluation of vision obstruction before building time-consuming and costly physical mockups.
Often new digital tools are introduced alongside existing tools and workflows to augment and fill gaps in current processes. Virtual and augmented reality (XR) tools are currently being deployed in this way within design processes, allowing for interactive visualization in virtual environments including the use of DHM tools. Currently, the focus is on how to implement XR as a stand-alone tool for single-user scenarios. However, in collaborative design contexts, screen-based and XR tools can be used together to leverage the benefits of each technology maximizing the potential of multi-user design processes. XR allows for an immersive exploration of designed objects in 3D space, while screen-based tools allow for easier notetaking and integration of additional non-3D software and meeting tools. Ensuring that these technologies are integrated in a mutually beneficial manner requires a framework for determining the best combination of technologies and interfaces for diverse design teams. This paper presents a framework for performing collaborative design reviews in a digital environment that can be accessed using both XR and 2D screen devices simultaneously. It enables asymmetric collaboration to provide each design team member with the technology that best fits their workflow and requirements.
Anthropometric data can be measured manually, through traditional methods, or obtained from a 3D body scan. In both cases, anthropometric dimensions are measured in a static posture (e.g. standing, sitting) however, people interact with products and environments in movement. Anthropometry applied to the ergonomic design of spaces (e.g. workplace, cockpits) includes measurements of reaches and considers dynamic anthropometry, that is the functional ranges of movements of the limbs. In the case of wearables, products that are worn in contact to the body (e.g. clothing, protective gear), the variability of the shape and dimensions during the moment is crucial information to achieve a good fitting, comfort and performance. The appearance of new 4D body scanning technology enables the generation of digital human models in movement which reproduce the actual body shape in motion. Anthropometry in movement is a new category of body metrics that can be obtained from a sequence of scans. In this paper, the variability of eight anthropometric dimensions (neck to waist length, back length, arm length, thigh girth, crotch length, arm girth, waist girth and hip girth) is analyzed in different movements. For this purpose, ten subjects, with a variety of morphotypes, have been measured performing different movements using a 4D scanning system. The methodology to process the sequence of body scans is described to obtain automatically anatomical references of the anthropometric measurements along the movement. The results presented show the evolution of the eight anthropometric dimensions during the movement for the different subjects and movements. The mean ranges of variation are also reported and can reach values between 2-14 cm that will be relevant information for wearable design. Anthropometric dimensions in movement is a new body metric that require further research to establish new protocols, better anthropometric definitions and the creation of new datasets.
Digital human models are usually constructed to study human anatomical or topological features and their variance and to optimize the size and shape of various products and tasks. Therefore, most of the researchers focused on developing accurate three-dimensional digital human models based on surface mesh using various methods and techniques. However, such models do not allow biomechanical and ergonomic analyses of product interface materials that are in direct contact with the user. Based on manual testing using various materials and analyzing the subjective response of users, researchers have shown that product interface material has an important impact on the overall product safety, comfort, and even performance. Basic ergonomic and biomechanical guidelines regarding the material choice were provided based on the findings; however, detailed material choice and even material parameter determination have not been studied, evaluated, and discussed due to the complex biomechanical systems and lack of appropriate digital human models. To overcome these limitations, numerical methods, especially the finite element method, have been used in the past by several authors. The finite element method allows calculating various results in terms of internal stresses and contact pressure, deformations, and displacements; however, it requires accurate development of numerical digital human models that accurately represent the anatomical, topological, and material properties, as well as boundary conditions. In this paper we present a theoretical background and provide a methodology for successful development of numerical digital human models that can be used for biomechanical analyses and product material ergonomic improvement. This is presented with a case study of the development of a numerical digital human finger model for ergonomic improvement of the biomechanical response of a product handle deformable interface material. Based on the developed numerical model, a novel deformable interface material is analyzed that reduces the resulting contact pressure during grasping and provides more uniform pressure distribution while still providing sufficient stability.
The US Army recently updated their fitness test from a historical three-task battery to a science-driven six-task battery called the Army Combat Fitness Test (ACFT). The Army chose the six events compared to the time required to complete a battery of commons soldier tasks (CSTs), thus targeting the time-domain aspect of physical requirements and capability. We aimed to critically evaluate the new ACFT using biomechanical analyses and digital human modeling to assess how well specific aspects of the ACFT tasks matched required joint torques to perform common soldier tasks. This paper will focus on one of the ACFT tasks, the dead lift. Five healthy ROTC students (three males, two females) completed simulated CSTs and the ACFT. All were instrumented with markers to use 3D motion analysis coupled with digital human modeling (DHM) using Santos® and Sophia® DHMs to estimate the muscle joint torque requirements (i.e., workloads) needed to complete each task. We assessed five major joints in the body: trunk (low-back extension and abdominal flexion), hip flexion/extension, knee flexion/extension, shoulder flexion/extension, and elbow flexion/extension. The ratio of peak torques needed to complete selective CSTs compared to the torque needed to complete the deadlift at the current passing score were modeled, where < 100% indicates the CSTs were less strenuous than the deadlift. We found examples of less, similar, and greater strength requirements across eight CSTs compared to the dead lift, including 150 – 200% higher torque requirements for select CSTs than the dead lift in some cases. For example, performing simulated casualty extractions required more torque at multiple joints. Overall, we concluded that the muscles involved in the ACFT dead lift often mimic those involved in one or more CSTs. Further, the absolute torques needed to complete the dead lift and simulated CSTs are not notably different between men and women.
Thanks to recent studies on the relationship between joint center locations, external body shape, and landmark positions, we can build a personalized kinematic human model in standing posture. It is, however, challenging to position it into a seated posture. This is particularly true for positioning the pelvis and spine due to the high number of degrees of freedom (DOF) involved and the very low number of anatomical landmarks available for palpation/motion capture. This is an under-determined problem. A priori knowledge is needed to find anatomically correct solutions. One way is to reduce the DOFs of the spine model by either not allowing all intervertebral joint rotate freely or introducing relationships between them. Earlier researchers reduced spinal DOFs from 51 to 5 by defining kinematic constraints and showed that a 5DOF-simplified model could produce smooth spine motions, while others used the relationships between spinal joint angles, called spinal coordination laws, to prevent unrealistic postures in motion reconstruction process. However, evidence-based statistical models are missing. The objective of this paper is to investigate the variation of spinal joint angles when changing posture and to identify spinal coordination laws.
A digital human modeling (DHM) software is a valuable tool in virtual manufacturing since it supports proactive consideration of ergonomics when designing new workstations by facilitating simulation of manual assembly work and by providing ergonomic assessments of different design proposals. Despite the advantage, there are still a lot of assembly tasks that are not simulated and assessed proactively. One reason is that it is time consuming for the user, even for simple tasks, to create and set up the assembly simulations. Increasing the automation level of DHM software has the potential to both increase the number of assembly task simulated as well as enable ergonomics to proactively be included in other manufacturing and product design related decisions. However, an increased automation level requires a manikin that can automatically compute collision-free and ergonomically sound motions based on some sort of instruction language that supports the DHM software user to communicate to the manikin which tasks the manikin is to perform. The instructions are, during simulation, interpreted by a simulation framework as path planning instances for the manikin, which results in motions that accomplish the tasks. In this work, we explore the possibility to use the DHM software IMMA’s instruction language to further increase the automation level and to identify gaps between the current functionality and the functional requirements for a more automated simulation framework. More specifically, we investigate the requirements for simulations where: (1) manikins perform collaborative tasks, such as when two manikins jointly handle an object, and where predicted motions are collision-free and ergonomically sound, and the forces needed to handle the object are distributed between both manikins; (2) robots and manikins collaborate when performing tasks; the simulation of such interaction needs to consider collisions, weight of carried objects, ergonomics of the manikin, as well as other automation equipment used in the assembly station; and (3) manikins interact with moving objects, e.g., during assembly of a part on a moving assembly line, or grasping a part that is moved by a collaborative robot.
To understand system performance, it is rational to consider all system components, including the humans involved in the control or maintenance of the system. Previous research has included human performance by modeling human tasks as events within Discrete Event Simulation (DES) models. These models typically represent the variability of task performance times and error rates by calculating the mean and variance across multiple individuals. Such approaches assume independence of task performance measures between individuals, but evidence exists which indicates that task performance measures are correlated between individuals. The current research seeks to understand methods to account for performance variability within DES models. A taxonomy of potential methods to address variability in DES models is developed and discussed. Among the findings derived through development of this taxonomy is the need to differentiate models of performance envelopes from models of average system performance and alternatives for modeling the human when predicting each class of performance.
DHM tools have been widely used to analyze and improve vehicle occupant packaging and interior design in the automotive industry. However, these tools still present some limitations for this application. Accurately characterizing seated posture is crucial for ergonomic and safety evaluations. Current human posture and motion predictions in DHM tools are not accurate enough for the precise nature of vehicle interior design, typically requiring manual adjustments from DHM users to get more accurate driving and passenger simulations. Manual adjustment processes can be time-consuming, tedious, and subjective, easily causing non-repeatable simulation results. These limitations create the need to validate the simulation results with real-world studies, which increases the cost and time in the vehicle development process. Working with multiple Swedish automotive companies, we have begun to identify and specify the limitations of DHM tools relating to driver and passenger posture predictions given predefined vehicle geometry points/coordinates and specific human body parts relationships. Two general issues frame the core limitations. First, human kinematic models used in DHM tools are based on biomechanics models that do not provide definitions of these models in relation to vehicle geometries. Second, vehicle designers follow standards and regulations to obtain key human reference points in seated occupant locations. However, these reference points can fail to capture the range of human variability. This paper describes the relationship between a seated reference point and a biomechanical hip joint for driving simulations. The lack of standardized connection between occupant packaging guidelines and the biomechanical knowledge of humans creates a limitation for ergonomics designers and DHM users. We assess previous studies addressing hip joint estimation from different fields to establish the key aspects that might affect the relationship between standard vehicle geometry points and the hip joint. Then we suggest a procedure for standardizing points in human models within DHM tools. A better understanding of this problem may contribute to achieving closer to reality driving posture simulations and facilitating communication of ergonomics requirements to the design team within the product development process.
Finite element models (FEM) of human body models (HBM) are used to analyze static seating discomfort mainly in terms of interface pressure distribution on the seat surface. However, most of the HBMs are not validated under actual seating conditions due to the difficulty of measuring internal body loads such as soft tissue deformation, intervertebral disc pressures, etc. The rare HBM-related studies claiming validation have only analyzed the interface pressure distribution. Recent experiments conducted with and without foam for different seat pan inclinations using open MRI indicate that soft tissue deformation below the ischial tuberosity (IT) is affected by both contact pressure and shear and thus could be an objective indicator in seat discomfort assessment. The aim of this present study is to report a preliminary evaluation of FE-HBMs against these subject-specific experimental data in terms of interface pressure and soft tissue deformation.
Dynamic modeling of body organs has become an elementary part of modern digital human modeling, where advanced biomedical models incorporate biomechanical behavior of tissues down to the cell level. While the biomechanical response of organs to impact and trauma has traditionally been considered an important aspect in developing safety-related models such as for vehicle crash simulation, organ behavior is now also reflected in models used for medical purposes, such as the simulation of breathing or cardiovascular circulation. All human body cells have in vivo nonlinear viscoelastic properties. Moreover, body tissue is composed of cells wrapped in an extracellular matrix (ECM). Body tissue in vivo nonlinear viscoelastic properties depend on its function in an organ system, which directly affects the tissue viscoelasticity modulus. For advanced perfusion or fluid passage simulation, we propose to represent the nonlinear viscoelastic behavior of the body tissue in a solid boundary condition using the moving deforming mesh (MDM) method. This shape modeling method can be used in segmentation to generate meshes of prescribed cell area. It considers how the viscoelastic perfusion wall transient fluid flow responds to the pressure pulse from human organ systems such as the lung or heart. The method also allows consideration of the change in the volume fraction of the ECM constituents, which may result from aging or disease such as cancer and lead to a changed viscous modulus (loss modulus) and elastic modulus (storage modulus) of organ tissue. In this study, we use the MDM method to examine two organ geometries from the respiratory and cardiovascular systems. Although the simulation effort using this method is more time-consuming, the simulation outcomes are expected to be in better accordance with the real organs when compared to simulation results using other computational fluid dynamics methods, where perfusion wall behavior is considered to be rigid. We propose that more accurate and personalized computational modeling will lead to predictive surgical planning, enabling an optimum choice of the most favorable reformative technique when considering specific patient conditions.
For planning and designing production and work systems, a holistic approach is necessary that considers both levels of factory planning and workplace design. Currently, separate digital tools are mostly used for the design of factories and the detailed planning of work systems. That leads to workers being considered inadequately or too late in the planning process of production. The consequence can be a time-consuming and costly replanning to solve problems in existing production and work processes. Using the example of an assembly of washing machines, an iterative approach is presented for a combined digital planning on factory and workplace level. A holistic design of the assembly line is carried out using the ema Software Suite, consisting of the ema Plant Designer (emaPD) and ema Work Designer (emaWD). In the case study, emaPD is used to optimize production elements such as operating resources, layout, and logistics by considering the material flow, throughput times, and production costs. These results are applied for detailed planning and design at the workstation level with emaWD, which uses an algorithmic approach for self-initiated motion generation based on objective task descriptions. The generated simulations are examined and optimized based on production time estimation (MTM-UAS) and ergonomic risk assessments (EAWS, NIOSH, reach and vision analysis) as well as workers’ abilities (age, anthropometry). As a result, an efficient factory with an optimized material flow could be planned while minimizing the manufacturing costs and throughput times while complying with the space specifications and ergonomics. The takeover of ergonomically unfavorable processes by robots as hybrid workstations enables, among other things, an improvement in ergonomics. The digital planning approach of combined factory (emaPD) and workplace design (emaWD) also enable early, coordinated, efficient planning of economical and ergonomic production.
Manual material handling such as box lifting is a very common task that is used in the industrial and medical fields. It is widely accepted that manual lifting can potentially lead to low back injury. Asymmetric lifting, which involves twisting of the trunk, shifts trunk muscle activation and can increase the lower back loading on the spine thus further increasing the likelihood of injury. Other researchers have explored asymmetric lifting but have not considered the effects of handedness. Sex has also been considered as a factor related to low back injury, but majority of research work include only male subjects in literature. This work aims to examine the effects of sex, handedness, box load, and box origin on the maximum lumbar flexion/extension L5-S1 joint moments generated during two-handed box lifting so that safer lifting recommendations can be made for those tasks. Eight participants (sex: 4 women, 4 men; age: 28.62 ± 4.53 years; height: 170.00 ± 7.45 cm; body mass: 72.36 ± 8.97 kg; handedness: 4 left-dominant, 4 right-dominant) performed two-handed box lifts with five different box origins (two left lifts, one sagittally symmetric lift, and two right lifts) and three different box weights (1.20 kg, 5.74 kg, 10.27 kg). Motion data was collected using a motion capture system and force plates. There were no clear trends for the effect of sex, but our results suggest that individuals should lift from their dominant-hand side when performing asymmetric two-handed lifting tasks. Future work which will incorporate the use multiscale modeling (musculoskeletal modeling and finite element modeling) to perform a deeper analysis of spine biomechanics during these lifts at the muscle and tissue levels, respectively.
A hand with 25 degrees of freedom (DOF) was proposed with forward and inverse kinematics for all fingers, with a realistic virtual simulation. However, the wrist is not in the model. Today, several authors have proposed in the literature that the wrist has a relative movement between the two rows of bones with eight bones. Some authors discuss a comparison of four joint coordinate systems previously described in the literature. Others propose a helical movement of wrist bones in distal movements. Objective: A new design the hand model of 25 DOF adding a movement of two rows and eight bones of the wrist. Methods: Once we locate a new coordinates system in the end of the radius close to the scaphoid, we apply Denavit-Hartenberg for all joints. Forward and inverse kinematics are applied. We include ten ligaments to apply restrictions in the wrist movement, which affects fingertip position. Results: A new model of a virtual human hand with more accuracy is presented and validated with a Cyberglove™ and Leap Motion. Conclusions: This new model that includes wrist movement yields a more accurate virtual human hand. New DOFs are added to the 25-DOF hand model.
Applying DHMs in the ergonomic design of vehicle interiors has been established for many years. Most use cases focus on various aspects of static driving configurations, but several dynamic occupant tasks must be evaluated as well for new vehicle concepts. Because of the task complexity, these tests are still performed in physical mock-ups. Over the past years, new DHM technologies have supported evaluating dynamic ergonomics of interior designs in digital mock-ups more efficiently. Nevertheless, there are still simulation aspects to be improved for proper industrial applications. This paper presents the recent development progress on knowledge-based motion simulation techniques using motion capture data and DHM prediction methods. The focus is on a large variability of motions in the database, more user control on the simulated motions, and functions for collision avoidance. Based on adjustable mock-ups, a range of ingress and egress motions into a truck and a passenger car were systematically measured, taking various positions of vehicle components like steps, doors, pillars, and roofs into account. These motion takes were reconstructed and annotated by DHMs and stored in a database. A new simulation tool was developed which uses the database to predict motions in virtual environments. The GUI provides a range of motion components subjected to various motion data and simulation methods. These components can be combined to create a cumulative motion. In addition, the intersection frames of consecutive components can be controlled by user-defined postures or tasks. Smooth transitions are supported by specific truncating and sewing up consecutive motions.In addition, the tool got new functions to consider collision avoidance during simulation. First, characteristic parameters (door angle) are extracted from the environment and used to find corresponding collision-free motions in the database. Second, specific geometric constraints avoid collisions at key frames. Applying both functions supports qualitative motion strategy changes and quantitative body positions to cope with collision situations. The tool development is accompanied by user evaluations with respect to usability and prediction capabilities. These identified open issues to be solved and pushed the tool further forward to a productive level.
The ability to predict the decline in muscle strength over the course of an activity (i.e., fatigue) can be a crucial aid to task design, injury prevention, and rehabilitation efforts. Current models of muscle fatigue have been hitherto validated only for isometric contractions, but most real-world tasks are dynamic in nature, involving continuously varying joint velocities. It has previously been proposed that a three-compartment-controller (3CC) model might be used to predict fatigue for such tasks by using it in conjunction with joint- and direction-specific torque-velocity-angle (TVA) surfaces. This allows for the calculation of a time-varying target load parameter that can be used by the 3CC model, but it increases model complexity and has not been validated by experimental data. An alternative approach is proposed where the effect of joint velocity is modeled by a velocity parameter and integrated into the fatigue model equations, removing the dependence on external TVA surfaces. The predictions using both methods are contrasted against experimental data collected from 20 subjects in a series of isokinetic tests involving the knee and shoulder joints, covering a range of velocities encountered in day-to-day tasks. A much lower degree of fatigue is observed for moderate velocities compared to that for very low or very high velocities. Predictions using the integrated velocity parameter are computationally less expensive than using TVA surfaces and are also closer to experimentally obtained values. The modified fatigue model can therefore be applied to dynamic tasks with varying velocities when the task is discretized into several isokinetic tasks.
