Digital human models (DHM) allow for a proactive ergonomic assessment of products by applying different models describing the user-product interaction. In engineering design, DHM tools are currently not established as computer-aided ergonomics tools, since (among other reasons) the interaction models are either cumbersome to use, unstandardised, time-demanding or not trustworthy. To understand the challenges in interaction modelling, we conducted a systematic literature review with the aim of identification, classification and examination of existing interaction models. A schematic user–product interaction model for DHM is proposed, abstracting existing models and unifying the corresponding terminology. Additionally, nine general approaches to proactive interaction modelling were identified by classifying the reviewed interaction models. The approaches are discussed regarding their scope, limitations, strength and weaknesses. Ultimately, the literature review revealed that prevalent interaction models cannot be considered unconditionally suitable for engineering design since none of them offer a satisfactory combination of genuine proactivity and universal validity. Practitioner summary: This contribution presents a systematic literature review conducted to identify, classify and examine existing proactive interaction modelling approaches for digital human models in engineering design. Ultimately, the literature review revealed that prevalent interaction models cannot be considered unconditionally suitable for engineering design since none of them offer a satisfactory combination of genuine proactivity and universal validity. Abbreviations: DHM: digital human model; CAE: computer-aided engineering; RQ: research question

Although biomechanical digital human models find their way into virtual engineering processes, biomechanical considerations are currently still unrecognized to a large extent. One major obstacle lies in the fact that even though subject-specific modeling procedures are developed, virtual user groups or populations are still missing. The objective of this contribution is to create such groups of musculoskeletal models. Therefore, a modeling procedure based upon population data is described. First of all, two generic three-dimensional models, one with female and one with male average anthropometric dimensions, were obtained. These models constitute the starting point for the following model adjustment phases. Evenly distributed dimensionless values for gender, age, height, mass, range of motion and strength are sampled and translated into more expressive parameters for the mentioned modeling domains serving as input data for the creation of each individual model of the desired population or user group. The most sophisticated step of the adaption is the strength mapping aiming to create models matching arbitrary target joint torques. Finally, the models’ maximal strength is assessed in a manual material handling task and compared to empirical strength data. The approach is shown using the example of the German population.

The individualization of patient-specific ankle joint orthoses is becoming increasingly important and can be ideally realized by means of additive manufacturing. However, currently, there are no functional additively manufactured fiber-reinforced products that are used in the field of orthopedic treatment. In this paper, an approach as to how additively manufactured orthopedic products can be designed and produced quickly and flexibly in the future is presented. This is demonstrated using the example of a solid ankle–foot orthosis. For this purpose, test results on PETG-CF15, which were determined in a previous work, were integrated into a material map for an FEA simulation. Therewith, the question can be answered as to whether production parameters that were determined at the test specimen level can also be adapted to real, usable components. Furthermore, gait recordings were used as loading conditions to obtain exact results for the final product. In order to perfectly adapt the design of the splint to the user, a 3D scan of a foot was performed to obtain a perfect design space for topology optimization. This resulted in a patient-specific and stiffness-optimized product. Subsequently, it was demonstrated that the orthosis could be manufactured using fused layer modelling. Finally, a comparison between the conventional design and the consideration of AM-specific properties was made. On this basis, it can be stated that the wearing comfort of the patient-specific design is very good, but the tightening of the splint still needs to be improved.

Stigma may be the Achilles’ heel of Inclusive Design, having a variety of negative effects on the user, e.g. anxiety or depression. From a product development (PD) perspective, such negative user stigmatisation can lead to the rejection of a product. PD cannot defeat stigma itself, but it can make a valuable contribution by reducing product-related stigma. Joining the battle, this contribution analyses the role of PD and identifies supports that help to reduce stigma in the respective context using an initial and a systematic literature review. The role of PD is split into four categories addressing the need to fulfil specific demands (reduce stigma and improve personal well-being), exploit potentials (see design as a tool, use the power of product semantics and design for our future selves), solve current problems (lack of knowledge and not taking the user seriously) and manage boundary conditions (complexity of stigma and the stigma-sensitivity of products). Individual, process, educational solutions or general strategies are supports that help meeting those expectations. Due to different challenges, there is still a need for action to improve those supports to deliver specific design recommendations and reduce the lack of knowledge.

Repetitive overhead work with a heavy load increases the risk for work-related shoulder disorders. Occupational exoskeletons supporting arm elevation are potential solutions to reduce that risk by lowering the physical strains on the shoulder. Many studies have reported a reduction in shoulder stress in various overhead tasks by using such exoskeletons. However, the support demand can vary in each phase of motion as well as in each individual task. This paper presents a laboratory study with five participants to evaluate the influence of the support level of an active shoulder exoskeleton in different motion phases (e.g., arm lifting, screw-in, and arm lowering of two overhead tasks) to identify the potential optimization of support at each phase. Results show that the support level of the exoskeleton should be adapted to the motion phase of the two chosen tasks. A higher support force is desired for the screw phase compared to the arm lifting and lowering phases, and the support level needs to be reduced immediately for arm lowering after the screw phase. The time for switching the support levels can be recognized by the electric current of the screwdriver.

Biomechanical simulation allows for in silico estimations of biomechanical parameters such as muscle, joint and ligament forces. Experimental kinematic measurements are a prerequisite for musculoskeletal simulations using the inverse kinematics approach. Marker-based optical motion capture systems are frequently used to collect this motion data. As an alternative, IMU-based motion capture systems can be used. These systems allow flexible motion collection without nearly any restriction regarding the environment. However, one limitation with these systems is that there is no universal way to transfer IMU data from arbitrary full-body IMU measurement systems into musculoskeletal simulation software such as OpenSim. Thus, the objective of this study was to enable the transfer of collected motion data, stored as a BVH file, to OpenSim 4.4 to visualize and analyse the motion using musculoskeletal models. By using the concept of virtual markers, the motion saved in the BVH file is transferred to a musculoskeletal model. An experimental study with three participants was conducted to verify our method’s performance. Results show that the present method is capable of (1) transferring body dimensions saved in the BVH file to a generic musculoskeletal model and (2) correctly transferring the motion data saved in the BVH file to a musculoskeletal model in OpenSim 4.4.