Occupational ergonomics in healthcare is an increasing challenge we have to handle in the near future. Physical assistive systems, so-called exoskeletons, are promising solutions to prevent work-related musculoskeletal disorders (WMSDs). Manual handling like pushing, pulling, holding and lifting during healthcare activities require practical and biomechanical effective assistive devices. In this article, a musculoskeletal-model-based development of an assistive exoskeleton is described for manual patient transfer in the surgery waiting room. For that purpose, kinematic data collected with an experimental set-up reproducing real patient transfer conditions are first used to define the kinetic boundary conditions for the model-based development approach. Model-based analysis reveals significant relief potential in the lower back and shoulder area of the musculoskeletal apparatus. This is corroborated by subjective feedback collected during measurements with real surgery assistants. A shoulder–arm exoskeleton design is then proposed, optimized and evaluated within the same simulation framework. The presented results illustrate the potential for the proposed design to reduce significantly joint compressions and muscle activities in the shoulder complex in the considered patient transfer scenarios.

Musculoskeletal disorders (MSDs) induced by industrial manual handling tasks are a major issue for workers and companies. As flexible ergonomic solutions, occupational exoskeletons can decrease critically high body stress in situations of awkward postures and motions. Biomechanical models with detailed anthropometrics and motions help us to acquire a comprehension of person- and application-specifics by considering the intended and unintended effects, which is crucial for effective implementation. In the present model-based analysis, a generic back-support exoskeleton model was introduced and applied to the motion data of one male subject performing symmetric and asymmetric dynamic manual handling tasks. Different support modes were implemented with this model, including support profiles typical of passive and active systems and an unconstrained optimal support mode used for reference to compare and quantify their biomechanical effects. The conducted simulations indicate that there is a high potential to decrease the peak compression forces in L4/L5 during the investigated heavy loaded tasks for all motion sequences and exoskeleton support modes (mean reduction of 13.3% without the optimal support mode). In particular, asymmetric motions (mean reduction of 14.7%) can be relieved more than symmetric ones (mean reduction of 11.9%) by the exoskeleton support modes without the optimal assistance. The analysis of metabolic energy consumption indicates a high dependency on lifting techniques for the effectiveness of the exoskeleton support. While the exoskeleton support substantially reduces the metabolic cost for the free-squat motions, a slightly higher energy consumption was found for the symmetric stoop motion technique with the active and optimal support mode.

Occupational exoskeletons are a promising solution to prevent work-related musculoskeletal disorders (WMSDs). However, there are no established systems that support heavy lifting to shoulder height. Thus, this work presents a model-based analysis of heavy lifting activities and subsequent exoskeleton concept optimization. Six motion sequences were captured in the laboratory for three subjects and analyzed in multibody simulations with respect to muscle activities (MAs) and joint forces (JFs). The most strenuous sequence was selected and utilized in further simulations of a human model connected to 32 exoskeleton concept variants. Six simulated concepts were compared concerning occurring JFs and MAs as well as interaction loads in the exoskeleton arm interfaces. Symmetric uplifting of a 21 kg box from hip to shoulder height was identified as the most strenuous motion sequence with highly loaded arms, shoulders, and back. Six concept variants reduced mean JFs (spine: >70%, glenohumeral joint: >69%) and MAs (back: >63%, shoulder: >59% in five concepts). Parasitic loads in the arm bracing varied strongly among variants. An exoskeleton design was identified that effectively supports heavy lifting, combining high musculoskeletal relief and low parasitic loads. The applied workflow can help developers in the optimization of exoskeletons.

Human-centred and ergonomic work design is one of the most important drivers for increasing the competitiveness of the European Union. As a flexible, person-specific occupational measure, exoskeletons promise great potential for effectively reducing individual ergonomic stress. Digital human models can provide important insights and offer great potential for systematising the effect and targeted use of exoskeletons, supporting their effective implementation in practice. In this article, digital human models are applied on two levels. Firstly, a realistic industrial logistics scenario in which boxes had to be relocated is designed with the help of a digital human model for workplace and process planning and secondly, a new biomechanical evaluation methodology to analyse intended and unintended effects on internal stress on the human body is demonstrated by applying musculoskeletal exoskeleton human models of four test subjects. Finally, the modelled biomechanical support tendencies of one exoskeleton are preliminary validated using EMG measurement data of the back muscles collected from the four male workers. The preliminary analysis of two back-support exoskeletons to demonstrate the new methodological approach confirms the expected, intended effects in the lower back and reveals unintended effects, such as e.g. changes in knee kinetics when applying a soft or hard-frame exoskeleton. Furthermore, the exemplary results to demonstrate the methodological approach expose notable differences between the test subjects, which underlines the relevance of person-specific evaluation and consideration of exoskeleton support. The preliminary validation shows a correlation between the modelled and the EMG-measured biomechanical exoskeleton support of the considered back muscles.

Ungünstig gestaltete Arbeitsplätze und -prozesse können das Risiko für Muskel-Skelett-Erkrankungen (MSE) erhöhen und insbesondere die Einsatzfähigkeit älterer Beschäftigter einschränken. Anhand eines Arbeitsplatzes in der Kosmetikindustrie wird gezeigt, wie mittels ema Work Designer Arbeitsprozesse unter Einsatz von digitalen Menschmodellen simuliert und optimiert werden. Dadurch konnten ergonomische und wirtschaftliche Probleme identifiziert und gezielte Maßnahmen ableitet werden, die jungen als auch älteren Mitarbeitenden eine gesundheitsgerechte und effiziente Arbeit ermöglichen.

Exoskeletons transfer loads to the human body via physical human–exoskeleton interfaces (pHEI). However, the human–exoskeleton interaction remains poorly understood, and the mechanical properties of the pHEI are not well characterized. Therefore, we present a novel methodology to precisely characterize pHEI interaction stiffnesses under various loading conditions. Forces and torques were applied in three orthogonal axes to the upper arm pHEI of 21 subjects using an electromechanical apparatus. Interaction loads and displacements were measured, and stiffness data were derived as well as mathematically described using linear and non-linear regression models, yielding all the diagonal elements of the stiffness tensor. We find that the non-linear nature of pHEI stiffness is best described using exponential functions, though we also provide linear approximations for simplified modeling. We identify statistically significant differences between loading conditions and report median translational stiffnesses between 2.1 N/mm along and 4.5 N/mm perpendicular to the arm axis, as well as rotational stiffnesses of 0.2 N·m/° perpendicular to the arm, while rotations around the longitudinal axis are almost an order of magnitude smaller (0.03 N·m/°). The resulting stiffness models are suitable for use in digital human–exoskeleton models, potentially leading to more accurate estimations of biomechanical efficacy and discomfort of exoskeletons.