Due to their potential to reduce occupational physical strain and enhance human performance, the development of exoskeletons has gained significant attention. This study presents a musculoskeletal simulation pipeline designed to evaluate the biomechanical effects of shoulder-supporting exoskeletons. The focus of the investigation is on the biomechanical tools obtained from musculoskeletal simulations for the evaluation of exoskeletons. Such tools result in many biomechanical values, such as joint kinematics, external joint torques, muscle activation and joint reaction forces. The pipeline was applied to a use case, where electromyography (EMG) signals were collected and compared with simulated muscle activations for validation. The simulated muscle activations had a relative root mean square error (RMSE) of 37% in the area under the curve (AUC) compared to the EMG muscle activation. Joint reaction force analysis revealed altered magnitude and direction of the tangential JRF in the glenohumeral joint during exoskeleton support. This work raises the question of whether the focus in the development of shoulder exoskeletons should be on reducing the load on the subacromial space. By analyzing joint reaction forces and muscle activations, the pipeline can help to identify design parameters that reduce the load on the rotator cuff in the subacromial space.

Wearable assistive devices such as ankle-foot orthoses (AFOs) or exoskeletons are commonly evaluated using musculoskeletal simulations, yet the interface between device and body is typically simplified. In reality, this interface consists of biological soft tissue. Soft tissue deformation influences relative movement, force transmission, and the biomechanical effectiveness of assistive devices. However, this aspect is often neglected in simulation-based design. This study therefore investigates the influence of biological soft tissue on human-device interaction within musculoskeletal modeling. A musculoskeletal simulation model was implemented and extended by integrating an AFO. Biological soft tissue behavior at the device-body interface was represented by viscoelastic spring-damper elements. Simulations were performed using gait data from multiple participants across different walking speeds and AFO support profiles representing varying severities of foot drop. In addition, systematic axis misalignments between the orthosis and the ankle joint were introduced. The simulations revealed that biological soft tissue substantially contributes to relative motion between the AFO and the body segment, with displacements reaching up to 20 mm, particularly near the end of the stance phase during gait. The magnitude of relative movement increased with greater muscle weakness and higher required support forces. In contrast, gait speed and axis misalignment produced comparatively smaller effects. Soft tissue deformation also influenced muscle activation patterns, especially in severely weakened conditions, where deviations of up to 13% were observed in the plantarflexor muscles. The findings demonstrate that incorporating biological soft tissue behavior significantly affects predicted human-orthosis interaction and muscle activation in musculoskeletal simulations. Accounting for these deformations potentially improves the realism of simulation-based analyses and supports more accurate evaluation of assistive device performance. Consequently, explicit modeling of biological soft tissue should be considered essential for the development and optimization of effective and comfortable wearable assistive technologies.

This paper presents a modular robot-assisted exoskeleton haptic simulation environment that uses collaborative robots (cobots) and ROS2 to accelerate the development and testing of shoulder exoskeletons. Traditional exoskeleton development requires multiple physical prototypes, resulting in considerable time and resource expenditure. The proposed system uses reconfigurable cobot formations to physically simulate various exoskeleton types and properties before final product development. Within various formations, different exoskeletons and support scenarios can be simulated. This approach offers a scalable, cost-effective method for exoskeleton design optimization that can be extended to other joint systems beyond the shoulder complex.

In recent years, the development of exoskeletons has increasingly focused on providing region-specific support for complex physical movements. While current systems are often tailored to fixed use cases, the integration of adaptive parameters offers a pathway toward more responsive assistance. This biomechanical study evaluates the muscular and postural effects of passive and active back exoskeletons to identify the potential advantages of integrating intelligent control systems. To analyze these effects, three measurement systems were utilized: electromyography (EMG) sensors to measure muscle activity in the Erector Spinae and Multifidus, a force plate for stance stability, and a motion capture system for postural analysis. The methodology involved five subjects performing three distinct, real-world-inspired tasks under three conditions: passive assistance, active assistance, and an exoskeleton-free approach. Technological principles, including the specific sensors, actuators, and materials employed, were classified to provide context for the observed results. Findings indicate that while both systems provide support, active back exoskeletons possess a unique stabilizing effect and considerable potential for reducing physical strain. However, high variability in muscle recruitment and subjective discomfort during trunk extension suggest that fixed-torque assistance can occasionally conflict with natural human kinematics, particularly across varying user anthropometrics. This evidence leads to the conclusion that the distinctive potential of active exoskeletons is best harnessed through intelligent control systems. By incorporating artificial intelligence to predict movement and recognize task-specific loads, these systems can optimize assistance, transitioning from rigid support to a seamless, adaptive partnership with the user.

Exoskeletons for industrial applications offer a promising approach in reducing physical strain, a risk factor for work-related musculoskeletal diseases. However, comparability of different devices is complicated as various physiological, kinematic, and kinetic measurement methods are common practice for assessment. The objective of this study was to assess the validity of a self-developed performance test bench to measure static and dynamic support behavior of industrial exoskeletons with single degree-of-freedom support. Two upper-limb exoskeletons (Comau Mate—CM, Levitate Airframe—LA) were used for reliability assessment. Root mean squared error between observed data and valid reference was below 5 θ̇ = 100—400°/s2) for dynamic measurements. Test—retest reliability was high for both tested exoskeletons based on ICCCM = 0.99 and ICCLA = 0.98 with a TEMCM = 0.09 Nm (2.4 θ̇ > 100°/s2) needs further optimization. Continuous measurements of support behavior form the fundamental basics for reliable biomechanical models of human-exoskeleton interactions.

One of the biggest challenges in developing exoskeletons is that they need a long development process. Emulation of exoskeleton behaviour can be a noticeable advantage for exoskeleton development and evaluation, e.g., by reducing the number of necessary physical exoskeleton prototypes and thus accelerating system optimization and evaluation. This paper proposes a framework to emulate the behaviour of exoskeletons by using an approach with collaborative robots (cobots), motion tracking system and Robot Operating System 2 (ROS2). The proposed approach offers an ability to see the exoskeleton-human interaction in physical environment while the exoskeleton is configured in digital environment. Within this ability, it differentiates from existing approaches. According to system testing, it is seen that the measured force profile and calculated force profile are close to each other. Therefore, the proposed approach gives promising results about that the physical simulation of exoskeleton is possible by using motion capture system, exoskeleton simulation framework and cobots. In future, the developed system will be further confirmed with more experimentation to improve the settings.

Abstract Industrielle Exoskelette und andere physische Unterstützungssysteme basieren nach wie vor weitgehend auf Erfahrungswerten, da die Ergebnisse aus digitalen und physischen Simulationen, Robotertests und Anwenderstudien selten konsistent integriert werden. In diesem Beitrag wird ein wissensbasiertes Expertensystem vorgestellt, das domänenübergreifende Daten und Kriterien integriert, um transparente Empfehlungen für die Entwicklung und Bewertung von Exoskeletten zu geben.

Occupational exoskeletons are designed to support workers in strenuous tasks and to promote health, yet their implementation and use often present challenges due to the close interaction between wearer and device. This study explored user perceptions of occupational exoskeletons through qualitative focus groups conducted after participants had gained hands-on experience with 16 different devices in four-hour trials. Key findings highlight users’ feedback on system sound, design, and support, movement restriction and wearer comfort, and underscore the important role of bodily sensations—alongside factors, such as usability and appearance—in exoskeleton user experience. A central discovery was the existence of conflicts between user preferences, for instance, between light-weight designs and effective user support. Based on these insights, we highlight implications for human-centered design of exoskeletons and aim to inspire further research within the human–computer interaction community.

IntroductionThis study investigated the user experience and perceived acceptance of a shoulder exoskeleton during Chemical, Biological, Radiological, and Nuclear (CBRN) tasks in a military context. While laboratory research on the same system has shown measurable reductions in muscle activity of 29%–41%, the present field study focused on how end users subjectively evaluate the exoskeleton.MethodsTwenty-seven soldiers of the German Armed Forces tested the exoskeleton for approximately 30 min while completing standardized scenarios, including overhead lifting, vehicle decontamination with a spray lance, and casualty rescue. Immediately afterward, participants completed a structured questionnaire assessing usability, wearing comfort, impact on work routine, perceived support, usefulness, skepticism, and intention to use.ResultsOverall, the exoskeleton was rated as easy to operate (mean item score: 5.15 ± 1.31 on a 7-point scale) and reasonably comfortable to wear (4.64 ± 1.31). Compatibility with work routines and perceived usefulness received moderate ratings (3.79 ± 1.53 and 3.05 ± 1.64, respectively), whereas the perceived mechanical support was notably low (2.78 ± 1.78). Skepticism (2.27 ± 1.08), and intentions to use the system were moderate (3.42 ± 2.08).DiscussionThe user feedback suggests that while the current design is usable and generally comfortable, acceptance may improve substantially if future systems provide a higher amount of support and an expanded functionality to address a wider variety of tasks. These findings underscore that, beyond biomechanical effectiveness, user acceptance is a critical factor for the successful implementation of exoskeletons as occupational health interventions.

The development of human-centered exoskeletons is critical for addressing labor shortages and reducing musculoskeletal disorders. However, studying these systems presents challenges, including ethical concerns, variability in human behavior, and limitations in long-term studies. This work proposes a novel methodology that integrates natural human movement captured via motion capture systems, modular 3Dprinted anthropometric body segments for replicating relevant body parts, and collaborative robots (cobots) for simulating and reproducing calculated human motion patterns. Using an upper arm case study, an algorithm to translate motion data into precise control values for the cobot is developed, achieving high-fidelity motion reproduction. The results demonstrate a robust framework for overcoming human-based study limitations, advancing the design and validation of exoskeletons.

Understanding and evaluating human motion is central to biomechanics, ergonomics, sports science, and humansystem interaction. Laboratory studies enable controlled measurements and technological accessibility but often suffer from low task realism and between-trial variability, which limits comparability across studies. Particularly in applications where kinematics play a crucial role, such as in assistive or ergonomic systems, biomechanical analyses are employed to derive user requirements, evaluate system performance, or train control algorithms. We present a virtual reality (VR) guided framework for human centred evaluations that preserves realistic task context while standardizing execution. Two industrial scenarios, overhead riveting and surface spraying, were recreated in the lab with and without VR guidance. Informational cues (path corridor, dwell indicators, progress feedback, haptic signals) were designed to focus attention, constrain timing, and implicitly shape movement trajectories. Ten healthy adults completed both tasks; full body kinematics and surface electromyography (EMG) (anterior/medial/posterior deltoid, trapezius descendens) were recorded. With VR guidance, shoulder elevation trajectories showed reduced dispersion, cycles became slower and more uniform, and peak angular speeds decreased with tighter spread. Procedurally, VR reduced protocol deviations and simplified postprocessing. These findings indicate that VR provides a practical, repeatable laboratory context that complements, rather than replaces, field evaluations by improving the quality and consistency of human motion data.

The development of exoskeletons requires a long development process that involves multiple stages, including prototyping, testing, and validation. Simulation of exoskeleton behavior can contribute to exoskeleton development and evaluation, e.g., by reducing the number of necessary exoskeleton prototypes and thus accelerating system optimization and evaluation. This paper presents a novel approach to streamline the exoskeleton development process by implementing a physical simulation platform using a collaborative robot (cobot) and Robot Operating System 2 (ROS2). The platform enables real-time haptic feedback and motion support, simulating exoskeleton properties. By using the precision and adaptability of cobots, combined with the modularity and real-time communication of ROS2, the proposed system reduces the need for multiple physical prototypes and extensive testing procedures. Experimental results prove the effectiveness of the platform in simulating shoulder joint movements and forces under various conditions, highlighting its potential to accelerate exoskeleton design cycles. This work contributes to the field by providing a cost-effective, efficient, and reusable framework for exoskeleton physical simulation.

The physical demands of overhead tasks can lead to musculoskeletal strain, particularly in scenarios requiring prolonged arm elevation such as in Chemical, Biological, Radiological, and Nuclear (CBRN) operations. To address this, an active shoulder exoskeleton was developed that is compatible with CBRN protective gear. The aim of this laboratory study was to assess the biomechanical and physiological effects of the system during upper limb tasks representative of real-world applications, without the use of protective suits. Twenty-two male participants performed two tasks with and without the exoskeleton: (1) 5 kg lifting task and (2) repetitive spraying tasks with a spray lance. Muscle activity of the m. anterior deltoid was measured using surface electromyography, while energy expenditure was assessed via spiroergometry. The exoskeleton significantly reduced muscular demands in the anterior deltoid, with a decrease of up to 40% during the spraying task and 29% percent during lifting task. Additionally, oxygen consumption per kilogram of body mass decreased by 6.5 to 8.2% across tasks. Participants reported lower fatigue and greater task manageability when using the exoskeleton, particularly for sustained and semi-static overhead postures. The results demonstrate that the exoskeleton effectively reduces workload during upper limb tasks. These findings support its application not only for soldiers in contaminated environments but also in industrial settings involving overhead work. Future research will need to validate these effects under realistic CBRN conditions to confirm operational compatibility.

Despite the increasing use of automation and digitalization in industrial workplaces, workers still have to handle heavy loads and have to perform strenuous, repetitive, long-term assembly tasks at head level or above, which may lead to degenerative musculoskeletal disorders. The growing trend towards wearable support systems has already resulted in a large number of exoskeletons being in research or commercially available. However, most of the support systems for industrial workplaces focus on the back and shoulders, but not the elbow joint. In a preliminary study, we presented a soft passive elbow exoskeleton, which was limited to static tasks, although dynamic support is necessary for most industrial tasks. Building upon that work, this paper presents an elbow exoskeleton that can be coupled to an existing shoulder exoskeleton. The developed prototype is designed to support the elbow flexion with a pneumatic actuator for industrial applications. The functionality of the prototype was tested on three male participants in one static and two dynamic tasks. The laboratory tests have shown that the exoskeleton reduced the mean muscular activity of the brachioradialis and biceps brachii in all tasks. Based on the results, the developed exoskeleton may potentially support the elbow flexion in industrial tasks, but further testing is needed to evaluate its biomechanical effects on the user.

Demographic shifts, extended working lives, and growing demand for quality and productivity heighten companies' need to support their workforce. Exoskeletons, as a new technology, offer potential ergonomic benefits but face challenges such as limited system acceptance, experience, and application knowledge, requiring proper training for occupational use. This article presents a training program for companies considering integrating exoskeletons. The program consolidates insights to transfer knowledge, equip decision-makers with essential skills, and foster experience exchange across industries. It comprises four modules, from analyzing ergonomics and manual work settings to implementing and evaluating exoskeletons in practice. Positive feedback from 63 participants across 26 companies highlighted the program's relevance and suitability. The program contributes to learning environments by translating research into practical training, helping companies foster innovation and operational excellence.

Occupational exoskeletons for industrial workplaces hold significant promise for improving worker ergonomics and safety. However, the successful selection of an exoskeleton depends on informed decision-making processes that consider various factors ranging from biomechanical performance to usability and compatibility with work tasks. This paper presents a methodology that aims to develop a co-simulation-based selection tool for selecting an exoskeleton for specific industrial work tasks. It integrates multidisciplinary knowledge from biomechanics, human factors engineering, and industrial ergonomics for assessing the suitability of exoskeletons across diverse industrial applications. The methodology is designed as a stage-gate process with five main stages corresponding to the product development process. It describes the main tasks in each phase, their results, and the gates between the stages. The tasks and results are derived and detailed from the current literature and preliminary work. The gates include the specification of the simulation and decision-relevant input and output parameters, the design of the co-simulation model consisting of task and biomechanical simulation, the weighting of the individual decision criteria, and the subsequent implementation of the multi-criteria decision analysis to create a ranking of suitable exoskeletons. This work concludes by elaborating on the impact of the novel co-simulation methodology on research and industry. Research implications include advanced simulation methods for exoskeleton evaluation, the systematic comparison of different exoskeletons, and the development of decision analysis models. Benefits to the industry include improved compatibility, informed selection processes, reduced investment risks, and increased technology adoption.

Physical support systems such as exoskeletons are gaining importance to support workers in smart and connected factories by reducing physical strain. In order for the exoskeleton to be integrated seamlessly with humans and tasks within the work environment, it must be able to detect and adapt to human intentions. Compared to conventional control, myoelectric control, i.e., control based on measured muscle activity, enables improved human–robot interaction and more intuitive interaction with humans. This paper explores how myoelectric control can improve the interaction of industrial exoskeletons. For this purpose, the anatomical basics of electromyography (EMG) for detecting muscle activity are presented, followed by existing myoelectric control strategies. The insights gained are applied to the implementation of myoelectric control for industrial exoskeletons. It is shown that EMG-based control benefits from human adaptivity, making it particularly suitable in the case of variant movements and changing conditions. Even though using electromyographic control for adaptation of the exoskeleton includes efforts in terms of setup and calibration, the insights gained into the physiological state of the human (e.g., muscle activity, fatigue) are crucial for the adaptation to the user.

In recent years, various exoskeletons have been developed to support specific movements and body regions. Exoskeletons are normally designed taking into account particular use cases and developed to support a certain body region and movement. While conducting a biomechanical study with different exoskeletons, it was realized that certain parameters could be efficiently used to control an exoskeleton. The present biomechanical study analyses the dependent parameters of exoskeletons, which inform the potential merits of integrating an intelligent control system. In the study, five test subjects were required to perform three distinct tasks, which were inspired by real-world scenarios, using a passive, active, and exoskeleton-free approach. The data was collected using electromyography sensors, a force plate and motion capture as well as using questionnaires. Firstly, it was demonstrated that active exoskeletons have a stabilizing effect on their wearers. Secondly, it was shown that these exoskeletons are fundamentally suitable for supporting their users in specific tasks. Nevertheless, the evidence also indicated that the incorporation of intelligent systems into exoskeletons can be particularly beneficial for predicting movement. This leads to the conclusion that active exoskeletons have a distinctive potential that can be harnessed through the integration of intelligent control systems.

Musculoskeletal disorders, particularly lower back pain, are common among healthcare workers due to frequent lifting, bending, and prolonged standing. To address this issue, we developed a lightweight, soft, and active exoskeleton designed to support lifting movements while maintaining user mobility and comfort. This paper presents the design of the exoskeleton. To assess the physiological effects on the wearer’s body, we conducted a biomechanical analysis, evaluating joint kinematics (hip and knee) and muscle activation (m. erector spinae and m. semitendinosus) during a lifting task. The results showed that the exoskeleton effectively reduced muscle activation in the m. erector spinae by 15.82 ± 13.35% and m. semitendinosus by 19.89 ± 20.84% without significantly altering the analyzed joint kinematics. These findings indicate that the system provides targeted support without restricting mobility, making it a promising tool for reducing physical strain in healthcare and other physically demanding professions.

This paper explores a five-axis printing method designed to improve the fabrication of continuous fiber-reinforced thermoplastic composites (CFRTPCs), essential for producing lightweight, complex structures in advanced manufacturing. Traditional CFRTPC placement techniques often face challenges with precision, scalability, and optimal fiber orientation, especially in customized, small-scale applications. The proposed five-axis printing technique overcomes these issues by enabling precise fiber orientation and the production of robust spatial structures using 3D-printed molds compatible with CFRTPCs. Validation through three-point bending and surface quality tests revealed that five-axis printed cylindrical-lattice samples, with fibers oriented at 45°, exhibited superior mechanical properties and surface quality. The five-axis printed samples achieved a load-to-weight ratio 27% higher than traditional samples and maintained their shape even under significant deformation. Surface quality improved significantly, with roughness values reduced from 37.63 µm to approximately 12 µm. This method advances CFRTPC applications in industries requiring complex, lightweight components.