Musculoskeletal disorders constitute the leading work-related health issue. Mechanical loading of the lower back contributes as a major risk factor and is prevalent in many tasks performed in logistics. The study aimed to compare acute effects of exoskeletons with different functional mechanisms in a logistic task. Twelve young, healthy individuals participated in the study. Five exoskeletons with different functional mechanisms were tested in a logistic task, consisting of lifting, carrying, and lowering a 13 kg box. By using electromyography (EMG), mean muscle activities of four muscles in the trunk were analyzed. Additionally, kinematics by task completion time and range of motion (RoM) of the major joints and segments were investigated. A main effect was found forMusculus erector spinae,Musculus multifidus, andMusculus latissimus dorsishowing differences in muscle activity reductions between exoskeletons. Reduction in ES mean activity compared to baseline was primarily during lifting from ground level. The exoskeletons SoftExo Lift and Cray X also showed ES mean reduction during lowering the box. Prolonged task duration during the lifting phase was found for the exoskeletons BionicBack, SoftExo Lift, and Japet.W. Japet.W showed a trend in reducing hip RoM during that phase. SoftExo Lift caused a reduction in trunk flexion during the lifting phase. A stronger trunk inclination was only found during lifting from the table for the SoftExo Lift and the Cray X. In conclusion, muscle activity reductions by exoskeleton use should not be assessed without taking their designed force paths into account to correctly interpret the effects for long-term injury prevention.

Future planetary exploration missions will rely heavily on efficient human–robot interaction to ensure astronaut safety and maximize scientific return. In this context, digital twins offer a promising tool for planning, simulating, and optimizing extravehicular activities. This study presents the development and evaluation of a digital twin for the AMADEE-24 analog Mars mission, organized by the Austrian Space Forum and conducted in Armenia in March 2024. Alternative local positioning methods were evaluated to enhance the system’s utility in Global Navigation Satellite System (GNSS)-denied environments. The digital twin integrates telemetry from the Aouda space suit simulators, inertial measurement unit motion capture (IMU-MoCap), and sensor data from the Intuitive Rover Operation and Collecting Samples (iROCS) rover. All nine experiment runs were reconstructed successfully by the developed digital twin. A comparative analysis of localization methods found that Simultaneous Localization and Mapping (SLAM)-based rover positioning and IMU-MoCap localization of the astronaut matched Global Positioning System (GPS) performance. Adaptive Cluster Detection showed significantly higher deviations compared to the previous GNSS alternatives. However, the IMU-MoCap method was limited by discontinuous segment-wise measurements, which required intermittent GPS recalibration. Despite these limitations, the results highlight the potential of alternative localization techniques for digital twin integration.

Occupational shoulder exoskeletons need to provide meaningful torques to achieve the desired support, thereby high pressures can occur within the physical human–machine interface (pHMI) of exoskeletons that may lead to discomfort, pain, or soft tissue injuries. This pilot study investigates the effects of occurring circumferential pressures within the pHMI in three different shoulder exoskeletons on the tissue oxygenation underneath the interfaces in resting position and dynamic use of the exoskeletons in 12 healthy subjects using near-infrared spectroscopy. Similar to standard Vascular Occlusion Tests, the tissue oxygen decreases while wearing the exoskeletons at rest (−2.1 (1.4) %/min). Dynamic use of the exoskeleton enhances the decrease in tissue oxygen (−7.3 (4.1) %/min) significantly and leads to greater resaturation after reopening the interface compared to resting position. This can be a sign of restricted blood supply to the upper extremity while wearing the exoskeleton. The shape and width of the circular interfaces showed no effect on the tissue oxygenation during use. Tissue oxygenation can be established as an additional safety criterion of exoskeletal pHMIs. The design of pHMI of shoulder exoskeletons should be reconsidered, e.g., in terms of open structures or the elasticity of closure straps to avoid occlusion effects.

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.

Introduction and Purpose Space exploration is transitioning to a new era. NASA’s Artemis program is spearheading crewed missions to the Moon in the next decade, paving the way for eventual human exploration of Mars (Smith et al., 2020). However, space missions further afar from Earth require a shift in operational concepts towards an increasingly autonomous mission architecture due to communication delay (Belobrajdic et al., 2021). Analog space missions, such as AMADEE24, address these methodological challenges in a terrestrial simulation scenario (Preston & Dartnell, 2014). In order to imitate the biomechanical and perceptual constraints of suited operations in an analog mission, the astronauts wear space-suit simulators during extravehicular activities (EVA; Groemer et al., 2012). As EVAs account for the most physically-demanding and risky operations during space missions, the relevance for human movement science in space research is increasing. We propose an approach to integrate already available data sources to conduct comprehensive human movement analysis in planetary exploration scenarios. As a proof of concept, we aimed to identify sensitive kinematic and physiological markers for muscular fatigue in astronauts’ gait during the AMADEE24 mission conducted by the Austrian Space Forum. Methods The AMADEE24 Mars simulation took place from March 5th until April 5th 2024 in the Ararat province in Armenia, which was selected as simulation site for its geological similarities to areas on Mars. Six analog astronauts (two female, four male) lived isolated in a habitat for 21 days, conducting robotic, psychological and geoscientific experiments pertinent to future surface activities on Mars. Extensive high-resolution drone imaging of the analog region before the mission was conducted to compile a digital elevation model used for EVAs. Experiments in the field were conducted by two analog astronauts wearing the AOUDA space-suit simulator with two astronauts supporting them from the habitat using radio communication (Groemer et al., 2012). The recorded telemetry data of the suit included GPS location, heart rate, CO2- and O2-concentrations in the helmet as well as temperature and humidity measurements in the suit and primarily serves for medical monitoring of the astronauts during the EVA. Beneath the suit, the astronauts wore the inertial whole-body motion capture system XsensTM Awinda (Xsens Technologies B.V., Enschede, Netherlands) with 17 IMU-sensors and an 8-channel electromyography (EMG) system (Cometa myon, Barregio, Italy) for muscle activity recordings of the back, lower- and upper-extremities on the dominant side. For all experiments involving geoscientific operations by the analog astronauts, a remote-controlled robotic vehicle accompanied the astronauts in the field (Edlinger et al., 2022). The rover carried tools, samples and receiver for the motion-capture- and EMG-sensors. Additionally, the rover tracked the ambient conditions and took images of the surroundings, which are used to improve the 3D-environmental-model of the EVA region (see Figure 1). Biomechanical recordings were started remotely from the habitat. Prior to each EVA, astronauts prepared the experiment in the habitat following a controlled workflow. Four generic geoscientific operations common for geological sample-taking were performed at the beginning and end of the EVA by the test subject. The operations were performed at four different sites, each site approximately 40 to 60 m apart. A previously designed traverse plan shown in the head-up-display of the suit’s helmet defined the traverses for the astronauts. All four geoscientific operations as well as the ambulatory pathways were recorded by the motion capture- and EMG-systems. In a preliminary analysis of gait alterations, we investigated the pre- and post-EVA traverses to identify muscular fatigue accumulated over the 3 to 4 h-EVAs. The reprocessing of the motion capture recordings was performed using the software XsensTM MVN Analyze Pro 2024.0. Joint angles, center of mass (CoM) kinematics and torso sway, calculated as the roll angle of the T8-segment of the XsensTM human model around the sagital axis, were exported from XsensTM MVN software. Log dimensionless jerk (LDLJ) of the CoM was computed (Balasubramanian et al., 2011). A principal component analysis (PCA) over all analog astronauts was calculated based on the whole-body kinematics using the PManalyzer (Haid et al., 2019). The raw EMG signal was butterworth-filtered (10 Hz low pass cut off, 5th order) and normalized to maximum-voluntary-contraction measurements conducted before EVA start. All variables of interest were sliced step-wise, time-normalized and averaged for a full gait cycle. A descriptive subject-wise comparison of pre- and post-patterns was performed. Data analysis was carried out in Spyder 5.4.3 IDE using Python 3.9. Results Eight EVAs were recorded with four of them being aborted due to LOS-procedures (loss of signal) before a post-measurement could be conducted. Eleven EMG-recordings were compromised or missing due to technical issues (data transmission, battery). Four astronauts completed the pre-post measurements, which will be further analyzed. Self-reported perceived muscular fatigue post-EVA based on the Borg CR10 scale was 4.75 ± 1.5 (min: 3, max: 6) which corresponds to a Borg RPE rating of 13 (somewhat hard). The CoM LDLJ increased in all four subjects between the pre-/post-condition on average by about 4.3% from -5.57 ± 0.29 to -5.80 ± 0.41. Additionally, mediolateral sway of the torso increased by ~25% (pre: 6.4 ± 3.8°, post: 8.0 ± 4.6°; see Figure 1). The results of the PCA indicate a consistent gait adaptation in all subjects between pre-/post-condition in PC1 and PC2. While PC1 was more pronounced in the post-condition, PC2 had a decreased contribution to the gait pattern. Peak muscle activity in left and right...

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.