Simulation models are a valuable tool for exoskeleton development, especially for system optimization and evaluation. It allows an assessment of the performance and effectiveness of exoskeletons even at an early stage of their development without physical realization. Due to the closed physical interaction between the exoskeleton and the user, accurate modeling of the human–exoskeleton interaction in defined scenarios is essential for exoskeleton simulations. This paper presents a novel approach to simulate exoskeleton motion in response to human motion and the interaction forces at the physical interfaces between the human and the exoskeleton. Our approach uses a multibody model of a shoulder exoskeleton in MATLAB R2021b and imports human motion via virtual markers from a digital human model to simulate human–exoskeleton interaction. To validate the human-motion-based approach, simulated exoskeleton motion and interaction forces are compared with experimental data from a previous lab study. The results demonstrate the feasibility of our approach to simulate human–exoskeleton interaction based on human motion. In addition, the approach is used to optimize the support profile of an exoskeleton, indicating its potential to assist exoskeleton development prior to physical prototyping.

Assistive devices like exoskeletons undergo extensive testing not least because of their close interaction with humans. Conducting user studies is a time-consuming process that demands expert knowledge, and it is accompanied by challenges such as low repeatability and a potential lack of comparability between studies. Obtaining objective feedback on the exoskeleton’s performance is crucial for developers and manufacturers to iteratively improve the design and development process. This paper contributes to the concept of using robots for objective exoskeleton testing by presenting various approaches to a robotic-based testing platform for upper-body exoskeletons. We outline the necessary requirements for realistically simulating use cases and evaluate different approaches using standard manipulators as robotic motion generators. Three approaches are investigated: (i) Exploiting the anthropomorphic structure of the robotic arm and directly placing it into the exoskeleton. (ii) Utilizing a customized, direct attachment between the robot and exoskeleton. (iii) Attaching a human arm dummy to the robot end effector to simulate a more realistic interface with the exoskeleton. Subsequently, we discuss and compare the results against the aforementioned requirements of a systematic testing platform. Our conclusion emphasizes that achieving objective and realistic testing necessitates highly specialized hardware, algorithms, and further research to address challenging requirements.

The authors introduce a new interconnection network for massively parallel systems called the incomplete star graph. They describe unique ways of interconnecting and labeling the nodes, and routing point-to-point communications within this network. A special class of the incomplete star graph is presented and the network measures for this special class are derived. An n-dimensional star graph increases by a factor of (n+1)>2 every time it grows to the next dimension. One of the main contributions is the development of a selection method for designing an m-processor network with (n-1)-factorial<m<n-factorial out of n-factorial possible permutations.