This file was created by the TYPO3 extension publications --- Timezone: CEST Creation date: 2026-04-22 Creation time: 02:16:34 --- Number of references 6 article vianello_robot-mediated_2025 2025 1937-3333, 1941-1189 10.1109/RBME.2025.3632161 IEEE Reviews in Biomedical Engineering 1—16 robotics rehabilitation https://ieeexplore.ieee.org/document/11267500/ Lorenzo Vianello Matthew Short Julia Manczurowsky Emek Barş Küçüktabak Francesco Di Tommaso Alessia Noccaro Laura Bandini Shoshana Clark Alaina Fiorenza Francesca Lunardini Alberto Canton Marta Gandolla Alessandra L. G. Pedrocchi Emilia Ambrosini Manuel Murie-Fernández Carmen B. Román Jesus Tornero Natacha Leon Andrew Sawers Jim Patton Domenico Formica Nevio Luigi Tagliamonte Georg Rauter Kilian Baur Fabian Just Christopher J. Hasson Vesna D. Novak Jose L. Pons article al-tashi_classroom-ready_2024 Abstract In recent years, robotic arm exoskeletons have emerged as promising tools, finding widespread application in the rehabilitation of neurological disorders and as assistive devices for everyday activities, even alleviating the physical strain on labor-intensive tasks. Despite the growing prominence of exoskeletons in everyday life, a notable knowledge gap exists in the availability of open-source platforms for classroom-ready usage in educational settings. To address this deficiency, we introduce an open-source educational exoskeleton platform aimed at Science, Technology, Engineering, and Mathematics (STEM) education. This platform represents an enhancement of the commercial EduExo Pro by AUXIVO, tailored to serve as an educational resource for control engineering and biomedical engineering courses. 2024 5 en 0178-2312, 2196-677X 10.1515/auto-2023-0208 at - Automatisierungstechnik 72 460—475 5 exoskeleton teaching https://www.degruyter.com/document/doi/10.1515/auto-2023-0208/html Mohammed Al-Tashi Bengt Lennartson Max Ortiz-Catalan Fabian Just article earley_cutting_2024 2024 1534-4320, 1558-0210 10.1109/TNSRE.2024.3366530 IEEE Transactions on Neural Systems and Rehabilitation Engineering 32 1013—1022 prosthetics https://ieeexplore.ieee.org/document/10438487/ Eric J. Earley Jan Zbinden Maria Munoz-Novoa Fabian Just Christiana Vasan Axel Sjögren Holtz Mona Emadeldin Justyna Kolankowska Björn Davidsson Alexander Thesleff Jason Millenaar Stewe Jönsson Christian Cipriani Hannes Granberg Paolo Sassu Rickard Brånemark Max Ortiz-Catalan article just_deployment_2024 2024 2169-3536 10.1109/ACCESS.2024.3371251 IEEE Access 12 40439—40449 prostetics ml https://ieeexplore.ieee.org/document/10452358/ Fabian Just Chiara Ghinami Jan Zbinden Max Ortiz-Catalan article just_human_2020 Abstract Background Arm weight compensation with rehabilitation robots for stroke patients has been successfully used to increase the active range of motion and reduce the effects of pathological muscle synergies. However, the differences in structure, performance, and control algorithms among the existing robotic platforms make it hard to effectively assess and compare human arm weight relief. In this paper, we introduce criteria for ideal arm weight compensation, and furthermore, we propose and analyze three distinct arm weight compensation methods ( Average , Full , Equilibrium ) in the arm rehabilitation exoskeleton ’ARMin’. The effect of the best performing method was validated in chronic stroke subjects to increase the active range of motion in three dimensional space. Methods All three methods are based on arm models that are generalizable for use in different robotic devices and allow individualized adaptation to the subject by model parameters. The first method Average uses anthropometric tables to determine subject-specific parameters. The parameters for the second method Full are estimated based on force sensor data in predefined resting poses. The third method Equilibrium estimates parameters by optimizing an equilibrium of force/torque equations in a predefined resting pose. The parameters for all three methods were first determined and optimized for temporal and spatial estimation sensitivity. Then, the three methods were compared in a randomized single-center study with respect to the remaining electromyography (EMG) activity of 31 healthy participants who performed five arm poses covering the full range of motion with the exoskeleton robot. The best method was chosen for feasibility tests with three stroke patients. In detail, the influence of arm weight compensation on the three dimensional workspace was assessed by measuring of the horizontal workspace at three different height levels in stroke patients. Results All three arm weight compensation methods reduced the mean EMG activity of healthy subjects to at least 49% compared with the no compensation reference. The Equilibrium method outperformed the Average and the Full methods with a highly significant reduction in mean EMG activity by 19% and 28% respectively. However, upon direct comparison, each method has its own individual advantages such as in set-up time, cost, or required technology. The horizontal workspace assessment in poststroke patients with the Equilibrium method revealed potential workspace size-dependence of arm height, while weight compensation helped maximize the workspace as much as possible. Conclusion Different arm weight compensation methods were developed according to initially defined criteria. The methods were then analyzed with respect to their sensitivity and required technology. In general, weight compensation performance improved with the level of technology, but increased cost and calibration efforts. This study reports a systematic way to analyze the efficacy of different weight compensation methods using EMG. Additionally, the feasibility of the best method, Equilibrium , was shown by testing with three stroke patients. In this test, a height dependence of the workspace size also seemed to be present, which further highlights the importance of patient-specific weight compensation, particularly for training at different arm heights. Trial registration ClinicalTrials.gov,NCT02720341 . Registered 25 March 2016 2020 12 en 1743-0003 10.1186/s12984-020-0644-3 Journal of NeuroEngineering and Rehabilitation 17 13 1 rehabilitation robotics https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-020-0644-3 Fabian Just Özhan Özen Stefano Tortora Verena Klamroth-Marganska Robert Riener Georg Rauter article just_exoskeleton_2018 Abstract Undesired forces during human-robot interaction limit training effectiveness with rehabilitation robots. Thus, avoiding such undesired forces by improved mechanics, sensorics, kinematics, and controllers are the way to increase exoskeleton transparency. In this paper, the arm therapy exoskeleton ARMin IV+ was used to compare the differences in transparency offered by using the previous feed-forward model-based controller, with a disturbance observer in a study. Systematic analysis of velocity-dependent effects of controller transparency in single- and multi-joint scenarios performed in this study highlight the advantage of using disturbance observers for obtaining consistent transparency behavior at different velocities in single-joint and multi-joint movements. As the main result, the concept of the disturbance observer sets a new benchmark for ARMin transparency. 2018 12 en 2196-677X, 0178-2312 10.1515/auto-2018-0069 at - Automatisierungstechnik 66 1014—1026 12 exoskeleton https://www.degruyter.com/document/doi/10.1515/auto-2018-0069/html Fabian Just Özhan Özen Philipp Bösch Hanna Bobrovsky Verena Klamroth-Marganska Robert Riener Georg Rauter