% % This file was created by the TYPO3 extension % publications % --- Timezone: CEST % Creation date: 2026-05-16 % Creation time: 01:06:20 % --- Number of references % 6 % @Article { vianello_robot-mediated_2025, author = {Vianello, Lorenzo and Short, Matthew and Manczurowsky, Julia and K\"{u}\c{c}\"{u}ktabak, Emek Bar\c{s} and Tommaso, Francesco Di and Noccaro, Alessia and Bandini, Laura and Clark, Shoshana and Fiorenza, Alaina and Lunardini, Francesca and Canton, Alberto and Gandolla, Marta and Pedrocchi, Alessandra L. G. and Ambrosini, Emilia and Murie-Fern\'{a}ndez, Manuel and Rom\'{a}n, Carmen B. and Tornero, Jesus and Leon, Natacha and Sawers, Andrew and Patton, Jim and Formica, Domenico and Tagliamonte, Nevio Luigi and Rauter, Georg and Baur, Kilian and Just, Fabian and Hasson, Christopher J. and Novak, Vesna D. and Pons, Jose L.}, title = {Robot-Mediated Physical Human–Human Interaction in Rehabilitation: A Position Paper}, year = {2025}, issn = {1937-3333, 1941-1189}, DOI = {10.1109/RBME.2025.3632161}, journal = {IEEE Reviews in Biomedical Engineering}, pages = {1--16}, tags = {robotics rehabilitation}, file_url = {https://ieeexplore.ieee.org/document/11267500/} } @Article { al-tashi_classroom-ready_2024, author = {Al-Tashi, Mohammed and Lennartson, Bengt and Ortiz-Catalan, Max and Just, Fabian}, title = {Classroom-ready open-source educational exoskeleton for biomedical and control engineering}, abstract = {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.}, year = {2024}, month = {5}, language = {en}, issn = {0178-2312, 2196-677X}, DOI = {10.1515/auto-2023-0208}, journal = {at - Automatisierungstechnik}, volume = {72}, pages = {460--475}, number = {5}, tags = {exoskeleton teaching}, file_url = {https://www.degruyter.com/document/doi/10.1515/auto-2023-0208/html} } @Article { earley_cutting_2024, author = {Earley, Eric J. and Zbinden, Jan and Munoz-Novoa, Maria and Just, Fabian and Vasan, Christiana and Holtz, Axel Sj\"{o}gren and Emadeldin, Mona and Kolankowska, Justyna and Davidsson, Bj\"{o}rn and Thesleff, Alexander and Millenaar, Jason and J\"{o}nsson, Stewe and Cipriani, Christian and Granberg, Hannes and Sassu, Paolo and Br\a{a}nemark, Rickard and Ortiz-Catalan, Max}, title = {Cutting Edge Bionics in Highly Impaired Individuals: A Case of Challenges and Opportunities}, year = {2024}, issn = {1534-4320, 1558-0210}, DOI = {10.1109/TNSRE.2024.3366530}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {32}, pages = {1013--1022}, tags = {prosthetics}, file_url = {https://ieeexplore.ieee.org/document/10438487/} } @Article { just_deployment_2024, author = {Just, Fabian and Ghinami, Chiara and Zbinden, Jan and Ortiz-Catalan, Max}, title = {Deployment of Machine Learning Algorithms on Resource-Constrained Hardware Platforms for Prosthetics}, year = {2024}, issn = {2169-3536}, DOI = {10.1109/ACCESS.2024.3371251}, journal = {IEEE Access}, volume = {12}, pages = {40439--40449}, tags = {prostetics ml}, file_url = {https://ieeexplore.ieee.org/document/10452358/} } @Article { just_human_2020, author = {Just, Fabian and \"{O}zen, \"{O}zhan and Tortora, Stefano and Klamroth-Marganska, Verena and Riener, Robert and Rauter, Georg}, title = {Human arm weight compensation in rehabilitation robotics: efficacy of three distinct methods}, abstract = {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}, year = {2020}, month = {12}, language = {en}, issn = {1743-0003}, DOI = {10.1186/s12984-020-0644-3}, journal = {Journal of NeuroEngineering and Rehabilitation}, volume = {17}, pages = {13}, number = {1}, tags = {rehabilitation robotics}, file_url = {https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-020-0644-3} } @Article { just_exoskeleton_2018, author = {Just, Fabian and \"{O}zen, \"{O}zhan and B\"{o}sch, Philipp and Bobrovsky, Hanna and Klamroth-Marganska, Verena and Riener, Robert and Rauter, Georg}, title = {Exoskeleton transparency: feed-forward compensation vs. disturbance observer}, abstract = {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.}, year = {2018}, month = {12}, language = {en}, issn = {2196-677X, 0178-2312}, DOI = {10.1515/auto-2018-0069}, journal = {at - Automatisierungstechnik}, volume = {66}, pages = {1014--1026}, number = {12}, tags = {exoskeleton}, file_url = {https://www.degruyter.com/document/doi/10.1515/auto-2018-0069/html} }