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Creation date: 2026-05-16
Creation time: 00:07:02
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6
article
vianello_robot-mediated_2025
Robot-Mediated Physical Human–Human Interaction in Rehabilitation: A Position Paper
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 BarÅŸ
°Ã¼Ã§Ã¼°ì³Ù²¹²ú²¹°ì
Francesco Di
Tommaso
Alessia
Noccaro
Laura
Bandini
Shoshana
Clark
Alaina
Fiorenza
Francesca
Lunardini
Alberto
Canton
Marta
Gandolla
Alessandra L. G.
Pedrocchi
Emilia
Ambrosini
Manuel
²Ñ³Ü°ù¾±±ð-¹ó±ð°ù²Ôá²Ô»å±ð³ú
Carmen B.
¸é´Ç³¾Ã¡²Ô
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
Classroom-ready open-source educational exoskeleton for biomedical and control engineering
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
Cutting Edge Bionics in Highly Impaired Individuals: A Case of Challenges and Opportunities
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
µþÂáö°ù²Ô
Davidsson
Alexander
Thesleff
Jason
Millenaar
Stewe
´³Ã¶²Ô²õ²õ´Ç²Ô
Christian
Cipriani
Hannes
Granberg
Paolo
Sassu
Rickard
µþ°ùÃ¥²Ô±ð³¾²¹°ù°ì
Max
Ortiz-Catalan
article
just_deployment_2024
Deployment of Machine Learning Algorithms on Resource-Constrained Hardware Platforms for Prosthetics
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
Human arm weight compensation in rehabilitation robotics: efficacy of three distinct methods
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
Ö³ú³ó²¹²Ô
Ö³ú±ð²Ô
Stefano
Tortora
Verena
Klamroth-Marganska
Robert
Riener
Georg
Rauter
article
just_exoskeleton_2018
Exoskeleton transparency: feed-forward compensation vs. disturbance observer
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
Ö³ú³ó²¹²Ô
Ö³ú±ð²Ô
Philipp
µþö²õ³¦³ó
Hanna
Bobrovsky
Verena
Klamroth-Marganska
Robert
Riener
Georg
Rauter