Papers
7
Total Citations
165
H-Index
5
About
Fabian Just is a leading researcher in rehabilitation robotics, specializing in exoskeleton control, human-robot interaction, and assistive technologies for neurorehabilitation. His major contributions center on improving the transparency and efficacy of robotic arm exoskeletons—particularly the ARMin system—by developing advanced compensation methods for undesired forces and arm weight. His work on feed-forward compensation and disturbance observers (50 citations) and comparative studies of arm weight compensation techniques (45 citations) has directly enhanced training outcomes for stroke patients, enabling greater active range of motion and reducing pathological muscle synergies. Just also pioneered online adaptive compensation algorithms (30 citations) and feedforward model-based approaches (30 citations) that allow robots to dynamically adjust to patient needs, increasing rehabilitation intensity and effectiveness. Beyond clinical applications, he has contributed to usability improvements for rehabilitation robots and developed an open-source educational exoskeleton for biomedical and control engineering classrooms. His research has been instrumental in bridging the gap between robotic hardware and patient-centered therapy, making rehabilitation more accessible and effective for individuals with neurological impairments.
Research Focus
Key Achievements
Top Papers
- 1Exoskeleton transparency: feed-forward compensation vs. disturbance observer50 citations · 2018
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- 3Online adaptive compensation of the ARMin Rehabilitation Robot30 citations · 2016
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