Philipp Arens
Papers
3
Total Citations
53
H-Index
3
About
Philipp Arens is a researcher at the intersection of rehabilitation robotics, human-robot interaction, and explainable AI. His work focuses on developing intelligent wearable systems that enhance human motor function while prioritizing user experience and trust. Arens made a significant contribution to post-stroke rehabilitation with his highly cited 2021 paper on real-time gait metric estimation using wearable sensors (43 citations), demonstrating how task-specific, intensive training can be delivered outside clinical settings. He further advanced occupational exoskeletons by introducing a preference-based assistance optimization framework for a soft back exosuit (2025), addressing critical usability barriers like comfort and perceived restriction that hinder real-world adoption. In a novel cross-domain contribution, Arens explored explainable AI by applying Shapley values to Bayesian optimization (2024), enabling human-AI collaboration in black-box optimization problems. This work bridges the gap between algorithmic efficiency and user interpretability. His research is notable for its human-centered approach—prioritizing user perception and collaborative decision-making alongside technical performance. Arens’s work is shaping the future of assistive and rehabilitative technologies that are not only effective but also trusted and adopted by their users.
Research Focus
Key Achievements
Top Papers
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