Yaniv Yacoby

Papers

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About

Yaniv Yacoby is a leading researcher in the field of wearable robotics and human-robot interaction, with a focus on developing assistive devices that are not only effective but also intuitive and user-friendly. His work centers on the design and optimization of soft exosuits—lightweight, textile-based wearable robots—for occupational and rehabilitative applications, particularly for lifting and lowering tasks. Yacoby's major contribution lies in his pioneering approach to preference-based assistance optimization, which directly addresses a critical barrier to the adoption of exoskeletons: user comfort and perceived benefit. By integrating user feedback into the control algorithms, his research ensures that these devices provide tangible, noticeable assistance without causing restriction or discomfort. His most-cited paper, "Preference-based assistance optimization for lifting and lowering with a soft back exosuit" (2025, 6 citations), exemplifies this innovative methodology, demonstrating how to tailor robotic support to individual user preferences. This work has significant implications for reducing workplace injuries and enhancing rehabilitation outcomes. Yacoby’s research is shaping the next generation of wearable robotics, making them more accessible and effective for real-world use.