Papers
9
Total Citations
114
H-Index
6
About
Jonathan Realmuto is a robotics researcher whose work sits at the intersection of assistive technology, soft robotics, and human-robot interaction. His research focuses on developing wearable robotic systems—including prostheses and orthoses—that restore or augment motor function for individuals with movement impairments, alongside developing sophisticated control strategies that adapt to human physiology. Realmuto's most influential contribution is his soft fabric-based robotic forearm orthosis, which employs antagonistic helical actuators to deliver active pronation and supination assistance, garnering 52 citations and representing a significant advance in lightweight, compliant assistive wearables. His work on powered ankle-foot prostheses has been equally impactful, with his human-in-the-loop optimization approach targeting gait symmetry earning 22 citations and offering a meaningful pathway to reducing long-term musculoskeletal complications in amputees. Beyond hardware, Realmuto has made notable contributions to control theory through iterative and collaborative learning algorithms that personalize robot behavior to individual users. His more recent work on omnidirectional bending actuators and modular soft exosuits further demonstrates his commitment to versatile, body-conforming robotic solutions. Collectively, his research advances a vision of soft, intelligent wearable robots that meaningfully improve the daily independence and long-term health of people living with physical disabilities.
Research Focus
Key Achievements
Top Papers
- 1A robotic forearm orthosis using soft fabric-based helical actuators52 citations · 2019
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- 3Iterative learning control for human-robot collaborative output tracking10 citations · 2016
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- 7Modular and Reconfigurable Body Mounted Soft Robots3 citations · 2024
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