Roozbeh Khodmbashi
Papers
1
Total Citations
17
H-Index
1
About
Roozbeh Khodmbashi is a leading researcher in rehabilitation robotics, with a focus on human-robot interaction and stroke recovery. His work centers on developing intelligent, therapist-inspired robotic systems for post-stroke gait training, aiming to make rehabilitation more personalized and effective. His most cited paper, "Learning Post-Stroke Gait Training Strategies by Modeling Patient-Therapist Interaction" (2023, 17 citations), introduces a novel approach that directly learns from physical therapists' manual assistance techniques. By modeling the complex dynamics between patient and therapist, Khodmbashi enables robots to adapt their support in real time, mimicking expert clinical judgment. This contribution bridges the gap between human expertise and robotic precision, offering safer and more responsive training for stroke survivors. His research has been recognized for its potential to transform clinical practice, with implications for scalable, at-home rehabilitation. With a growing citation record and a focus on translating data-driven methods into tangible patient outcomes, Khodmbashi is shaping the future of assistive robotics and neurorehabilitation.
Research Focus
Key Achievements
Top Papers
- 1