Papers
12
Total Citations
144
H-Index
6
About
Felix M. Escalante is a leading researcher in rehabilitation and wearable robotics, with a core focus on human-robot interaction, robust control, and Markovian jump systems. His major contribution lies in developing advanced impedance and force control frameworks that make robotic rehabilitation safer and more adaptive to the unpredictable dynamics of human movement. By integrating Markovian robust filtering and control with series elastic actuators (SEAs), Escalante has pioneered methods that allow robots to respond to abrupt changes in human behavior—a critical challenge in therapy and exoskeleton use. His most cited work, "Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach" (49 citations), established a foundation for this approach, while his subsequent papers on transparency control and electromyographic signal integration have pushed the field toward more intuitive, user-responsive devices. Escalante’s impact is evident in over 130 total citations, with influential studies on ankle rehabilitation platforms and knee exoskeletons. Notably, he also developed ReRobApp, an open-source software framework that democratizes robotic rehabilitation research. His work bridges theoretical control engineering with practical, human-centered robotics, making him a key figure in the next generation of assistive technology.
Research Focus
Key Achievements
Top Papers
- 1Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach49 citations · 2017
- 2Markovian robust filtering and control applied to rehabilitation robotics22 citations · 2020
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- 4Markovian Transparency Control of an Exoskeleton Robot13 citations · 2022
- 5Markovian Robust Compliance Control Based on Electromyographic Signals8 citations · 2018
- 6Robust Markovian Impedance Control applied to a Modular Knee-Exoskeleton7 citations · 2020
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- 9Impedance Control Analysis for Legged Locomotion in Oscillating Ground5 citations · 2024
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