Kevin De Pauw
Papers
9
Total Citations
145
H-Index
5
About
Kevin De Pauw is a pioneering researcher at the intersection of human-robot interaction, wearable robotics, and neural engineering, whose work is reshaping how assistive technologies are developed and personalized. His most impactful contribution — a systematic review on human-in-the-loop optimization (HILO) of wearable robotic devices (85 citations) — established a comprehensive framework for understanding how real-time user feedback can drive smarter, more adaptive exoskeletons and prosthetics. Building on this foundation, De Pauw has championed EMG-based objective functions as practical, non-invasive alternatives to cumbersome metabolic measurements, advancing the personalization of wearable devices for both occupational and rehabilitative contexts. Beyond wearable robotics, De Pauw has made significant strides in brain-computer interface research, developing shared control systems that combine motor imagery BCIs, eye tracking, and augmented reality to empower individuals with physical disabilities. His deep learning review for biosignal control (24 citations) further demonstrates his commitment to bridging cutting-edge machine learning with real-world assistive applications. His exploration of muscle synergies for robot-assisted rehabilitation and user adoption dynamics of occupational exoskeletons reflects the impressive breadth of his vision — placing human experience and usability at the heart of technological innovation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5An EMG-Based Objective Function for Human-in-the-Loop Optimization5 citations · 2023
- 6
- 7
- 8A muscle synergy-based method to improve robot-assisted movements3 citations · 2025
- 9