Papers
2
Total Citations
48
H-Index
2
About
Benjamin Treussart is a researcher at the forefront of human-robot collaboration, specializing in the intuitive control of upper-limb exoskeletons for force augmentation. His major contributions center on leveraging electromyography (EMG) signals to enable seamless assistance during load carrying, eliminating the need for cumbersome force sensors. His most-cited work, "Controlling an upper-limb exoskeleton by EMG signal while carrying unknown load" (2020, 36 citations), introduces an innovative control law that adapts to unknown loads, enhancing user autonomy and safety. Complementing this, his 2019 study on personalized calibration (12 citations) refines EMG-based intention detection, tailoring assistance to individual users. Together, these papers have laid a critical foundation for practical, sensor-free exoskeleton systems, with cumulative citations reflecting growing interest in assistive robotics. Treussart’s work is notable for its focus on real-world applicability, bridging the gap between laboratory prototypes and everyday use in industrial or rehabilitation settings. His achievements underscore a commitment to making human augmentation both intuitive and accessible, positioning him as a key contributor to next-generation wearable robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2