Alexis Derumigny

Papers

Total Citations

H-Index

About

Alexis Derumigny is a researcher at the intersection of human motor learning, robotics, and personalized rehabilitation. Their key research areas include haptic guidance, robotic-assisted motor training, and the modulation of learning by individual differences such as personality traits. Derumigny’s major contribution lies in demonstrating that the effectiveness of robotic assistance during motor training is not uniform—it is significantly influenced by the trainee’s personality. In their most cited work (2024, 4 citations), they showed that haptic guidance can enhance motor learning outcomes, but only when tailored to the individual’s psychological profile, paving the way for more adaptive, user-centered rehabilitation technologies. This work highlights a critical shift from one-size-fits-all robotic training to personalized, trait-aware interventions. Although early in their career, Derumigny’s research has already been recognized for its potential to improve motor recovery in both healthy populations and patients with neurological conditions. Their findings offer a compelling framework for designing smarter, more empathetic robotic systems that respond not just to movement, but to the person behind it.