Etienne Burdet

Out-of-sight partners: autonomous wearable supernumerary limbs for dynamic co-manipulation

This study demonstrates that humans can effectively collaborate with autonomous wearable robotic limbs during dynamic tasks without visual feedback, achieving reliable task completion and high perceived safety.

Explainable Decoding of Sensorimotor Communication in Joint Object Manipulation

This study decodes human intent during collaborative object manipulation using multimodal signals and explains how sensorimotor communication occurs through action.

Information-dependent eye-hand coordination emerges from active vision

The paper develops a computational model of active vision that explains how eye-hand coordination adapts to information context, showing how saccade-pursuit patterns emerge from minimizing task-related uncertainty.

How individual vigor shapes human-human physical interaction

This study shows how individual vigor affects dyadic coordination in physical tasks, with slower partners influencing dyadic vigor and coordination patterns.

A modular architecture for trial-by-trial learning of redundant muscle activity patterns in novel sensorimotor tasks

This paper presents a computational model that learns redundant muscle activity patterns in novel sensorimotor tasks through trial-by-trial adaptation of muscle synergies and their recruitment coefficients.

Model predictive game control for personalized and targeted interactive assistance

This paper develops a model-predictive game controller for contact robots to improve human-robot interaction by predicting human control and adapting to individual motor strategies.

Intermittent movement control emerges from information-based planning

This study introduces an information-based control framework that generates human-like movement behavior in discrete and continuous tasks by dynamically adjusting planning based on surprise and task constraints.

Effects of Uni- and Bidirectional Interaction During Dyadic Ankle and Wrist Tracking

This study examines how uni- and bidirectional haptic interactions affect motor performance and muscle activation during wrist and ankle tracking tasks, finding mutual benefits in bidirectional interaction across limbs.

Co-Contraction Embodies Uncertainty: An Optimal Feedforward Strategy for Robust Motor Control

The paper shows that muscle co-contraction increases with environmental uncertainty to stabilize motor control when feedback is insufficient.

During haptic communication, the central nervous system compensates distinctly for delay and noise

The paper investigates how humans compensate for delay and noise in haptic communication with a robot, finding distinct strategies for each.

Control limitations in the null-space of the wrist muscle system

This study investigates the ability to control muscle activation in the null-space of the wrist system for movement augmentation, finding limitations in null-space control but capability in concurrent force and co-contraction control.

A model predictive control strategy to regulate movements and interactions

This paper introduces a Model Predictive Control strategy that regulates both movement and interaction control, demonstrating its ability to produce human-like movements and handle nonlinear dynamics.

The control and training of single motor units in isometric tasks are constrained by a common synaptic input signal

The paper shows that humans cannot easily control individual motor units independently, as their activation is governed by a shared input signal and changes in de-recruitment order.