Samuel A. Burden

This study investigates how humans adapt to a new walking condition after broad experience with different belt speeds, finding that participants adjust their gait strategies when exposed to a distinct energy landscape.

The paper develops a computational framework using control and game theory to predict and optimize user-decoder interactions in co-adaptive neural interfaces through experimental validation.

This study demonstrates that using eye gaze as training data can achieve comparable performance to task-specific training in adaptive myoelectric interfaces for 2D cursor control.

This study examines how handedness affects learned controllers and performance in trajectory-tracking tasks, finding no significant differences between hands.

This study evaluates three data-driven phase-varying models to predict kinematic and myoelectric responses to ankle exoskeletons during walking, finding LPV models provide better accuracy than PV models for kinematic predictions.