BiomotumDevelopment of a Real-time Controller to Estimate Walking Performance Using a Bilateral Ankle Exoskeleton

This arm employs a within-subject design with two methods of estimating metabolic cost versus the gold standard measure of metabolic cost, wherein a single participant is subjected to two distinct measurements. This design allows for a direct comparison of the effects of each method (i.e., estimation versus gold standard) within the same individual, minimizing intersubject variability and enhancing the statistical power of the analysis.

This intervention uses a robotic ankle exoskeleton equipped with a real-time adaptive controller that adjusts plantarflexion torque based on each participant's walking mechanics. Unlike standard exoskeleton controllers that use fixed or pre-programmed assistance levels, this system employs human-in-the-loop optimization to continuously update torque magnitude and timing during treadmill walking. The controller integrates metabolic estimations, kinematic data, and musculoskeletal modeling to identify individualized assistance patterns that reduce walking effort and improve muscle activation efficiency. Participants complete multiple walking trials while the controller automatically modifies assistance to determine the optimal personalized settings.