Comparing volitional electromyographic control strategies: from proportional mapping to muscle modeling and reflex augmentation.

To advance intuitive volitional control for lower-limb prostheses, this study compares three torque control architectures based on electromyography (EMG) - including a novel reflex-augmented approach - using a virtual balance task. The goal is to determine whether muscle-model-based control improves performance and reduces user load relative to proportional EMG control, and whether incorporating simulated stretch reflexes further enhances results. Sixteen participants performed a virtual balancing task using EMG signals from antagonist lower-leg muscles to control an inverted pendulum subjected to perturbations. Four controllers were tested in randomized order: proportional, model-based, and two reflex-augmented variants differing in reflex gain. The model-based controller employed paired Hill-type muscle models; reflex variants additionally injected velocity-dependent stretch reflex feedback. User load was captured alongside control performance. While all participants successfully used all controllers, the model-based controller consistently enabled more stable and less effortful control than proportional EMG control. Reflex augmentation altered pendulum dynamics and showed slight performance tendencies in favor of the weaker reflex gain but did not yield clear or consistent benefits across participants compared with the model-based controller alone. Overall, incorporating muscle mechanics into EMG-based control substantially improves intuitive torque regulation over simple proportional mapping. While reflex augmentation showed promising potential, its current formulation did not provide reliable added value, indicating a need for refined reflex modeling and parameter tuning for future volitional prosthesis control applications.