Human-In-The-Loop Control of a Soft Pneumatic Exosuit for Step Width Guidance Via Hip Abduction/Adduction

The constraints of cable-driven actuation have largely limited mediolateral (ML) assistance from soft exosuits to hip abduction. To address this limitation, we developed a soft pneumatic exosuit actuated by pneumatic artificial muscles (PAMs) capable of providing bidirectional assistance to both hip abduction and adduction to guide the wearer’s step width. Given the challenges in accurately modeling PAM- driven systems, we propose a Human-in-the-Loop (HIL) ap- proach that treats the human-exosuit system as a black box and uses Bayesian optimization to tune control parameters. In walking experiments with two healthy participants, the proposed HIL framework successfully identified participant- specific PI gains during the parameter tuning session. In the subsequent validation, the controller based on the optimized gains reduced the mean step-width RMSE by 43.4 % for Participant 1 and 26.8 % for Participant 2 compared with the condition without assistance. The optimized gains also provided an additional improvement of 3.76 % for Participant 1 and 1.07 % for Participant 2 relative to the controller with initial gains. These results indicate that the proposed approach offers a practical method for personalizing assistance in soft pneumatic exosuits and contributes to the development of devices that enhance ML balance.