Optimal Integration of Hybrid FES-Exoskeleton for Precise Knee Trajectory Control

This paper introduces a novel hybrid torque allocation method for improving wearability and mobility in integrated functional electrical stimulation (FES) of the quadriceps muscles and powered exoskeleton systems. Our proposed approach leverages a hierarchical closed-loop controller for knee joint position tracking while addressing limitations of powered exoskeletons and FES systems by reducing power consumption and battery size and by mitigating FES-induced muscle fatigue, respectively. The core component is a model-free optimization algorithm that dynamically distributes torque between FES and the exoskeleton by considering tracking error, effort, and the prediction of muscle fatigue in the cost function, computing allocation gain in an online manner. The online optimization approach interactively changes the optimal allocation gain by taking into account the instantaneous value of error and effort and also penalizing FES-induced fatigue, a common challenge in long-duration experiments. The results demonstrate that this dynamic allocation significantly improves system wearability by reducing power consumption without increasing muscle fatigue during the extension phase of walking. This hybrid control approach contributes to improving exoskeleton wearability and rehabilitation outcomes for individuals with SCI and mobility impairments, enhancing assistive technology and quality of life.