Fatigue Assessment and Control With Lower Limb Exoskeletons

Abstract

Acknowledging the vital importance of fatigue management for improving rehabilitation results, customizing treatment, safeguarding patient well-being, and enhancing the quality of life of hemiplegic patients, this study presents the development of a tailored fatigue model and a corresponding human-in-the-loop (HiL) control system for exoskeleton-assisted walking. For this, the selected three-compartment controller fatigue model including a resting recovery parameter was adapted to a dynamic walking task scenario, incorporating a torque–velocity–angle dependency to quantify muscle activity. The model parameters were experimentally verified in a study with six healthy subjects, demonstrating accurate prediction of maximum voluntary contraction (MVC) decline with an average mean absolute error of 4.9%MVC. Subsequently, an HiL control mechanism was developed, utilizing ratings of perceived fatigue and state of fatigue values as reference metrics. The presented control approach effectively regulates fatigue levels within a 0%MVC–6%MVC steady-state error range during simulations. Experimental validation confirmed this performance, however, with partly higher steady-state errors mainly due to the restrictions of the exoskeleton's assistance. This preliminary study provides a promising foundation for future research, demonstrating the potential to manage fatigue effectively in exoskeleton users, offering an improved, personalized experience.