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Wearable robotic exoskeletons hold great promise for gait rehabilitation as portable, accessible tools. However, a better understanding of the potential for exoskeletons to elicit neural adaptation-a critical component of neurological gait rehabilitation-is needed. In this study, we investigated whether humans adapt to bilateral asymmetric stiffness perturbations applied by a hip exoskeleton, taking inspiration from the asymmetry augmentation strategies used in split-belt treadmill training. During walking, we applied torques about the hip joints to repel the thigh away from a neutral position on the left side and attract the thigh toward a neutral position on the right side. Six participants performed an adaptation walking trial on a treadmill while wearing the exoskeleton. The exoskeleton elicited time-varying changes and aftereffects in step length and propulsive/braking ground reaction forces, indicating behavioral signatures of neural adaptation. These responses resemble typical responses to split-belt treadmill training, suggesting that the proposed intervention with a robotic hip exoskeleton may be an effective approach to (re)training symmetric gait.

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Recent experiments with a variable stiffness treadmill (VST) suggest that modulating foot-ground contact dynamics during walking may offer an effective new paradigm for gait rehabilitation. How gait adapts to extended perturbations of asymmetrical surface stiffness is still an open question. In this study, we simulated human gait with prolonged asymmetrical changes in ground stiffness using two methods: (1) forward simulation of a muscle-reflex model and (2) optimal control via direct collocation. Simulation results showed that both models could competently describe the biomechanical trends observed in human experiments with a VST which altered the walking surface stiffness for one step. In addition, the simulations revealed important considerations for future experiments studying the effect of asymmetric ground stiffness on gait behavior. With the muscle-reflex model, we observed that although subtle, there was a difference between gait biomechanics before and after the prolonged asymmetric stiffness perturbation, showing the behavioral signature of an aftereffect despite the lack of supraspinal control in the model. In addition, the optimal control simulations showed that damping has a large effect on the overall lower-body muscle activity, with the muscle effort cost function used to optimize the biomechanics increasing 203% between 5 Ns/m and 2000 Ns/m at a stiffness of 10 kN/m. Overall, these findings point to new insights and considerations for advancing our understanding of human neuromotor control of locomotion and enhancing robot-aided gait rehabilitation.

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