Stabilization of a three-dimensional limit cycle walking model through step-to-step ankle control

Unilateral, below-knee amputation is associated with an increased risk of falls, which may be partially related to a loss of active ankle control. If ankle control can contribute significantly to maintaining balance, even in the presence of active foot placement, this might provide an opportunity to improve balance using robotic ankle-foot prostheses. We investigated ankle- and hip-based walking stabilization methods in a three-dimensional model of human gait that included ankle plantarflexion, ankle inversion-eversion, hip flexion-extension, and hip ad/abduction. We generated discrete feedback control laws (linear quadratic regulators) that altered nominal actuation parameters once per step. We used ankle push-off, lateral ankle stiffness and damping, fore-aft foot placement, lateral foot placement, or all of these as control inputs. We modeled environmental disturbances as random, bounded, unexpected changes in floor height, and defined balance performance as the maximum allowable disturbance value for which the model walked 500 steps without falling. Nominal walking motions were unstable, but were stabilized by all of the step-to-step control laws we tested. Surprisingly, step-by-step modulation of ankle push-off alone led to better balance performance (3.2% leg length) than lateral foot placement (1.2% leg length) for these control laws. These results suggest that appropriate control of robotic ankle-foot prosthesis push-off could make balancing during walking easier for individuals with amputation.