Generating Pathological Gait Patterns via the Use of Robotic Locomotion Models

Abstract

Abstract In this article we explore a feasibility of modeling normal and pathological human gait using a relatively simple five-element model. We use a robust, nonlinear control scheme to regulate the gait pattern of the model. Simulated gait patterns are generated through the use of five constraint relationships that depend on four gait parameters. Two pathological conditions due to muscle weaknesses were simulated by modifying the control torques at the joints. We demonstrate that the model successfully approximates the qualitative and quantitative dynamic trends that were observed in normal and pathological human locomotion.