Dynamic and Uncertainty Analysis of an Exoskeletal Robot to Assist Paraplegics Motion

Dynamic modeling of the lower extremity exoskeletons for assisting paraplegic patient’s mobility has been addressed in this paper. Three distinct phases which manifests to three different dynamic models have been identified for anterior-posterior motion analysis. Design of the proper actuators to compensate the inertial effects of the exoskeleton, joint stiffness and damping torques are estimated using uncertainty analysis. Simulation results show that the anthropometric design of the assistive system was achieved when the mass and inertia of the exoskeleton leg segments are increased up to 60% of the corresponding human leg segments. A dynamic model based on CGA data employing neuro-fuzzy inference system with an optimum distribution of the membership functions and minimum fuzzy rule bases was introduced for control purposes