Dynamics modeling and identification of the human-robot interface based on a lower limb rehabilitation robot

A lower limb rehabilitation robot, namely iLeg, has been developed recently. Since active exercises have been proven to be effective for neurorehabilitation and motor recovery, they are suggested to be implemented on iLeg. To this goal, patients´ motion intention should be recognized. Therefore, a method based on the dynamic model of the human-robot interface (HRI) is designed to recognize the human motion intention. This paper is devoted to modeling and identifying the dynamics of the HRI. Firstly, the dynamic model of the HRI is designed by combining the dynamic models of the human leg and iLeg, where the human leg dynamic model (HLDM) is mainly concerned. By considering the motion trajectories during the rehabilitation exercises provided by iLeg, the human leg can be taken as a manipulator with two degrees of freedom; meanwhile, the joint angles and torques of the human leg can be measured indirectly by using the position and torque sensors mounted on the joints of iLeg. As a result, an 8-parameter HLDM can be designed by using the Lagrangian method. Then, the dynamic model of the HRI is identified by respectively and independently identifying the undetermined dynamic parameters of iLeg and the HLDM, where the dynamic parameters of the HLDM are mainly considered. Finally, the feasibility of the dynamic model of the HRI is validated by experiments.