Optimal impedance via model predictive control for robot-aided rehabilitation |
| |
Affiliation: | 1. Y?ld?z Technical University, Mechanical Engineering Faculty, Department of Mechatronics Engineering Department, Istanbul, Turkey;2. Yeni Yüzy?l University, Medical Sciences Faculty, Department of Physiotherapy and Rehabilitation, Istanbul, Turkey;1. Department of Electrical and Computer Engineering, University of Michigan, Dearborn, MI, United States;2. Department of Computer Science, California State University, Channel Islands, Camarillo, CA, United States |
| |
Abstract: | This paper proposes an optimal impedance controller for robot-aided rehabilitation of walking, aiming to increase the patient’s activity during the therapy. In an online procedure, the joint torques produced by the patient during the gait is estimated using the generalized momenta-based disturbance observer and the Extended Kalman filter algorithm. At the same time, a model predictive control is performed to obtain the instantaneous optimal stiffness parameters of the robot’s impedance controller, trying to maximize the patient’s active participation by increasing his/her joint torques. In this feasibility study, experiments with a healthy subject, considering a modular lower limb exoskeleton and a set of user’s behaviors, are performed to evaluate the proposed controller. The results show the robot stiffness converges to a value which increases the user’s active participation. |
| |
Keywords: | Rehabilitation robotics Exoskeleton Torque estimation Optimal impedance Model predictive control |
本文献已被 ScienceDirect 等数据库收录! |
|