The Control of an Exoskeleton and The Reduction of Interaction Force Using Human Intent Detection by EMG Signals and Torque Estimation

Abstract

Disability and motor disorders are some of the problems that people may face due to some factors such as accident, spinal cord injuries, brain damage, and the presence of a problem in neurological commands due to stroke. One of the proposed methods for solving the problems of these people is the use of exoskeletons to generate movement. The main goal of this paper is the control of Sharif Exoskeleton Robot and the reduction of interaction force between user and robot by using human intent detection. This goal is done by estimating the knee torque of one degree of freedom in a swing phase using Hill model based on the EMG data from the thigh muscles. Accordingly, the calibration algorithm is implemented in order to use Hill model and identify the parameters by genetic algorithm. The interaction force between the user and the robot is reduced by about 25% using Hill's torque to detect the intent; in addition, the torque required for moving the user's knee is reduced obviously.