Abstract

In the design of rehabilitation robots aiming at people with special needs (i.e., elderly, people with impairments, or people with disabilities), the human-robot interface (HRI) is considered to be one of most difficult and important parts. It directly determines the patient safety, operation convenience and rehabilitation effectiveness of the whole system. The interface design mainly consists of two main parts, that is, hard and soft human-robot interface design that are labeled hHRI and sHRI respectively in the paper. hHRI is the physical human-robot interaction which transfers the power from robot to the patient or vice-versa. And sHRI is mainly a control interface between human and robot. After the robot mechanical structures being established, system function and performance is largely decided by sHRI. In the paper, in order to be able to do continuous control for robot motion and generate the desired supporting torque for patients with the actuation of the robot, the present work proposes a new sHRI that based on surface electromyography (sEMG) and human neuro-musculo-skeletal model. It can transform the body's own neural command signal of sEMG recordings to kinematic variables that were used to control the rehabilitation robot. Under the work of sHRI, rehabilitation robot can offer assistance to patients during rehabilitation by guiding motions on correct training rehabilitation trajectories, or give force support to be able to perform certain motions at all. The mechanism is compelling from the standpoint of biomechanical analysis of human motion as well as the synthesis of artificial control. It may lead to seamless integration and an intuitive control of the controlled robot.

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