Rehabilitation robot following motion control algorithm based on human behavior intention

Abstract

In response to the current problem of low intelligence of mobile lower limb motor rehabilitation aids. This paper proposes an intelligent control scheme based on human movement behavior in order to control the rehabilitation robot to follow the patient’s movement. Firstly, a multi-sensor data acquisition system is designed according to the rehabilitation needs of the patient and the movement characteristics of the human body. A mathematical model of movement behavior is then established. By analyzing and processing motion data, the change in the center of gravity of the human body and the behavior intention signal are derived and used as a control command for the robot to follow the human body’s movement. Secondly, in order to improve the control effect of rehabilitation robot following human motion, an adaptive radial basis function neural network sliding mode controller (ARBFNNSMC) is designed based on the robot dynamic model. The adaptive adjustment of switching gain coefficient is performed by radial basis function neural network. The controller can overcome the influence caused by the change of robot control system parameters due to the fluctuation of the center of gravity of human body, enhance the adaptability of the system to other disturbance factors, and improve the accuracy of following human body motion. Finally, the motion following experiment of the rehabilitation robot is performed. The experimental results show that the robot can recognize the motion intention of human body and perform the training goal of following different subjects to complete straight lines and curves. The correctness of human motion behavior model and robot control algorithm is verified, which shows the feasibility of the intelligent control method proposed in this paper.

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Autonomous motion and control of lower limb exoskeleton rehabilitation robot

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A multi-degree-of-freedom reconfigurable ankle rehabilitation robot with adjustable workspace for post-stroke lower limb ankle rehabilitation

“…Stroke is an acute cerebrovascular disorder characterized by a high incidence rate, elevated mortality, and a range of complications (Feigin et al, 2021;Markus, 2022). In recent years, the issue of poststroke motor dysfunction has become increasingly pressing due to the growing number of stroke patients, with data indicating that approximately 65% of survivors require rehabilitation (Miao et al, 2023). Traditional rehabilitation is labor-intensive, and associated with limitations such as the inability to quantify rehabilitation data, strained medical resources, inconsistent training, and high costs (Gittler and Davis, 2018;Gao et al, 2023).…”