Machine Learning Approach Enhancing Rehabilitation Exoskeleton Performance for Stability Analysis and Trajectory Tracking with RBF-Neural Sliding Mode Control

Abstract

The purpose of this research was to study the effectiveness of the application of the machine learning-driven approach using a robotic exoskeleton with Radial Basis Function control for higher quality and more efficient rehabilitation. The results of the analysis of gait parameters, joint angles, and training techniques allowed researchers to draw important conclusions about the capacity to use exoskeleton technology in real life and the potential benefits of the approach. To study the problem, two groups of people were selected, one of which underwent the procedure of rehab with the help of a robotic exoskeleton, while the other followed traditional training. Gait analysis results revealed considerable improvement of motion parameters, including stride length, walking speed, cadence as well as gait characteristics for exoskeleton users. The analysis of joint angles concluded that training with the help of the robotic exoskeleton brought increased flexibility of motion, more significant amplitude of movement in the hip and knee joints. Overall, the Radial Basis Function control system allowed the exoskeleton to respond better to the data received from the sensors and adapt to the motion of the user more adequately. This, in turn, made it possible to ensure the provision of the required level of assistance to allow exoskeleton users to achieve the results of a higher quality in rehabilitation in the final analysis in comparison to traditional rehab users. The results of the study suggest the outstanding potential of exoskeleton technology. The technology and its combination with machine learning and robotics can turn the niche of rehabilitation into something new. As a result, residents with disabilities, particularly those who have a partial paralysis will be provided with essential new opportunities to become more mobile. They will consequently boost their life quality.