Fuzzy Logic based Kinematics Mathematical Modelling of Lower Limb Exoskeleton for Rehabilitation in Stroke Patients

This study presents a fuzzy-logic based kinematics mathematical modeling for a lower limb exoskeleton utilized in post-stroke rehabilitation. The proposed system implements adaptive fuzzy control to improve rehabilitation outcomes through an adaptive actuation approach based on patient movement patterns. The exoskeleton achieves accurate motion control through its combination of advanced kinematic and dynamic modeling techniques which leads to enhanced rehabilitative outcomes. The system processes real-time biomechanical feedback to develop individualized treatments that maximize both safety and effective therapy while maintaining comfort throughout the session. The system provides both excellent ergonomics and low weight which together promote comfortable use without causing user fatigue. The proposed approach performs better at improving gait and motor function than standard rehabilitation techniques according to comparative evaluations. Experimental studies have verified the effectiveness of this system by showing better mobility alongside better patient healing outcomes during clinical evaluations. This research promotes intelligent rehabilitation technology advancement through a reliable patient-oriented solution which can achieve better performance after machine learning optimization for stroke rehabilitation applications.