Neuro-Adaptive Feedback Control in Wearable Robotics for Stroke Rehabilitation: Integrating EEG Signals with Cable-Driven Exoskeletons

Abstract

Neuro-adaptive control systems and wearable robots have brought a revolution to stroke rehabilitation. The use of cable-driven exoskeletons based on electroencephalography (EEG) signals is one of the most significant innovations in the personalization of therapy and the improvement of motor recovery among stroke patients. This paper concentrates on the interaction between EEG-based brain-computer interfaces and adaptive control strategies of wearable robotics, and the ways they are used to address post-stroke motor rehabilitation. It discusses velocity-free neuro-adaptive control, neural optimization through observers, and leader-follower models of cooperation, which contribute to adaptive and customized robotic assistance. This paper further addresses the advantages and limitations of cable-based systems with lightweight and compliant actuation, suggesting their applicability to clinical and home-based therapy settings. The review demonstrates the promise of neuro-adaptive, EEG-controlled exoskeletons to rehabilitate motor performance and quality of life in stroke survivors by assessing current trends and providing future directions for the technology.