Closed-Loop Brain-Controlled Exoskeleton System with a Hybrid Model for Stroke Rehabilitation

Stroke (Cerebrovascular Accident, CVA) is one of the diseases with the greatest impact on human health, particularly due to the neurological dysfunctions that often follow, such as upper or lower limb paralysis, foot drop, muscle weakness, and cognitive impairment, which significantly affect patients' daily lives. Existing research indicates that the first three months after a stroke is the "golden period" for treatment, during which rehabilitation training can greatly improve a patient's quality of life and promote neuroplasticity. However, some stroke patients are unable to engage in active rehabilitation training due to physical limitations and can only rely on passive rehabilitation methods. To address this issue, this study proposes a closed-loop brain-controlled exoskeleton system based on brain-computer interface (BCI) technology to enhance rehabilitation in post-stroke patients. This study designed a brain-controlled exoskeleton system consisting of open-loop control and closed-loop feedback. In the open-loop control stage, patients control the exoskeleton's standing, walking, and sitting commands through electroencephalogram (EEG) signals; in the closed-loop feedback stage, the rehabilitation effect is evaluated through brainwave analysis and clinical evaluation. Experimental results demonstrate that the system can effectively assist patients in regaining motor control during training and elicit significant neurophysiological responses in the preparation and execution stages of movement. Additionally, clinical evaluation results showed that patients made notable progress in muscle strength and functional recovery. Although the study sample size was small (n=3) and the treatment period was short, the study highlights the potential application of brain-controlled exoskeleton systems in post-stroke rehabilitation. Future studies should expand the sample size and include long-term follow-up to further assess its clinical feasibility and long-term effects.