Clinical Research Directory

Neurofeedback-Guided BCI Motor Imagery for Upper-Limb Recovery in Chronic Stroke

Stroke can lead to long-term impairment of upper-limb function, particularly in the chronic phase, where recovery is often limited. Brain-computer interface (BCI) systems combined with motor imagery (MI) are emerging as promising neurorehabilitation approaches. Providing real-time neurofeedback during MI may enhance motor recovery by promoting use-dependent neuroplasticity; however, evidence in individuals with chronic stroke remains limited. This controlled pilot study aims to evaluate the feasibility and preliminary effects of an EEG-based BCI neurofeedback intervention combined with MI and physiotherapy on upper-limb motor function and brain activation patterns in individuals with chronic stroke. Participants are assigned to either an experimental group receiving MI with real-time EEG-based neurofeedback or a control group receiving MI with sham feedback, alongside a standardized four-week physiotherapy program. Motor function is assessed using validated clinical measures, including the Action Research Arm Test, Fugl-Meyer Assessment, Motor Assessment Scale, and grip strength, with changes interpreted according to clinically meaningful thresholds. Neurophysiological changes are explored through EEG-based measures of brain symmetry and task-related functional MRI. It is expected that participants receiving real neurofeedback will show greater improvements in upper-limb function and more adaptive brain activation patterns compared to those receiving sham feedback. Findings from this study will help determine the feasibility of this approach and inform the design of larger trials to evaluate its effectiveness in chronic stroke rehabilitation.

Clinical validatiOn of an AI-based DEcision Support System for Robotic Upper Limb Rehabilitation in Patients With Stroke. A CO-AIDER Study.

The goal of this clinical trial is to validate an artificial intelligence-based decision support system (AI-DSS) for robotic rehabilitation in participants with stroke. The study aims to answer the following questions: * Can the AI-DSS support therapists in setting therapy parameters and adapting personalized robotic rehabilitation programs effectively? * Can AI-supported robotic rehabilitation improve upper limb function, activities of daily living (ADL), cognitive function, and quality of life compared with standard therapist-guided robotic rehabilitation? Researchers will compare two groups: * Robotic rehabilitation supported by the AI-DSS (CO-AIDER); * Robotic rehabilitation with parameters set by therapists (control group). Participants will: * Receive robotic rehabilitation for the upper limb, either guided by the AI-DSS or by therapists; * Be monitored throughout the program, with therapy parameters adjusted according to their progress; * Complete assessments to evaluate changes in upper limb function, activities of daily living, cognitive function, and quality of life. The study will also evaluate the usability and acceptability of the AI-supported robotic system as perceived by participants and clinical staff, and will include a cost-effectiveness analysis of the two interventions.

Upper Limb Functional Index

To translate and validate the Upper Limb Functional Index into Albanian for use in the Albanian-speaking population.