Researching brain-computer interfaces for enhancing communication and control in neurological disorders

Abstract

The paper provides a comprehensive exploration of brain-computer interfaces (BCIs) and their application in addressing communication and control challenges in neurological disorders like Amyotrophic Lateral Sclerosis (ALS), locked-in syndrome, Parkinson’s disease, and Spinal Cord Injury. It traces BCI advancements from foundational information theory principles to their current state. Neurological disorders severely impact communication and control abilities, with ALS causing muscle weakness and paralysis, and locked-in syndrome confining individuals within paralyzed bodies while maintaining cognitive functions. BCIs decode brain signals, enabling control of external devices like computers, offering hope for restoring communication and control in affected individuals. Employing data analysis and visualization techniques, this study evaluates BCI performance in improving communication and control across various disorders. Matplotlib generates informative graphs and performance metrics, quantifying BCI efficacy for users with differing motor impairments. The findings highlight BCI transformative potential, guiding clinicians and researchers toward personalized solutions for diverse patient populations. This research underscores the necessity for continued innovation and exploration in BCI technology, envisioning a more inclusive and adaptive future for individuals with neurological disorders