Eye Tracking for Communication in Locked-In Syndrome Patients

Individuals with mobility impairments, including those affected by conditions such as Locked-in Syndrome (LIS), ALS, or stroke, face significant challenges in communication due to the loss of voluntary muscle control. This research presents an advanced eye- tracking system that enables individuals with restricted mobility to communicate using eye blinks. The proposed system leverages computer vision, artificial intelligence, and machine learning techniques to detect and interpret eye movements, converting them into textual communication. By integrating Haar cascades and adaptive language modeling, the system ensures precise detection and real-time processing, even on low-end devices. Additionally, the study highlights challenges such as accuracy, affordability, and accessibility while proposing solutions to improve usability. The research aims to empower individuals with mobility impairments, enhancing their independence and fostering social inclusion through assistive technology.