AI-Driven Neural Eye Cursor For Paralyzed Patients

Neural Eye Cursor system powered by AI, aimed at offering hands-free computer interaction for people with physical disabilities, especially those who are paralyzed. The system utilizes deep learning algorithms for gaze estimation and eye movement tracking to convert visual attention into accurate cursor control in the Windows operating system. Convolutional neural networks (CNNs) are employed by the core framework to analyze real-time video input from a standard webcam, determining gaze direction and correlating it with screen coordinates. Click functions are realized through the use of blink detection and dwell-time thresholds, so that peripheral input devices are not required. Results from experiments show a high level of accuracy 0.96 and responsiveness 0.97, even when lighting conditions change and users move their heads.