Review on Mouse Control Using Eye-Tracking: Integrating CNN and NLP for Intelligent Human-Computer Interaction

Mouse control using eye-tracking technology is an advanced human-computer interaction method with broad applications, particularly in assisting individuals with motor impairments. In this study, Convolutional Neural Networks (CNNs) are utilized to process eye image data, while Natural Language Processing (NLP) analyzes input patterns and predicts cursor movements. The proposed system accurately detects gaze direction and blinking, allowing for seamless mouse cursor control and text prediction using word-completion models. Experimental results demonstrate high precision in eye movement recognition and user interaction with computer systems. This technology has promising applications in medical fields, gaming, and assistive systems for individuals with special needs.

کلیدواژه ها:

Eye-tracking ، Convolutional Neural Networks ، Natural Language Processing ، Computer Vision