Eye Movement Controlled Smart Wheelchair

This paper presents the design and implementation of an Eye Movement Controlled Smart Wheelchair aimed at assisting individuals with severe motor disabilities. The system enables hands-free navigation by interpreting real-time eye movements as directional commands. A camera-based eye tracking mechanism is implemented using OpenCV to detect gaze direction. The system is powered by a Raspberry Pi, which processes eye movement data and translates it into movement commands such as forward, backward, left, right, and stop. To ensure user safety, ultrasonic sensors are integrated for obstacle detection and collision avoidance. The system automatically halts movement when obstacles are detected within a predefined range. The proposed system combines computer vision, embedded systems, and sensor-based automation to provide a cost-effective, reliable, and user-friendly assistive mobility solution. Experimental results demonstrate high accuracy and real-time performance, making it suitable for smart healthcare applications.