Computer Cursor Movement with Eye Blink for Paralyzed Individuals

This research study addresses the challenges faced by individuals afflicted with quadriplegia, who often struggle to operate a conventional mouse. Leveraging cutting-edge technology, the system employs Canny-detection, and Face-Mesh-Facial recognition techniques to implement electronic eye movement control for paralyzed individuals. With approximately 40 cases per millions of quadriplegia reported annually, the need for innovative solutions is evident. By accurately identifying and analyzing data points such as pupil shape and size, the system enables seamless navigation of the computer interface. The implementation, executed through PYTHON serial commands in CMD, eliminates the dependency on external assistance, significantly simplifying the lives of those with limb paralysis. This pioneering approach not only offers practical convenience but also underscores the transformative potential of technology in enhancing accessibility and independence for individuals facing physical challenges.