Eyeblinktotext: Empowering Communication for Paralyzed Patients Through Eye Blink Detection Using Opencv

Numerous individuals worldwide live with physical disabilities, such as paralysis, which hinders their ability to communicate effectively. Those who have experienced accidents or trauma also face communication challenges. Paralysis, in particular, results in muscle weakness affecting the hands, feet, or voice, making it challenging for patients to carry out voluntary movements and communicate their needs. The proposed system is designed to help physically disabled individuals to translate their intentions into text by utilizing eye-blinks to interact with computing systems. Experimental results indicate an average detection accuracy of 79.44 %. Given that paralyzed individuals retain the ability to move their eyes, the natural motion of an eyeblink can be effectively used as a medium to convey information.