Eye Gaze Control for Android Operating System Smartphones for Arm-disabled Individuals

The primary objective of this study is to develop algorithms for controlling a cursor on mobile devices, such as smartphones or tablets, utilizing eye-tracking techniques. The aim is to provide assistance to individuals with impairments in arm, hand, or finger movements. To achieve this goal, the researchers employed digital image processing theories, including the Haar cascade classifier and region of interest detection. Additionally, they utilized the OpenCV library and Internet of Things (IoT) technology to compute eye positions and detect eye movements. The control of the cursor was simulated using a microcontroller. The findings of the research demonstrate the program's capability to accurately detect facial features and locate eye positions. Furthermore, the system effectively controls the cursor in accordance with user preferences. In the experimental phase, the system achieved an accuracy rate of 78%.