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

Conference proceedings article


Authors/Editors


Strategic Research Themes


Publication Details

Author listThanatchaphan Phetcharat; Thittaporn Ganokratanaa; Mahasak Ketcham

PublisherInstitute of Electrical and Electronics Engineers Inc.

Publication year2024

ISBN979-835037905-1

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85203582381&doi=10.1109%2fITC-CSCC62988.2024.10628138&partnerID=40&md5=19e45e5b2885ee9f5f596f63652ab41d

LanguagesEnglish-Great Britain (EN-GB)


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Abstract

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%. © 2024 IEEE.


Keywords

Android Operating System SmartphonesArm-disabled Individuals sEye Gaze Control


Last updated on 2024-26-10 at 00:00