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All Journal JOIV : International Journal on Informatics Visualization Jurnal Mnemonic Jurnal Bumigora Information Technology (BITe) Journal of Electrical Engineering and Computer (JEECOM) ALINIER: Journal of Artificial Intelligence & Applications Jurnal Fortech SinarFe7 Magnetika: Jurnal Mahasiswa Teknik Elektro Nucleus Journal Jurnal FORTECH
I Komang Somawirata
Teknik Elektro, Institut Teknologi Nasional Malang
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Journal : JOIV : International Journal on Informatics Visualization

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Selecting Control Menu on Electric Wheelchair Using Eyeball Movement for Difable Person Fitri Utaminingrum; I Komang Somawirata; Gusti Pengestu; Tipajin Thaipisutikul; Timothy K. Shih
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1011

Abstract

Each country's number of people with disabilities and strokes increases yearly. Hand defects and stroke make them have limitations in doing activities. It caused their hand has paralyzed. Hence, they find it difficult to do daily activities, such as running a wheelchair, choosing a menu on the screen display, and so on. One solution offered is utilizing eye movement as a navigation tool that can replace the role of the user's hand, so they can run a wheelchair independently or choose a menu selection on display by themselves through the movement of their eyes. Detection of eyeball movements in this study only utilizes a camera as a sensor mounted in front of the user. So that it is more practical and easier to use than if we have to pair an electrooculography sensor in the area around the user's eyes. This research proposed a new approach to detect the five gazes (upward, downward, leftward, rightward, and forward) of the eyeball movements by using Backpropagation Neural Network (BPNN) and Dynamic Line Sector Coordinate (DLSC). Line Sector Coordinate is used to detect the eyeball movement based on the pupil coordinate position. The eyeball movement direction was analyzed from four lengths of a line. Our proposed method can detect five gaze directions that can be used for selecting four menus on the display monitor. The mean accuracy of our proposed method to detect eye movements for each gaze is 88.6%.
Co-Authors Achmad Danang Subekti aditya_alfiansyah Alfa Z Fikri, Mohammad Aryuanto Soetedjo Awan Uji Krismanto B Sulistiawati, Irrine Bagus Saputra Dyah Ayu Girindraswari Edo Mikrado, Juan Fahrudi Setiawan, Ahmad Fitri Utaminingrum Gusti Pengestu heldi bafadhal, Heldi I Gede Putu Nanda Udayana Ifsul Hidayat Rusmuriadi Ilmi, Muhammad Akmal Irmalia Suryani Faradisa Irrine B Sulistiawati Irrine Budi S Juan Edo Mikrado Jumadil Awal Luis A. M. Dos Santos Lukman Fajar Andri F M. Ibrahim Ashari M. Ibrahim Ashari M. Ibrahim Ashari Michael Ardita Mohammad Alfa Z Fikri Mohammad Syafa' Karim Amrulloh Muhammad Sakhalish Zayyan Muhammad Sya’roni Muhammad Taufikurrachman Nicola Natha Teopilus Ginting Obed Dyan Winarto Purwoko Suryo Wibowo Purwoko Suryo Wibowo Qurrotun Ainun Najib Radimas Putra Muhammad Davi Labib Rakhman, Aditya Djulqodri Refsi Hanindya Abdillah Reynaldi Ramlan Roichan Nafis Sakhalish Zayyan, Muhammad Septa Yudha Prasetya Setiawan, Katon Bagus Sotyohadi Sotyohadi , Sotyohadi Timothy K. Shih Tipajin Thaipisutikul Trio Wahyu Saputro Wahyu Krisna Wijaya Wahyu Surya Dewa Wilhan Jechovanda Susant0 Yoga Prasetyo