Selecting Control Menu on Electric Wheelchair Using Eyeball Movement for Difable Person

Fitri Utaminingrum - Brawijaya University
I Komang Somawirata - National Institute of Technology (ITN Malang)
Gusti Pengestu - Bina Nusantara University
Tipajin Thaipisutikul - Mahidol University
Timothy Shih - National Central University


Citation Format:



DOI: http://dx.doi.org/10.30630/joiv.7.1.1011

Abstract


The number of people with disabilities and strokes in each country always 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 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 pro-posed 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). Our proposed method can detect five gaze directions and select four menus on the display monitor. The mean accuracy of our proposed method to detect eye movements for each gaze is 88.6%.

Keywords


Disabilities, Detection, Eyeball Movements, Eyeball Movements, Dynamic Line Sector Coordinate

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