Open AccessProsthetic hand with 2-dimensional motion based EOG signal control
Author(s) -
M. R. Pratomo,
Bambang Guruh Irianto,
Triwiyanto Triwiyanto,
Bagus Budi Utomo,
Endang Dian Setioningsih,
Dyah Titisari
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/850/1/012024
Subject(s) - electrooculography , amplifier , computer science , filter (signal processing) , microcontroller , computer vision , instrumentation amplifier , signal (programming language) , artificial intelligence , bluetooth , eye movement , computer hardware , engineering , differential amplifier , electrical engineering , telecommunications , wireless , programming language , cmos
A prosthetic hand is an artificial device that resembles a human hand which can help the human with a physical disability. Previously, the development of a prosthetic hand is designed in various method, from passive to bionic. Electrooculography (EOG) is a technique for measuring potential differences between the front (positive pole formed by the cornea) and the back (negative pole formed by the retina) of the eyeball which can be used to detect eye movements. The purpose of this study is to design a prosthetic hand with two degrees (2D) of freedom using EOG based control. This system consists of electrodes, EOG amplifier, Bluetooth transmitter-receiver, servo motors, and hand prosthetics. In this study, the system will recognize the eye movements, namely front, right, left, up, and down. The system will recognize the motion based on a threshold value. In the hardware implementation, the system was composed of five electrode sensors which installed around the eye, instrumentation amplifier, high pass filter, low pass filter, noninverting amplifier, summing amplifier, a notch filter circuit, and Arduino UNO microcontroller. In EOG data acquisition, this study involved ten healthy subjects. After the evaluation with five trial for each motion, the error for each eye movement is 0%, 0%, 36%, 4% and 16% for right, left, top, bottom, and front, respectively. This study provided an alternative method to control a prosthetics hand with good performance.