The Classification of Electrooculogram (EOG) through the application of Linear Discriminant Analysis (LDA) of selected time-domain signals

Farhan Anis, Azhar and Mahfuzah, Mustafa and Norizam, Sulaiman and Rashid, Mamunur and Bari, Bifta Sama and Islam, Md Nahidul and Hasan, Md Jahid and Nur Fahriza, Mohd Ali (2022) The Classification of Electrooculogram (EOG) through the application of Linear Discriminant Analysis (LDA) of selected time-domain signals. In: Lecture Notes in Electrical Engineering; Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2020 , 6 August 2020 , Gambang, Kuantan. pp. 583-591., 730 (262829). ISSN 1876-1100 ISBN 978-981334596-6

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Abstract

Recently, Human Computer Interface (HCI) has been studied extensively to handle electromechanical rehabilitation aids using different bio-signals. Among various bio-signals, electrooculogram (EOG) signal have been studied in depth due to its significant signal pattern stability. The primary goal of EOG based HCI is to control assistive devices using eye movement which can be utilized to rehabilitate the disabled people. In this paper, a novel approach of four classes EOG has been proposed to investigate the possibility of real-life HCI application. A variety of time-domain based EOG features including mean, root mean square (RMS), maximum, variance, minimum, medium, skewness and standard deviation have been explored. The extracted features have been classified by the linear discriminant analysis (LDA) with the classification accuracy of training accuracy (90.43%) and testing accuracy (88.89%). The obtained accuracy is very encouraging to be utilized in HCI technology in the purpose of assisting physically disabled patients. Total 10 participants have been contributed to record EOG data and the range between 21 and 29 years old.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Electrooculogram; EOG; HCI; Human computer interface; Machine learning
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures
Faculty/Division:	Institute of Postgraduate Studies College of Engineering Faculty of Electrical and Electronic Engineering Technology Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	03 Jan 2024 00:49
Last Modified:	03 Jan 2024 00:49
URI:	http://umpir.ump.edu.my/id/eprint/39841
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