Human Mental Stage Interpretation Based on the Analysis of Electroencephalogram (EEG) Signals

Norizam, Sulaiman and Mahfuzah, Mustafa and Fahmi, Samsuri and Siti Armiza, Mohd Aris and Nik Izzat Amirul, Mohd Zailani (2024) Human Mental Stage Interpretation Based on the Analysis of Electroencephalogram (EEG) Signals. In: Intelligent Manufacturing and Mechatronics, Lecture Notes in Networks and Systems. 4th International conference on Innovative Manufacturing, Mechatronics and Materials Forum, iM3F2023 , 07 – 08 August 2023 , Pekan, Malaysia. pp. 225-237., 850. ISSN 2367-3389 ISBN 978-981-99-8819-8

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Abstract

There are various stages in human mental development. Among them are consciousness, drowsiness, and light sleep. These human mental stages and conditions can be affected by human emotions (Ali et al. in Wirel Pers Commun 125:3699–3713, 2022; Katmah et al. in Sensors 21(15):5043). Hence, human brainwaves or electroencephalogram (EEG) signals can be employed to analyze and interpret the development of human mental stage. In this research, 1-channel EEG device is employed to measure neural electrical activity from five people as they are engaged in three different cognitive exercises such as playing a video game, reading a book, and watching a movie. EEG signals are analyzed in LabVIEW software to reveal the unique features which are able to describe various human stages. The EEG power spectrum in terms of mean and standard deviation for each EEG frequency band (theta band, alpha band, and beta band) is computed. Then, the k-nearest neighbor (k-NN) classifier is employed to discover the best feature that is capable to indicate status of human mental stage. The findings of the study demonstrated that the mean EEG feature with the training and testing ratio of k-NN classifier at 80:20 could detect and categorize human stages with the classification accuracy of 81.57%. Meanwhile, LabVIEW graphical user interface (GUI) and block diagram are constructed to display the analyses of human stages of each subject for the specified human stage activities. In addition, a device is built to indicate human mental stage in an off-line manner.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Classification; EEG power spectrum; Human mental stages; LabVIEW GUI
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Miss Amelia Binti Hasan
Date Deposited:	23 May 2024 06:58
Last Modified:	23 May 2024 06:58
URI:	http://umpir.ump.edu.my/id/eprint/41349
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