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Analysis of EEG features for brain computer interface application

Rashid, Mamunur and Norizam, Sulaiman and Mahfuzah, Mustafa and M. S., Jadin and M. S., Najib and Sabira, Khatun and Bari, Bifta Sama (2019) Analysis of EEG features for brain computer interface application. In: 5th International Conference on Electrical, Control and Computer Engineering (INECCE 2019), 29-30 July 2019 , Swiss Garden Kuantan. pp. 1-12.. (Unpublished)

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Abstract

Brain-Computer Interface (BCI) or Human-Machine Interface (HMI) is now becoming vital engineering and technology field which applies electroencephalography (EEG) signal to provide Assistive Technology (AT) to humans. This paper presents the analysis of EEG signals from various human cognitive or mental states to determine the suitable EEG features that can be employed in BCI field. Here, EEG features in term of power spectral density, log energy entropy and spectral centroid are selected to recognize human men- tal or cognitive state from 3 different exercises; i) solving math problem, ii) playing game and iii) do nothing (relax). The average power spectral density, average log energy entropy and average spectral centroid of EEG Alpha and Beta band for three mental exercises are calculated in order to determine the best features that can be used for BCI application. The results of the research shows that the EEG features in term of power spectral density, log energy en- tropy and spectral centroid can be used to indicate the change in cognitive states after exposing human to several cognitive exercises.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Brain-Computer Interface (BCI); Electroencephalography (EEG); EEG Feature; Power Spectral Density (PSD)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 23 Dec 2019 07:52
Last Modified: 20 Jan 2020 02:28
URI: http://umpir.ump.edu.my/id/eprint/26561
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