Enhancement of filter design and EEG power ratio features in IQ pattern analysis / N. H. R. Azamin ...[et al.]

Azamin, N. H. R. and Jahidin, A. H. and Megat Ali, M. S. A. and Taib, M. N. (2017) Enhancement of filter design and EEG power ratio features in IQ pattern analysis / N. H. R. Azamin ...[et al.]. Journal of Electrical and Electronic Systems Research (JEESR), 11: 7. pp. 38-44. ISSN 1985-5389

Abstract

Power ratio is an established electroencephalogram
(EEG) feature that has been used to study cognitive performance.
Essentially, the technique computes the normalized power for
each of the brainwave components prior to pattern analysis. The
method however, is subject to further improvement as previous
pre-processing approach rely on low-order filter designs. As a
result, the obtained features are less accurate due to the presence
of spectral leakages within the pre-processing element. Hence,
this paper propose an improved extraction algorithm based on
the use of high-order equiripple filters. Pre-existing intelligence
quotient data are acquired from 50 samples and their EEG is
recorded from the left pre-frontal cortex. The power ratio
features are obtained from the energy spectral density of theta,
alpha and beta bands. While results maintain conformity with
the Neural Efficiency Hypothesis of human intelligence,
comparative study shows that with equiripple filters, the revised
power ratio is more suitable for IQ pattern analysis.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Azamin, N. H. R.
hidayahazamin254@gmail.com
Jahidin, A. H.
UNSPECIFIED
Megat Ali, M. S. A.
UNSPECIFIED
Taib, M. N.
UNSPECIFIED
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electronics > Microelectromechanical systems
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Journal or Publication Title: Journal of Electrical and Electronic Systems Research (JEESR)
UiTM Journal Collections: UiTM Journal > Journal of Electrical and Electronic Systems Research (JEESR)
ISSN: 1985-5389
Volume: 11
Page Range: pp. 38-44
Keywords: EEG, equiripple filter, intelligence, power ratio
Date: December 2017
URI: https://ir.uitm.edu.my/id/eprint/63014
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