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Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis

This paper presents the study of sound frequency characteristic based on Electroencephalography (EEG) signals. The study includes feature extraction of the EEG signals with respect to different sound frequencies, covering low frequency (40 Hz), mid-range frequency (5000 Hz), and high frequency (1500...

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Main Authors: Sudirman, Rubita, A. K. Chee, Wan Daud, Wan Mohd Bukhari
Format: Article
Language:English
Published: IEEE XPLORE 2010
Online Access:http://eprints.utem.edu.my/id/eprint/4534/1/05489225.pdf
http://eprints.utem.edu.my/id/eprint/4534/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5489225
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spelling my.utem.eprints.45342022-01-06T12:50:46Z http://eprints.utem.edu.my/id/eprint/4534/ Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis Sudirman, Rubita A. K. Chee Wan Daud, Wan Mohd Bukhari This paper presents the study of sound frequency characteristic based on Electroencephalography (EEG) signals. The study includes feature extraction of the EEG signals with respect to different sound frequencies, covering low frequency (40 Hz), mid-range frequency (5000 Hz), and high frequency (15000 Hz). Human brain activities are expected to be different when exposed to different sound frequencies, and can be shown through EEG signals. In this paper, EEG signal characterization is done using Fast Fourier Transform (FFT), moving average filters, and simple artefact filtering with reference EEG data per individual. Based on the characteristics of the EEG signal, the sound frequency can be categorized and identified using the proposed method. IEEE XPLORE 2010-05-28 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/4534/1/05489225.pdf Sudirman, Rubita and A. K. Chee and Wan Daud, Wan Mohd Bukhari (2010) Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis. Mathematical/Analytical Modelling and Computer Simulation (AMS). pp. 221-226. ISSN 978-1-4244-7196-6 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5489225 DOI 10.1109/AMS.2010.52
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description This paper presents the study of sound frequency characteristic based on Electroencephalography (EEG) signals. The study includes feature extraction of the EEG signals with respect to different sound frequencies, covering low frequency (40 Hz), mid-range frequency (5000 Hz), and high frequency (15000 Hz). Human brain activities are expected to be different when exposed to different sound frequencies, and can be shown through EEG signals. In this paper, EEG signal characterization is done using Fast Fourier Transform (FFT), moving average filters, and simple artefact filtering with reference EEG data per individual. Based on the characteristics of the EEG signal, the sound frequency can be categorized and identified using the proposed method.
format Article
author Sudirman, Rubita
A. K. Chee
Wan Daud, Wan Mohd Bukhari
spellingShingle Sudirman, Rubita
A. K. Chee
Wan Daud, Wan Mohd Bukhari
Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis
author_facet Sudirman, Rubita
A. K. Chee
Wan Daud, Wan Mohd Bukhari
author_sort Sudirman, Rubita
title Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis
title_short Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis
title_full Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis
title_fullStr Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis
title_full_unstemmed Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis
title_sort modeling of eeg signal sound frequency characteristic using time frequency analysis
publisher IEEE XPLORE
publishDate 2010
url http://eprints.utem.edu.my/id/eprint/4534/1/05489225.pdf
http://eprints.utem.edu.my/id/eprint/4534/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5489225
_version_ 1724077879540580352
score 13.211869

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