Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution

Wavelet transform (WT) is one of the favored tools for analyzing the biomedical signals. This study describes the identification of Electrooculography (EOG) signals of eye movement potentials by using wavelet transform which gives a lot of information than Fourier transform. The efficiency of wavele...

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Main Authors: W. Daud, W. M. Bukhari, Sudirman, R, Omar, Camallil
Format: Article
Language:English
Published: IEEE-AICIT KOREA 2012
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Online Access:http://eprints.utem.edu.my/id/eprint/6049/1/ICISS01-777026TO.pdf
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spelling my.utem.eprints.60492022-01-20T15:45:00Z http://eprints.utem.edu.my/id/eprint/6049/ Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution W. Daud, W. M. Bukhari Sudirman, R Omar, Camallil T Technology (General) Wavelet transform (WT) is one of the favored tools for analyzing the biomedical signals. This study describes the identification of Electrooculography (EOG) signals of eye movement potentials by using wavelet transform which gives a lot of information than Fourier transform. The efficiency of wavelet transform is to distribute the potential signal of energy with the change of time in different frequency bands. This will show the characteristic of the signals since energy is a considerable physical variable in signal analysis. The EOG signals are captured using electrodes placed on the forehead around the eyes to record the eye movements. The wavelet algorithm is used to determine the characteristic of eye movement waveform. This technique is adopted because it is a non-invasive, inexpensive and accurate. The new technology enhancement has allowed the EOG signals captured using the EEG Neurofax-9200. The recorded data is composed of an eye movement toward four directions that is upward, downward, left and right involving 15 subjects. The proposed analysis for each eyes signal is analyzed by using WT by comparing the energy distribution with the change of time and frequency of each signal. A wavelet scalogram is plotted to display different percentages of energy for each wavelet coefficient towards different movement. In conclusion, it is proved that the different EOG signals exhibit approximately differences in signals energy with their corresponding scales such as leftward with scale 6 (8 - 16 Hz), rightward with scale 8 (2 - 4 Hz), downward with scale 9 (1 - 2 Hz) and upward with scale 7 (4 - 8 Hz). Analysis of variance statistically proved that there is 99 % significance difference between each scale that is (F = 28.4, P < 0.001). IEEE-AICIT KOREA 2012-06-26 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/6049/1/ICISS01-777026TO.pdf W. Daud, W. M. Bukhari and Sudirman, R and Omar, Camallil (2012) Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution. 2012 International Conference on Information Science and Digital Content Technology (ICIS and IDCTA), 20417. ISSN 978-89-88678-70-1 (Submitted) http://www.aicit.org/icidt/home/index.html 20417
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
topic T Technology (General)
spellingShingle T Technology (General)
W. Daud, W. M. Bukhari
Sudirman, R
Omar, Camallil
Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution
description Wavelet transform (WT) is one of the favored tools for analyzing the biomedical signals. This study describes the identification of Electrooculography (EOG) signals of eye movement potentials by using wavelet transform which gives a lot of information than Fourier transform. The efficiency of wavelet transform is to distribute the potential signal of energy with the change of time in different frequency bands. This will show the characteristic of the signals since energy is a considerable physical variable in signal analysis. The EOG signals are captured using electrodes placed on the forehead around the eyes to record the eye movements. The wavelet algorithm is used to determine the characteristic of eye movement waveform. This technique is adopted because it is a non-invasive, inexpensive and accurate. The new technology enhancement has allowed the EOG signals captured using the EEG Neurofax-9200. The recorded data is composed of an eye movement toward four directions that is upward, downward, left and right involving 15 subjects. The proposed analysis for each eyes signal is analyzed by using WT by comparing the energy distribution with the change of time and frequency of each signal. A wavelet scalogram is plotted to display different percentages of energy for each wavelet coefficient towards different movement. In conclusion, it is proved that the different EOG signals exhibit approximately differences in signals energy with their corresponding scales such as leftward with scale 6 (8 - 16 Hz), rightward with scale 8 (2 - 4 Hz), downward with scale 9 (1 - 2 Hz) and upward with scale 7 (4 - 8 Hz). Analysis of variance statistically proved that there is 99 % significance difference between each scale that is (F = 28.4, P < 0.001).
format Article
author W. Daud, W. M. Bukhari
Sudirman, R
Omar, Camallil
author_facet W. Daud, W. M. Bukhari
Sudirman, R
Omar, Camallil
author_sort W. Daud, W. M. Bukhari
title Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution
title_short Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution
title_full Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution
title_fullStr Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution
title_full_unstemmed Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution
title_sort electrooculograph signals of eye movement behavior with reconstruction wavelet energy distribution
publisher IEEE-AICIT KOREA
publishDate 2012
url http://eprints.utem.edu.my/id/eprint/6049/1/ICISS01-777026TO.pdf
http://eprints.utem.edu.my/id/eprint/6049/
http://www.aicit.org/icidt/home/index.html
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