Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction
The time frequency analysis of non-stationary signals has been the considerable research effort in recent years. Wavelet transform is one of the favoured tool for the analyzing the biomedical signals. In this study, we describe the identification of Electro-oculography (EOG) signals of eye movement...
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The Indonesian Journal of ICT and Internet Development
2011
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my.utem.eprints.60502022-01-20T15:58:44Z http://eprints.utem.edu.my/id/eprint/6050/ Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction Wan Daud, Wan Mohd Bukhari T Technology (General) The time frequency analysis of non-stationary signals has been the considerable research effort in recent years. Wavelet transform is one of the favoured tool for the analyzing the biomedical signals. In this study, we describe the identification of Electro-oculography (EOG) signals of eye movement potentials by using wavelet algorithm which gives a lot of information than FFT. The capability of wavelet transform is to distribute the signal energy with the change of time in different frequency bands. This will show the characteristic of the signals since energy is an important 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 features are 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 Neurofax EEG-9200. The recorded data is composed of an eye movement toward four directions, i.e. downward, upward, leftward and rightward. The proposed analysis for each eyes signal is analyzed by using Wavelet Transform (WT) with energy algorithm and by comparing the energy distribution with the change of time and frequency of each signal. A wavelet scalogram is plotted to display the different percentages of energy for each wavelet coefficient towards different movement. From the result, it is proved that the different EOG signals exhibit differences in signals energy with their corresponding scale such as leftward with scale 6 (8-16Hz), rightward with scale 8 (2-4Hz), downward with scale 9 (1-2Hz) and upward with scale 7 (4-8Hz). The Indonesian Journal of ICT and Internet Development 2011 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/6050/1/iij_vol3_no1_2011_covers.pdf Wan Daud, Wan Mohd Bukhari (2011) Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction. Internetworking Indonesia Journal, 3 (1). pp. 3-10. ISSN 1942-9703 http://www.InternetworkingIndonesia.org |
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The time frequency analysis of non-stationary signals has been the considerable research effort in recent years. Wavelet transform is one of the favoured tool for the analyzing the biomedical signals. In this study, we describe the identification of Electro-oculography (EOG) signals of eye movement potentials by using wavelet algorithm which gives a lot of information than FFT. The capability of wavelet transform is to distribute the signal energy with the change of time in different frequency bands. This will show the characteristic of the signals since energy is an important 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 features are 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 Neurofax EEG-9200. The recorded data is composed of an eye movement toward four directions, i.e. downward, upward, leftward and rightward. The proposed analysis for each eyes signal is analyzed by using Wavelet Transform (WT) with energy algorithm and by comparing the energy distribution with the change of time and frequency of each signal. A wavelet scalogram is plotted to display the different percentages of energy for each wavelet coefficient towards different movement. From the result, it is proved that the different EOG signals exhibit differences in signals energy with their corresponding scale such as leftward with scale 6 (8-16Hz), rightward with scale 8 (2-4Hz), downward with scale 9 (1-2Hz) and upward with scale 7 (4-8Hz). |
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Wan Daud, Wan Mohd Bukhari |
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Wan Daud, Wan Mohd Bukhari |
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Wan Daud, Wan Mohd Bukhari |
title |
Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction |
title_short |
Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction |
title_full |
Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction |
title_fullStr |
Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction |
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Wavelet Approach on Frequency Energy Distribution of Electrooculography Potential Towards Direction |
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wavelet approach on frequency energy distribution of electrooculography potential towards direction |
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The Indonesian Journal of ICT and Internet Development |
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2011 |
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http://eprints.utem.edu.my/id/eprint/6050/1/iij_vol3_no1_2011_covers.pdf http://eprints.utem.edu.my/id/eprint/6050/ http://www.InternetworkingIndonesia.org |
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