Wavelet Frequency Energy Distribution of Electrooculogram Potential Towards Vertical and Horizontal Movement
Wavelet transform is one of the favoured tool for analyzing the biomedical signals. In this paper, we describe the identification of Electro oculography (EOG) signals of eye movement potentials by using wavelet transform which gives more feature informations than FFT. The capability of wavelet trans...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
IEEE XPLORE
2011
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/5926/1/05701865.pdf http://eprints.utem.edu.my/id/eprint/5926/ http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=5701865&contentType=Conference+Publications&queryText%3DWavelet+Frequency+Energy+Distribution+of+Electrooculogram+Potential+towards+Vertical+and+Horizontal+Movement |
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| Summary: | Wavelet transform is one of the favoured tool for analyzing the biomedical signals. In this paper, we describe the identification of Electro oculography (EOG) signals of eye movement potentials by using wavelet transform which gives more feature informations than FFT. The capability of wavelet transform is to distribute the signal energy over the change of time in different frequency bands. The EOG signals are captured using electrodes placed on the forehead around the eyes to record the eye movements using the Neuro fax EEG-9200. The wavelet features are used to determine the characteristic of eye movement waveform. The recorded data is composed of an eye movement toward vertical, upward and downward and horizontal, left and right movements. From the result, it is proved that different EOG signals exhibit differences in signals energy, in which their corresponding dominant energy are: level 6 (8-16Hz) for left eye movement, level 7 (4-8Hz) for upward, level 8 (2-4Hz) for right and level 9 (1-2Hz) for downward. |
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