Electrooculograph Signals of Eye Movement Behavior with Reconstruction Wavelet Energy Distribution

• Main Authors: W. Daud, W. M. Bukhari, Sudirman, R, Omar, Camallil
• Format: Article
• Language: English
• Published: IEEE-AICIT KOREA 2012
• Subjects: T Technology (General)
• Online Access: 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

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).