Wavelet approach on frequency energy distribution of electrooculograph potential towards direction

Abstract

Biomedical signals recognition activity has been studied by many researchers. In this study, we describe the identification of Electro-oculography (EGG) signals of eye movement potentials by using wavelet transform which gives a lot of information than FFf. 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 EGG 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 non-invasive, inexpensive and accurate. New technology enhancement has allowed the EGG signals to be captured using the Neurofax EEG-9200. The recorded data is composed of an eye movement towards four directions, i.e. upward, downward, left and right. The proposed analysis for each eyes signal is analyzed by using Wavelet Transform (WT) 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 shown that the different EGG signals exhibit differences in signals energy with their corresponding scale such as left with scale 6 (8-16Hz), right with scale 8 (24Hz), downward with scale 9 (I-2Hz) and upward with scale 7 (4-8Hz).