Time frequency analysis of electrooculograph (EOG) signal of eye movement potentials based on wavelet energy distribution

Abstract

In this study, we describe the identification electroencephalography (EOG) signals of eye movement potentials by using wavelet algorithm which gives a lot of information than FFT. It shows the characteristic of the signals since energy is an important physical variable in signal analysis. The EOG signals are captured using electrodes place don the forehead around the eyes to record the eye movements. The wavelet features are used to determine the characteristic of eye movement waveform. The recorded data is composed of an eye movement toward 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 proved that the different EOG signals exhibit differences in signals energy with their corresponding scale such as left with scale 6 (8-16Hz), right with scale 8 (2-4Hz), downward with scale 9 (1-2Hz) and upward with scale 7 (4-8Hz).