A wavelet approach on energy distribution of eye movement potential towards direction

Abstract

This study presents an investigation in classification of Electrooculography (EOG) signals of eye movement potentials. In recent years, the classification of EOG signals by using the FFT is computationally efficient in means and has been a good considerable in research effort. In the quest to improve the accuracy of the EOG signals classification, a method of time-frequency based analysis is proposed. 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. EOG signals are captured using the Neurofax EEG-9200. The recorded data is composed of an eye movement toward four directions (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 a 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 level such as left with level 6 (8–16Hz), right with level 8 (2–4Hz), downward with level 7 (4–8Hz) and upward with level 9 (1–2Hz).