EYEBALL MOVEMET FREQUENCY DETECTION USING FAST FOURIER TRANSFORM ALGORITHM ONELECTROOCULOGRAPHY SIGNALS

• Main Author: Dwigiantara, Ryan
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/76877
• Institution: Institut Teknologi Bandung

Electrooculography is a way of reading the electrical signals of the human body by utilizing the standing potential caused by differences in the concentration of charges on the cornea and retina of the eye. Electrooculography is the optimal method for detecting eyeball movement, so it is often used to design means of interaction between humans and computers. On the other hand, EOG also has diagnostic functions such as detecting Rapid Eye Movement sleep disturbances. However, the EOG tool cannot stand alone without good signal processing. Therefore, in this study, we studied the use of the Fast Fourier Transform (FFT) algorithm which is capable of performing Discrete Fourier Transform (DFT) analysis of high-speed EOG signals. To study the effectiveness of this method, EOG signal data were collected from healthy subjects with the help of a reference video by varying the reference video frequency (0.5, 0.125, 0.07, and 0.05 Hz), video duration (60, 90, and 120 s), and the distance between screens. with subjects (30, 45, and 60 cm) in vertical and horizontal orientation. In this study, the application of the FFT algorithm to the EOG signal measured on 22-year-old subjects indicated good results in horizontal orientation measurements using high-frequency (0.5 Hz) video, with a measurement duration of 60-90 seconds at a measurement distance of 30 cm