Analysis on Visual Signal based on the Effect of Eye Massaging Device using Wavelet Transform
DOI:
https://doi.org/10.11113/jt.v74.4664Keywords:
Eye massaging device, electroencephalography, electrooculography, energy of approximation, t-test analysisAbstract
This study has been conducted to examine the effectiveness of the eye massaging device to reduce massive amount of eyesight problem. The electrical activity of the muscles surrounding the eyes is recorded by using Neurofax EEG-9200 machine. Electroencephalography (EEG) is a process to determine the brain signal, while Electrooculography (EOG) is used to measure the biopotential produced by the changes in eye position and eye movement occurred. The conventional electrode setting (also called 10-20) system is applied on the scalp electrodes for EEG to record the brain signals. While five electrodes on the forehead is used to record EOG signals. Channel O1 and O2 that act as visual processing is selected in order to record EEG signals. The signal is analyzed using Wavelet Transform and the useful parameter, Energy of Approximation (Ea) was extracted. In this study, t-test analysis is used to validate the differences of data produced before and after using eye massaging device. Based on the results, the average value collected for EEG signals before using the eye massaging device has been decreased for both channel with the different (O1: 5.083, O2: 3.385). Thus, it is proved that the eye massaging device exhibit difference for each movement tested.ÂReferences
J. Sheedy and K. Larson, 2008. Blink: The Stress of Reading. Eye, 67(17): 95.
R. Slavicek and A. Wassef, 2005. EOG for REM Sleep Detection.ECE 445 Senior Design Project. No. 23.
W. M. B. W. Daud and R. Sudirman, 2011. A Wavelet Approach on Energy Distribution of Eye Movement Potential towards Direction. Jurnal Teknologi 54 (Sains&Kej.) Keluaran Khas © Universiti Teknologi Malaysia. 299-309.
B. R. Frueh, A. Hayes, G.S. Lynch, D.A. Williams, 1994. Contractile Properties and Temperature Sensitivity of the Extraocular Muscles, the Levator and Superior Rectus of the Rabbit. Journal of Physiology. 327-336.
Open Stax College, 2013. Anatomy & Physiology. [Online]. From:http://cnx.org/content/col11496/latest/.
A. Bulling, J. A. Ward, H. Gellersen,G. Troster, 2011. Eye Movement Analysis for Activity Recognition using Electrooculography. IEEE Transaction on Pattern Analysis and Machine Intelligence. 33(4): 741-753.
F. A. Mansor, 2014. The Effects of Eye Massage Device on Electrooculography Signals. Bachelor Thesis. Universiti Teknologi Malaysia.
S. Weiss, C. Dawson, I. Kapouleas, R. Nozik, D. Skorich, J. Ostroff, 1988. Rule-based Diagnostic Decision Aids for Common Eye Problems. IEEE Engineering in Medicine and Biology Society 10th Annual International Conference. 3: 1395-1396.
E. Niedermeyer and F. L. Silva, 2005. Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. 5th Ed. Philadelphia: Lippincott Williams & Wilkins.
H. Jasper, 1958. Report of the Committee on Methods of Clinical Examination in Electroencephalography. Electroencephalography and Clinical Neurophysiology. 10(2): 370-375.
S. Sanei and J. A. Chambers, 2007. EEG Signal Processing. England: John Wiley and Sons Ltd.
Cleveland Medical Devices Inc., 2006. Electroencephalography I Laboratory. CleveLabs Laboratory Course System-Student Edition.
Staff of AD Instruments, Power AD Instruments. 2004. Human Electro-oculography (EOG). Teaching Instrument.
W. M. B. W. Daud, 2011. Formulation of Eye Movement Behavior based on Signal Energy Distribution using Wavelet Transform. Master Thesis. Universiti Teknologi Malaysia.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
