Surface electromyography of eyes potential behaviour using wavelet transform analysis
The previous study of eyes potential behaviorwas carried out using Fourier Transformwhich is found to beworking on a single scale. Then,Wavelet Transform was proposed to overcomethe limitation. Hence, the objective of this paper is to identify thesurface electromyography of eyemovement potentials be...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
2013
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/40826/ http://eprints.utm.my/40826/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The previous study of eyes potential behaviorwas carried out using Fourier Transformwhich is found to beworking on a single scale. Then,Wavelet Transform was proposed to overcomethe limitation. Hence, the objective of this paper is to identify thesurface electromyography of eyemovement potentials behavior by using Wavelet Transform scalogram analysis. The eye movementsignals are detected by using electrodes that areplaced on a person’s forehead around theeye. It thenrecorded the signalusing the data acquisition Electroencephalograph Neurofax-9200. The eye movedtowards variousdirections involving15 humanswere identified. The Wavelet scalogram analyzed theeye movement signals by comparing the energy distribution with the change of time and frequency ofeach signal. The resultsproved that different surface electromyography of eye movement signalscreateddifferent signalsenergy withtheir corresponding scales.Analysisof variance statisticallyproved that there wasa99%significance difference betweeneachscaleindicatingthat each eyemovement has different frequency bands and energy distribution. Thesefindings couldbe integratedtodesign a support machinefor paralyzed peopleto move their robotor wheelchairby using eyemovements. Future works should explore the energy and frequency bands distribution within four eyemovement signals for better interpretation of surface Electromyography signals analysis by usingWavelet scalogram. |
|---|