Epilepsy; Data from Multimedia University, Faculty of Engineering advance knowledge in epilepsy

K. Asaduzzaman, (2011) Epilepsy; Data from Multimedia University, Faculty of Engineering advance knowledge in epilepsy. Pain & Central Nervous System Week. p. 7. ISSN 1531-6394

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Abstract

The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly.

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 22 Oct 2013 03:37
Last Modified: 22 Oct 2013 03:37
URI: http://shdl.mmu.edu.my/id/eprint/4283

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