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Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task

The aim of this pilot study was to select the most similar mother wavelet function and the most efficient threshold in order to use with wavelet basis function for the human brain electrical activity during working memory task. A 60 seconds was recorded from the scalp using the Electroencephalograph...

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Main Authors: Al-Qazzaz, Noor Kamal, Md. Ali, Sawal Hamid, Ahmad, Siti Anom, Islam, Md. Shabiul, Ariff, Mohd Izhar
Format: Conference or Workshop Item
Language:English
Published: IEEE 2014
Online Access:http://psasir.upm.edu.my/id/eprint/55962/1/Selection%20of%20mother%20wavelets%20thresholding%20methods%20in%20denoising%20multi-channel%20EEG%20signals%20during%20working%20memory%20task.pdf
http://psasir.upm.edu.my/id/eprint/55962/
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spelling my.upm.eprints.559622017-06-30T09:57:06Z http://psasir.upm.edu.my/id/eprint/55962/ Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task Al-Qazzaz, Noor Kamal Md. Ali, Sawal Hamid Ahmad, Siti Anom Islam, Md. Shabiul Ariff, Mohd Izhar The aim of this pilot study was to select the most similar mother wavelet function and the most efficient threshold in order to use with wavelet basis function for the human brain electrical activity during working memory task. A 60 seconds was recorded from the scalp using the Electroencephalography (EEG). 19 electrodes were placed over different sites on the scalp where analyzed for one control subject and one post-stroke patients in the first week of his stroke onset. In this study, forty-five mother wavelet basis functions from orthogonal families with four thresholding methods were used. The selection of mother wavelet functions like Daubechies (db), symlet (sym) and coiflet (coif) and the thresholding methods these are sqtwolog, rigrsure, heursure and minimax are to check mother wavelet functions similarity with the recorded EEG signals during working memory task. The test have been done using four evaluating criteria, namely signal to noise ratio (SNR), peak signal to noise ratio (PSNR) mean square error (MSE) and crosscorelation method (xcorr). Symlet mother wavelet of order 9 (sym9) is the most compatible for all the 19 channels for both EEG datasets that selected to be examined and the best results have been obtained by using the rigrsure thresholding method. IEEE 2014 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/55962/1/Selection%20of%20mother%20wavelets%20thresholding%20methods%20in%20denoising%20multi-channel%20EEG%20signals%20during%20working%20memory%20task.pdf Al-Qazzaz, Noor Kamal and Md. Ali, Sawal Hamid and Ahmad, Siti Anom and Islam, Md. Shabiul and Ariff, Mohd Izhar (2014) Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task. In: 2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES 2014), 8-10 Dec. 2014, Miri, Sarawak, Malaysia. (pp. 214-219). 10.1109/IECBES.2014.7047488
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The aim of this pilot study was to select the most similar mother wavelet function and the most efficient threshold in order to use with wavelet basis function for the human brain electrical activity during working memory task. A 60 seconds was recorded from the scalp using the Electroencephalography (EEG). 19 electrodes were placed over different sites on the scalp where analyzed for one control subject and one post-stroke patients in the first week of his stroke onset. In this study, forty-five mother wavelet basis functions from orthogonal families with four thresholding methods were used. The selection of mother wavelet functions like Daubechies (db), symlet (sym) and coiflet (coif) and the thresholding methods these are sqtwolog, rigrsure, heursure and minimax are to check mother wavelet functions similarity with the recorded EEG signals during working memory task. The test have been done using four evaluating criteria, namely signal to noise ratio (SNR), peak signal to noise ratio (PSNR) mean square error (MSE) and crosscorelation method (xcorr). Symlet mother wavelet of order 9 (sym9) is the most compatible for all the 19 channels for both EEG datasets that selected to be examined and the best results have been obtained by using the rigrsure thresholding method.
format Conference or Workshop Item
author Al-Qazzaz, Noor Kamal
Md. Ali, Sawal Hamid
Ahmad, Siti Anom
Islam, Md. Shabiul
Ariff, Mohd Izhar
spellingShingle Al-Qazzaz, Noor Kamal
Md. Ali, Sawal Hamid
Ahmad, Siti Anom
Islam, Md. Shabiul
Ariff, Mohd Izhar
Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task
author_facet Al-Qazzaz, Noor Kamal
Md. Ali, Sawal Hamid
Ahmad, Siti Anom
Islam, Md. Shabiul
Ariff, Mohd Izhar
author_sort Al-Qazzaz, Noor Kamal
title Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task
title_short Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task
title_full Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task
title_fullStr Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task
title_full_unstemmed Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task
title_sort selection of mother wavelets thresholding methods in denoising multi-channel eeg signals during working memory task
publisher IEEE
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/55962/1/Selection%20of%20mother%20wavelets%20thresholding%20methods%20in%20denoising%20multi-channel%20EEG%20signals%20during%20working%20memory%20task.pdf
http://psasir.upm.edu.my/id/eprint/55962/
_version_ 1643836049742364672
score 13.211869

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