Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet" |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 214-219 |
| Number of pages | 6 |
| ISBN (Print) | 9781479940844 |
| DOIs | |
| Publication status | Published - 23 Feb 2015 |
| Event | 3rd IEEE Conference on Biomedical Engineering and Sciences, IECBES 2014 - Kuala Lumpur Duration: 8 Dec 2014 → 10 Dec 2014 |
Other
| Other | 3rd IEEE Conference on Biomedical Engineering and Sciences, IECBES 2014 |
|---|---|
| City | Kuala Lumpur |
| Period | 8/12/14 → 10/12/14 |
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ASJC Scopus subject areas
- Biomedical Engineering
Cite this
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.
IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet". Institute of Electrical and Electronics Engineers Inc., 2015. p. 214-219 7047488.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task
AU - Al-Qazzaz, Noor Kamal
AU - Md Ali, Sawal Hamid
AU - Ahmad, Siti Anom
AU - Islam, Md. Shabiul
AU - Ariff, Mohd Izhar
PY - 2015/2/23
Y1 - 2015/2/23
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84925688263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84925688263&partnerID=8YFLogxK
U2 - 10.1109/IECBES.2014.7047488
DO - 10.1109/IECBES.2014.7047488
M3 - Conference contribution
AN - SCOPUS:84925688263
SN - 9781479940844
SP - 214
EP - 219
BT - IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet"
PB - Institute of Electrical and Electronics Engineers Inc.
ER -