Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach
This recent study introduces and discusses briefly the use of wavelet approach in removing the artifacts and extraction of features for electroencephalography (EEG) signal. Many of new approaches have been discovered by the researcher for processing the EEG signal. Generally, the EEG signal processi...
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Online Access: | http://eprints.utm.my/id/eprint/71386/1/RubitaSudirman2016_Artifactremovalandbrainrhythm.pdf http://eprints.utm.my/id/eprint/71386/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979670171&doi=10.11113%2fjt.v78.9460&partnerID=40&md5=1cf26811458bba3a47be91a4778b4c39 |
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my.utm.713862017-11-20T08:30:36Z http://eprints.utm.my/id/eprint/71386/ Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita TK Electrical engineering. Electronics Nuclear engineering This recent study introduces and discusses briefly the use of wavelet approach in removing the artifacts and extraction of features for electroencephalography (EEG) signal. Many of new approaches have been discovered by the researcher for processing the EEG signal. Generally, the EEG signal processing can be divided into pre-processing and postprocessing. The aim of processing is to remove the unwanted signal and to extract important features from the signal. However, the selections of non-suitable approach affect the actual result and wasting the time and energy. Wavelet is among the effective approach that can be used for processing the biomedical signal. The wavelet approach can be performed in MATLAB toolbox or by coding, that require a simple and basic command. In this paper, the application of wavelet approach for EEG signal processing is introduced. Moreover, this paper also discusses the effect of using db3 mother wavelet with 5th decomposition level of stationary wavelet transform and db4 mother wavelet with 7th decomposition level of discrete wavelet transform in removing the noise and decomposing of the brain rhythm. Besides, the simulation result are also provided for better configuration. Penerbit UTM Press 2016 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/71386/1/RubitaSudirman2016_Artifactremovalandbrainrhythm.pdf Sayed Daud, Syarifah Noor Syakiylla and Sudirman, Rubita (2016) Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach. Jurnal Teknologi, 78 (7-5). pp. 135-143. ISSN 0127-9696 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979670171&doi=10.11113%2fjt.v78.9460&partnerID=40&md5=1cf26811458bba3a47be91a4778b4c39 |
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TK Electrical engineering. Electronics Nuclear engineering Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach |
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This recent study introduces and discusses briefly the use of wavelet approach in removing the artifacts and extraction of features for electroencephalography (EEG) signal. Many of new approaches have been discovered by the researcher for processing the EEG signal. Generally, the EEG signal processing can be divided into pre-processing and postprocessing. The aim of processing is to remove the unwanted signal and to extract important features from the signal. However, the selections of non-suitable approach affect the actual result and wasting the time and energy. Wavelet is among the effective approach that can be used for processing the biomedical signal. The wavelet approach can be performed in MATLAB toolbox or by coding, that require a simple and basic command. In this paper, the application of wavelet approach for EEG signal processing is introduced. Moreover, this paper also discusses the effect of using db3 mother wavelet with 5th decomposition level of stationary wavelet transform and db4 mother wavelet with 7th decomposition level of discrete wavelet transform in removing the noise and decomposing of the brain rhythm. Besides, the simulation result are also provided for better configuration. |
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Article |
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Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita |
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Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita |
author_sort |
Sayed Daud, Syarifah Noor Syakiylla |
title |
Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach |
title_short |
Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach |
title_full |
Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach |
title_fullStr |
Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach |
title_full_unstemmed |
Artifact removal and brain rhythm decomposition for eeg signal using wavelet approach |
title_sort |
artifact removal and brain rhythm decomposition for eeg signal using wavelet approach |
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Penerbit UTM Press |
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2016 |
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http://eprints.utm.my/id/eprint/71386/1/RubitaSudirman2016_Artifactremovalandbrainrhythm.pdf http://eprints.utm.my/id/eprint/71386/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979670171&doi=10.11113%2fjt.v78.9460&partnerID=40&md5=1cf26811458bba3a47be91a4778b4c39 |
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