Staff View: Wavelet based filters for artifact elimination in electroencephalography signal: A review

Wavelet based filters for artifact elimination in electroencephalography signal: A review

Electroencephalography (EEG) is a diagnostic test that records and measures the electrical activity of the human brain. Research investigating human behaviors and conditions using EEG has increased from year to year. Therefore, an efficient approach is vital to process the EEG dataset to improve the...

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Main Authors:	Sayed Daud, Syarifah Noor Syakiylla, Sudirman, Rubita
Format:	Article
Published:	Springer 2022
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/100797/ http://dx.doi.org/10.1007/s10439-022-03053-5
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id	my.utm.100797
record_format	eprints
spelling	my.utm.1007972023-04-30T11:38:18Z http://eprints.utm.my/id/eprint/100797/ Wavelet based filters for artifact elimination in electroencephalography signal: A review Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita TK Electrical engineering. Electronics Nuclear engineering Electroencephalography (EEG) is a diagnostic test that records and measures the electrical activity of the human brain. Research investigating human behaviors and conditions using EEG has increased from year to year. Therefore, an efficient approach is vital to process the EEG dataset to improve the output signal quality. The wavelet is one of the well-known approaches for processing the EEG signal in time–frequency domain analysis. The wavelet is better than the traditional Fourier Transform because it has good time–frequency localized properties and multi-resolution analysis where the transient information of an EEG signal can be extracted efficiently. Thus, this review article aims to comprehensively describe the application of the wavelet method in denoising the EEG signal based on recent research. This review begins with a brief overview of the basic theory and characteristics of EEG and the wavelet transform method. Then, several wavelet-based methods commonly applied in EEG dataset denoising are described and a considerable number of the latest published EEG research works with wavelet applications are reviewed. Besides, the challenges that exist in current EEG-based wavelet method research are discussed. Finally, alternative solutions to mitigate the issues are recommended. Springer 2022 Article PeerReviewed Sayed Daud, Syarifah Noor Syakiylla and Sudirman, Rubita (2022) Wavelet based filters for artifact elimination in electroencephalography signal: A review. Annals of Biomedical Engineering, 50 (10). pp. 1271-1291. ISSN 0090-6964 http://dx.doi.org/10.1007/s10439-022-03053-5 DOI : 10.1007/s10439-022-03053-5
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita Wavelet based filters for artifact elimination in electroencephalography signal: A review
description	Electroencephalography (EEG) is a diagnostic test that records and measures the electrical activity of the human brain. Research investigating human behaviors and conditions using EEG has increased from year to year. Therefore, an efficient approach is vital to process the EEG dataset to improve the output signal quality. The wavelet is one of the well-known approaches for processing the EEG signal in time–frequency domain analysis. The wavelet is better than the traditional Fourier Transform because it has good time–frequency localized properties and multi-resolution analysis where the transient information of an EEG signal can be extracted efficiently. Thus, this review article aims to comprehensively describe the application of the wavelet method in denoising the EEG signal based on recent research. This review begins with a brief overview of the basic theory and characteristics of EEG and the wavelet transform method. Then, several wavelet-based methods commonly applied in EEG dataset denoising are described and a considerable number of the latest published EEG research works with wavelet applications are reviewed. Besides, the challenges that exist in current EEG-based wavelet method research are discussed. Finally, alternative solutions to mitigate the issues are recommended.
format	Article
author	Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita
author_facet	Sayed Daud, Syarifah Noor Syakiylla Sudirman, Rubita
author_sort	Sayed Daud, Syarifah Noor Syakiylla
title	Wavelet based filters for artifact elimination in electroencephalography signal: A review
title_short	Wavelet based filters for artifact elimination in electroencephalography signal: A review
title_full	Wavelet based filters for artifact elimination in electroencephalography signal: A review
title_fullStr	Wavelet based filters for artifact elimination in electroencephalography signal: A review
title_full_unstemmed	Wavelet based filters for artifact elimination in electroencephalography signal: A review
title_sort	wavelet based filters for artifact elimination in electroencephalography signal: a review
publisher	Springer
publishDate	2022
url	http://eprints.utm.my/id/eprint/100797/ http://dx.doi.org/10.1007/s10439-022-03053-5
_version_	1765296703488917504
score	13.211869

Wavelet based filters for artifact elimination in electroencephalography signal: A review

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