Empirical Mode Decomposition, Viterbi and Wavelets Applied to Electrocardiogram Noise Removal
The electrocardiogram (ECG) signal is generally used as a cardiovascular disease diagnostic tool. The accuracy of the diagnosis is directly related to the quality of the ECG signal, which can be corrupted by several sources of noises such as, for example, baseline wanders and power line interference...
Gespeichert in:
Veröffentlicht in: | Circuits, systems, and signal processing systems, and signal processing, 2021-02, Vol.40 (2), p.691-718 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 718 |
---|---|
container_issue | 2 |
container_start_page | 691 |
container_title | Circuits, systems, and signal processing |
container_volume | 40 |
creator | Vargas, Regis Nunes Veiga, Antônio Cláudio Paschoarelli |
description | The electrocardiogram (ECG) signal is generally used as a cardiovascular disease diagnostic tool. The accuracy of the diagnosis is directly related to the quality of the ECG signal, which can be corrupted by several sources of noises such as, for example, baseline wanders and power line interference. This paper proposes a new ECG denoising methodology based on wavelets, empirical mode decomposition (EMD), and Viterbi algorithm. The EMD decomposes the signal in intrinsic mode functions (IMFs), then each one of these IMFs is processed by the discrete wavelet transform through a decision process based on the Viterbi algorithm. We apply the proposed method to a synthetic ECG signal and three real ECG signals. The simulations results show that this novel methodology outperforms denoising schemes based on wavelets, empirical mode decomposition, and total variation. |
doi_str_mv | 10.1007/s00034-020-01489-5 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2487069987</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2487069987</sourcerecordid><originalsourceid>FETCH-LOGICAL-c319t-7fdd62c80939d4bee02e9db0542675bc5a54d3142d5c48426ccb74a53695c5cc3</originalsourceid><addsrcrecordid>eNp9kEtLxDAUhYMoOI7-AVcBt1Zv0qRNloOODxgVxNdGQppkhgxtU5POgP_eagV3ri4czncufAgdEzgjAOV5AoCcZUAhA8KEzPgOmhCek4yLUuyiCdBSZCDI2z46SGkNQCSTdILe503noze6xnfBOnzpTGi6kHzvQ3uKX3zvYuWxbi1-1VtXuz7hWdfV3lncBzyvneljMDpaH1ZRN_g--OTwo2vCVteHaG-p6-SOfu8UPV_Nny5ussXD9e3FbJGZnMg-K5fWFtQIkLm0rHIOqJO2As5oUfLKcM2ZzQmjlhsmhtCYqmSa54XkhhuTT9HJuNvF8LFxqVfrsInt8FJRJkoopBTl0KJjy8SQUnRL1UXf6PipCKhvjWrUqAaN6kej4gOUj1Aayu3Kxb_pf6gvCFt1uQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2487069987</pqid></control><display><type>article</type><title>Empirical Mode Decomposition, Viterbi and Wavelets Applied to Electrocardiogram Noise Removal</title><source>Springer Nature - Complete Springer Journals</source><creator>Vargas, Regis Nunes ; Veiga, Antônio Cláudio Paschoarelli</creator><creatorcontrib>Vargas, Regis Nunes ; Veiga, Antônio Cláudio Paschoarelli</creatorcontrib><description>The electrocardiogram (ECG) signal is generally used as a cardiovascular disease diagnostic tool. The accuracy of the diagnosis is directly related to the quality of the ECG signal, which can be corrupted by several sources of noises such as, for example, baseline wanders and power line interference. This paper proposes a new ECG denoising methodology based on wavelets, empirical mode decomposition (EMD), and Viterbi algorithm. The EMD decomposes the signal in intrinsic mode functions (IMFs), then each one of these IMFs is processed by the discrete wavelet transform through a decision process based on the Viterbi algorithm. We apply the proposed method to a synthetic ECG signal and three real ECG signals. The simulations results show that this novel methodology outperforms denoising schemes based on wavelets, empirical mode decomposition, and total variation.</description><identifier>ISSN: 0278-081X</identifier><identifier>EISSN: 1531-5878</identifier><identifier>DOI: 10.1007/s00034-020-01489-5</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Circuits and Systems ; Decomposition ; Diagnostic software ; Diagnostic systems ; Discrete Wavelet Transform ; Electrical Engineering ; Electrocardiography ; Electronics and Microelectronics ; Engineering ; Instrumentation ; Noise reduction ; Power lines ; Signal quality ; Signal,Image and Speech Processing ; Viterbi algorithm detectors ; Wavelet transforms</subject><ispartof>Circuits, systems, and signal processing, 2021-02, Vol.40 (2), p.691-718</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020</rights><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-7fdd62c80939d4bee02e9db0542675bc5a54d3142d5c48426ccb74a53695c5cc3</citedby><cites>FETCH-LOGICAL-c319t-7fdd62c80939d4bee02e9db0542675bc5a54d3142d5c48426ccb74a53695c5cc3</cites><orcidid>0000-0001-7860-1197</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00034-020-01489-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00034-020-01489-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27915,27916,41479,42548,51310</link.rule.ids></links><search><creatorcontrib>Vargas, Regis Nunes</creatorcontrib><creatorcontrib>Veiga, Antônio Cláudio Paschoarelli</creatorcontrib><title>Empirical Mode Decomposition, Viterbi and Wavelets Applied to Electrocardiogram Noise Removal</title><title>Circuits, systems, and signal processing</title><addtitle>Circuits Syst Signal Process</addtitle><description>The electrocardiogram (ECG) signal is generally used as a cardiovascular disease diagnostic tool. The accuracy of the diagnosis is directly related to the quality of the ECG signal, which can be corrupted by several sources of noises such as, for example, baseline wanders and power line interference. This paper proposes a new ECG denoising methodology based on wavelets, empirical mode decomposition (EMD), and Viterbi algorithm. The EMD decomposes the signal in intrinsic mode functions (IMFs), then each one of these IMFs is processed by the discrete wavelet transform through a decision process based on the Viterbi algorithm. We apply the proposed method to a synthetic ECG signal and three real ECG signals. The simulations results show that this novel methodology outperforms denoising schemes based on wavelets, empirical mode decomposition, and total variation.</description><subject>Algorithms</subject><subject>Circuits and Systems</subject><subject>Decomposition</subject><subject>Diagnostic software</subject><subject>Diagnostic systems</subject><subject>Discrete Wavelet Transform</subject><subject>Electrical Engineering</subject><subject>Electrocardiography</subject><subject>Electronics and Microelectronics</subject><subject>Engineering</subject><subject>Instrumentation</subject><subject>Noise reduction</subject><subject>Power lines</subject><subject>Signal quality</subject><subject>Signal,Image and Speech Processing</subject><subject>Viterbi algorithm detectors</subject><subject>Wavelet transforms</subject><issn>0278-081X</issn><issn>1531-5878</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kEtLxDAUhYMoOI7-AVcBt1Zv0qRNloOODxgVxNdGQppkhgxtU5POgP_eagV3ri4czncufAgdEzgjAOV5AoCcZUAhA8KEzPgOmhCek4yLUuyiCdBSZCDI2z46SGkNQCSTdILe503noze6xnfBOnzpTGi6kHzvQ3uKX3zvYuWxbi1-1VtXuz7hWdfV3lncBzyvneljMDpaH1ZRN_g--OTwo2vCVteHaG-p6-SOfu8UPV_Nny5ussXD9e3FbJGZnMg-K5fWFtQIkLm0rHIOqJO2As5oUfLKcM2ZzQmjlhsmhtCYqmSa54XkhhuTT9HJuNvF8LFxqVfrsInt8FJRJkoopBTl0KJjy8SQUnRL1UXf6PipCKhvjWrUqAaN6kej4gOUj1Aayu3Kxb_pf6gvCFt1uQ</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Vargas, Regis Nunes</creator><creator>Veiga, Antônio Cláudio Paschoarelli</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>88I</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope><orcidid>https://orcid.org/0000-0001-7860-1197</orcidid></search><sort><creationdate>20210201</creationdate><title>Empirical Mode Decomposition, Viterbi and Wavelets Applied to Electrocardiogram Noise Removal</title><author>Vargas, Regis Nunes ; Veiga, Antônio Cláudio Paschoarelli</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-7fdd62c80939d4bee02e9db0542675bc5a54d3142d5c48426ccb74a53695c5cc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Circuits and Systems</topic><topic>Decomposition</topic><topic>Diagnostic software</topic><topic>Diagnostic systems</topic><topic>Discrete Wavelet Transform</topic><topic>Electrical Engineering</topic><topic>Electrocardiography</topic><topic>Electronics and Microelectronics</topic><topic>Engineering</topic><topic>Instrumentation</topic><topic>Noise reduction</topic><topic>Power lines</topic><topic>Signal quality</topic><topic>Signal,Image and Speech Processing</topic><topic>Viterbi algorithm detectors</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vargas, Regis Nunes</creatorcontrib><creatorcontrib>Veiga, Antônio Cláudio Paschoarelli</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><jtitle>Circuits, systems, and signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vargas, Regis Nunes</au><au>Veiga, Antônio Cláudio Paschoarelli</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Empirical Mode Decomposition, Viterbi and Wavelets Applied to Electrocardiogram Noise Removal</atitle><jtitle>Circuits, systems, and signal processing</jtitle><stitle>Circuits Syst Signal Process</stitle><date>2021-02-01</date><risdate>2021</risdate><volume>40</volume><issue>2</issue><spage>691</spage><epage>718</epage><pages>691-718</pages><issn>0278-081X</issn><eissn>1531-5878</eissn><abstract>The electrocardiogram (ECG) signal is generally used as a cardiovascular disease diagnostic tool. The accuracy of the diagnosis is directly related to the quality of the ECG signal, which can be corrupted by several sources of noises such as, for example, baseline wanders and power line interference. This paper proposes a new ECG denoising methodology based on wavelets, empirical mode decomposition (EMD), and Viterbi algorithm. The EMD decomposes the signal in intrinsic mode functions (IMFs), then each one of these IMFs is processed by the discrete wavelet transform through a decision process based on the Viterbi algorithm. We apply the proposed method to a synthetic ECG signal and three real ECG signals. The simulations results show that this novel methodology outperforms denoising schemes based on wavelets, empirical mode decomposition, and total variation.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s00034-020-01489-5</doi><tpages>28</tpages><orcidid>https://orcid.org/0000-0001-7860-1197</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0278-081X |
ispartof | Circuits, systems, and signal processing, 2021-02, Vol.40 (2), p.691-718 |
issn | 0278-081X 1531-5878 |
language | eng |
recordid | cdi_proquest_journals_2487069987 |
source | Springer Nature - Complete Springer Journals |
subjects | Algorithms Circuits and Systems Decomposition Diagnostic software Diagnostic systems Discrete Wavelet Transform Electrical Engineering Electrocardiography Electronics and Microelectronics Engineering Instrumentation Noise reduction Power lines Signal quality Signal,Image and Speech Processing Viterbi algorithm detectors Wavelet transforms |
title | Empirical Mode Decomposition, Viterbi and Wavelets Applied to Electrocardiogram Noise Removal |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T04%3A56%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Empirical%20Mode%20Decomposition,%20Viterbi%20and%20Wavelets%20Applied%20to%20Electrocardiogram%20Noise%20Removal&rft.jtitle=Circuits,%20systems,%20and%20signal%20processing&rft.au=Vargas,%20Regis%20Nunes&rft.date=2021-02-01&rft.volume=40&rft.issue=2&rft.spage=691&rft.epage=718&rft.pages=691-718&rft.issn=0278-081X&rft.eissn=1531-5878&rft_id=info:doi/10.1007/s00034-020-01489-5&rft_dat=%3Cproquest_cross%3E2487069987%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2487069987&rft_id=info:pmid/&rfr_iscdi=true |