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T-Wave Alternans Found in Preventricular Tachyarrhythmias in CCU Patients Using a Wavelet Transform-Based Methodology
Ventricular tachyarrhythmias are potentially lethal cardiac pathologies and the commonest cause of sudden cardiac death. Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function...
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Published in: | IEEE transactions on biomedical engineering 2008-11, Vol.55 (11), p.2658-2665 |
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description | Ventricular tachyarrhythmias are potentially lethal cardiac pathologies and the commonest cause of sudden cardiac death. Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function that may be associated with ventricular tachycardia (VT) and ventricular fibrillation. A novel TWA detection algorithm utilizing the continuous wavelet transform is described in this paper. Simulated ECGs containing artificial TWA were used to test the algorithm that achieved a sensitivity of 91.40% and a specificity of 94.00%. The algorithm was subsequently used to analyze the ECGs of eight patients prior to the onset of VT. Of these, the algorithm indicated that five patients exhibited TWA prior to the onset of the tachyarrhythmic events, while the remaining three patients did not exhibit identifiable TWA. Healthy individuals were also studied in which one short TWA episode was detected by the algorithm. However, closer visual inspection of the data revealed this to be a likely false positive result. |
doi_str_mv | 10.1109/TBME.2008.923912 |
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Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function that may be associated with ventricular tachycardia (VT) and ventricular fibrillation. A novel TWA detection algorithm utilizing the continuous wavelet transform is described in this paper. Simulated ECGs containing artificial TWA were used to test the algorithm that achieved a sensitivity of 91.40% and a specificity of 94.00%. The algorithm was subsequently used to analyze the ECGs of eight patients prior to the onset of VT. Of these, the algorithm indicated that five patients exhibited TWA prior to the onset of the tachyarrhythmic events, while the remaining three patients did not exhibit identifiable TWA. Healthy individuals were also studied in which one short TWA episode was detected by the algorithm. 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(IEEE) 2008</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c407t-644f568b78422e1e3c212c62f0891f9e290cab1775896a9fb52f7d315f52c8c53</citedby><cites>FETCH-LOGICAL-c407t-644f568b78422e1e3c212c62f0891f9e290cab1775896a9fb52f7d315f52c8c53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4666712$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18990637$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Romero, Inaki</creatorcontrib><creatorcontrib>Grubb, Neil R.</creatorcontrib><creatorcontrib>Clegg, Gareth R.</creatorcontrib><creatorcontrib>Robertson, Colin E.</creatorcontrib><creatorcontrib>Addison, Paul S.</creatorcontrib><creatorcontrib>Watson, James N.</creatorcontrib><title>T-Wave Alternans Found in Preventricular Tachyarrhythmias in CCU Patients Using a Wavelet Transform-Based Methodology</title><title>IEEE transactions on biomedical engineering</title><addtitle>TBME</addtitle><addtitle>IEEE Trans Biomed Eng</addtitle><description>Ventricular tachyarrhythmias are potentially lethal cardiac pathologies and the commonest cause of sudden cardiac death. Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function that may be associated with ventricular tachycardia (VT) and ventricular fibrillation. A novel TWA detection algorithm utilizing the continuous wavelet transform is described in this paper. Simulated ECGs containing artificial TWA were used to test the algorithm that achieved a sensitivity of 91.40% and a specificity of 94.00%. The algorithm was subsequently used to analyze the ECGs of eight patients prior to the onset of VT. Of these, the algorithm indicated that five patients exhibited TWA prior to the onset of the tachyarrhythmic events, while the remaining three patients did not exhibit identifiable TWA. Healthy individuals were also studied in which one short TWA episode was detected by the algorithm. 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methods</topic><topic>Feature extraction</topic><topic>Fibrillation</topic><topic>Heart attacks</topic><topic>Humans</topic><topic>Inspection</topic><topic>Models, Cardiovascular</topic><topic>Pathology</topic><topic>Sensitivity and Specificity</topic><topic>Signal Processing, Computer-Assisted</topic><topic>Statistics, Nonparametric</topic><topic>T-wave alternans (TWAs)</topic><topic>Tachycardia, Ventricular - diagnosis</topic><topic>Tachycardia, Ventricular - physiopathology</topic><topic>Testing</topic><topic>ventricular tachyarrhithmia (VTA)</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Romero, Inaki</creatorcontrib><creatorcontrib>Grubb, Neil R.</creatorcontrib><creatorcontrib>Clegg, Gareth R.</creatorcontrib><creatorcontrib>Robertson, Colin E.</creatorcontrib><creatorcontrib>Addison, Paul S.</creatorcontrib><creatorcontrib>Watson, James N.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</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>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transactions on biomedical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Romero, Inaki</au><au>Grubb, Neil R.</au><au>Clegg, Gareth R.</au><au>Robertson, Colin E.</au><au>Addison, Paul S.</au><au>Watson, James N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>T-Wave Alternans Found in Preventricular Tachyarrhythmias in CCU Patients Using a Wavelet Transform-Based Methodology</atitle><jtitle>IEEE transactions on biomedical engineering</jtitle><stitle>TBME</stitle><addtitle>IEEE Trans Biomed Eng</addtitle><date>2008-11-01</date><risdate>2008</risdate><volume>55</volume><issue>11</issue><spage>2658</spage><epage>2665</epage><pages>2658-2665</pages><issn>0018-9294</issn><eissn>1558-2531</eissn><coden>IEBEAX</coden><abstract>Ventricular tachyarrhythmias are potentially lethal cardiac pathologies and the commonest cause of sudden cardiac death. Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function that may be associated with ventricular tachycardia (VT) and ventricular fibrillation. A novel TWA detection algorithm utilizing the continuous wavelet transform is described in this paper. Simulated ECGs containing artificial TWA were used to test the algorithm that achieved a sensitivity of 91.40% and a specificity of 94.00%. The algorithm was subsequently used to analyze the ECGs of eight patients prior to the onset of VT. Of these, the algorithm indicated that five patients exhibited TWA prior to the onset of the tachyarrhythmic events, while the remaining three patients did not exhibit identifiable TWA. Healthy individuals were also studied in which one short TWA episode was detected by the algorithm. 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subjects | Algorithm design and analysis Algorithms Continuous wavelet transforms Coronary Care Units Defibrillators Detection algorithms ECG analysis Electrocardiography Electrocardiography - methods Feature extraction Fibrillation Heart attacks Humans Inspection Models, Cardiovascular Pathology Sensitivity and Specificity Signal Processing, Computer-Assisted Statistics, Nonparametric T-wave alternans (TWAs) Tachycardia, Ventricular - diagnosis Tachycardia, Ventricular - physiopathology Testing ventricular tachyarrhithmia (VTA) Wavelet transforms |
title | T-Wave Alternans Found in Preventricular Tachyarrhythmias in CCU Patients Using a Wavelet Transform-Based Methodology |
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