New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data

In this study, a method for determining the location and extent of myocardial infarction using BSPM data that was obtained from PhysioNet challenge 2007 database has been suggested. This data is related to the four patients with MI that we used from two patients as training set to determine rules, a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Safdarian, N., Dabanloo, N. J., Attarodi, G.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 508
container_issue
container_start_page 505
container_title
container_volume
creator Safdarian, N.
Dabanloo, N. J.
Attarodi, G.
description In this study, a method for determining the location and extent of myocardial infarction using BSPM data that was obtained from PhysioNet challenge 2007 database has been suggested. This data is related to the four patients with MI that we used from two patients as training set to determine rules, and from two other patients for testing set and the conclusion of the proposed model. At first, T-wave amplitude, R-wave amplitude and integration of T-wave as three features of ECG signals were extracted. Then with definition and applying several rules and threshold levels for those features, areas that are with MI and these extents were diagnosed. In this study to determine the precise location of MI, 17-segments standard model of left ventricle (LV) was used. Finally, overall accuracy of this method that expressed with SO parameter and EPD parameter for two patients in test set was obtained to 0.94 and 5.37, respectively. The main advantages of this method were its simplicity and high accuracy.
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6420441</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6420441</ieee_id><sourcerecordid>6420441</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-3a1d10d1d2a22eb0e4bcdc3b685a1412c349a53dba3be154f98717603b5a13c3</originalsourceid><addsrcrecordid>eNo1jUlOw0AQRZtJIgk5AZu6gKUe3fYSojBIYZDIPiq7y6GRh6jdEYR7cF-cBFalr_ffrxM2zW0mdGqV5NbYUzaSSpoky4w6Y-N_kJpzNuLSpklqrL5k477_4FzkuTUj9vNMn-AoUhl910JD8b1zUGBPDoY8n91D79ct1lARxm2gHmJ3EELjW4K6K7H233iwsXVAX5HaCF0FzW5gwfnB9W2F4fhh2_t2Dbed28HbNlRYErx2e2Xfe8INOIx4xS4qrHua_t0JW97Nl7OHZPFy_zi7WSReWBMThcIJ7oSTKCUVnHRRulIVaWZQaCFLpXM0yhWoChJGV3lmhU25KgauSjVh18dZT0SrTfANht0q1ZJrLdQvtqpnPw</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Safdarian, N. ; Dabanloo, N. J. ; Attarodi, G.</creator><creatorcontrib>Safdarian, N. ; Dabanloo, N. J. ; Attarodi, G.</creatorcontrib><description>In this study, a method for determining the location and extent of myocardial infarction using BSPM data that was obtained from PhysioNet challenge 2007 database has been suggested. This data is related to the four patients with MI that we used from two patients as training set to determine rules, and from two other patients for testing set and the conclusion of the proposed model. At first, T-wave amplitude, R-wave amplitude and integration of T-wave as three features of ECG signals were extracted. Then with definition and applying several rules and threshold levels for those features, areas that are with MI and these extents were diagnosed. In this study to determine the precise location of MI, 17-segments standard model of left ventricle (LV) was used. Finally, overall accuracy of this method that expressed with SO parameter and EPD parameter for two patients in test set was obtained to 0.94 and 5.37, respectively. The main advantages of this method were its simplicity and high accuracy.</description><identifier>ISSN: 0276-6574</identifier><identifier>ISBN: 1467320765</identifier><identifier>ISBN: 9781467320764</identifier><identifier>EISSN: 2325-8853</identifier><identifier>EISBN: 9781467320757</identifier><identifier>EISBN: 9781467320771</identifier><identifier>EISBN: 1467320757</identifier><identifier>EISBN: 1467320773</identifier><language>eng</language><publisher>IEEE</publisher><subject>Electrocardiography ; Feature extraction ; Mathematical model ; Myocardium ; Torso ; Training</subject><ispartof>2012 Computing in Cardiology, 2012, p.505-508</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6420441$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>310,311,781,785,790,791,2059,54922</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6420441$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Safdarian, N.</creatorcontrib><creatorcontrib>Dabanloo, N. J.</creatorcontrib><creatorcontrib>Attarodi, G.</creatorcontrib><title>New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data</title><title>2012 Computing in Cardiology</title><addtitle>CiC</addtitle><description>In this study, a method for determining the location and extent of myocardial infarction using BSPM data that was obtained from PhysioNet challenge 2007 database has been suggested. This data is related to the four patients with MI that we used from two patients as training set to determine rules, and from two other patients for testing set and the conclusion of the proposed model. At first, T-wave amplitude, R-wave amplitude and integration of T-wave as three features of ECG signals were extracted. Then with definition and applying several rules and threshold levels for those features, areas that are with MI and these extents were diagnosed. In this study to determine the precise location of MI, 17-segments standard model of left ventricle (LV) was used. Finally, overall accuracy of this method that expressed with SO parameter and EPD parameter for two patients in test set was obtained to 0.94 and 5.37, respectively. The main advantages of this method were its simplicity and high accuracy.</description><subject>Electrocardiography</subject><subject>Feature extraction</subject><subject>Mathematical model</subject><subject>Myocardium</subject><subject>Torso</subject><subject>Training</subject><issn>0276-6574</issn><issn>2325-8853</issn><isbn>1467320765</isbn><isbn>9781467320764</isbn><isbn>9781467320757</isbn><isbn>9781467320771</isbn><isbn>1467320757</isbn><isbn>1467320773</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1jUlOw0AQRZtJIgk5AZu6gKUe3fYSojBIYZDIPiq7y6GRh6jdEYR7cF-cBFalr_ffrxM2zW0mdGqV5NbYUzaSSpoky4w6Y-N_kJpzNuLSpklqrL5k477_4FzkuTUj9vNMn-AoUhl910JD8b1zUGBPDoY8n91D79ct1lARxm2gHmJ3EELjW4K6K7H233iwsXVAX5HaCF0FzW5gwfnB9W2F4fhh2_t2Dbed28HbNlRYErx2e2Xfe8INOIx4xS4qrHua_t0JW97Nl7OHZPFy_zi7WSReWBMThcIJ7oSTKCUVnHRRulIVaWZQaCFLpXM0yhWoChJGV3lmhU25KgauSjVh18dZT0SrTfANht0q1ZJrLdQvtqpnPw</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Safdarian, N.</creator><creator>Dabanloo, N. J.</creator><creator>Attarodi, G.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201209</creationdate><title>New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data</title><author>Safdarian, N. ; Dabanloo, N. J. ; Attarodi, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-3a1d10d1d2a22eb0e4bcdc3b685a1412c349a53dba3be154f98717603b5a13c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Electrocardiography</topic><topic>Feature extraction</topic><topic>Mathematical model</topic><topic>Myocardium</topic><topic>Torso</topic><topic>Training</topic><toplevel>online_resources</toplevel><creatorcontrib>Safdarian, N.</creatorcontrib><creatorcontrib>Dabanloo, N. J.</creatorcontrib><creatorcontrib>Attarodi, G.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore Digital Library</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Safdarian, N.</au><au>Dabanloo, N. J.</au><au>Attarodi, G.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data</atitle><btitle>2012 Computing in Cardiology</btitle><stitle>CiC</stitle><date>2012-09</date><risdate>2012</risdate><spage>505</spage><epage>508</epage><pages>505-508</pages><issn>0276-6574</issn><eissn>2325-8853</eissn><isbn>1467320765</isbn><isbn>9781467320764</isbn><eisbn>9781467320757</eisbn><eisbn>9781467320771</eisbn><eisbn>1467320757</eisbn><eisbn>1467320773</eisbn><abstract>In this study, a method for determining the location and extent of myocardial infarction using BSPM data that was obtained from PhysioNet challenge 2007 database has been suggested. This data is related to the four patients with MI that we used from two patients as training set to determine rules, and from two other patients for testing set and the conclusion of the proposed model. At first, T-wave amplitude, R-wave amplitude and integration of T-wave as three features of ECG signals were extracted. Then with definition and applying several rules and threshold levels for those features, areas that are with MI and these extents were diagnosed. In this study to determine the precise location of MI, 17-segments standard model of left ventricle (LV) was used. Finally, overall accuracy of this method that expressed with SO parameter and EPD parameter for two patients in test set was obtained to 0.94 and 5.37, respectively. The main advantages of this method were its simplicity and high accuracy.</abstract><pub>IEEE</pub><tpages>4</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0276-6574
ispartof 2012 Computing in Cardiology, 2012, p.505-508
issn 0276-6574
2325-8853
language eng
recordid cdi_ieee_primary_6420441
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Electrocardiography
Feature extraction
Mathematical model
Myocardium
Torso
Training
title New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-17T17%3A53%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=New%20detection%20method%20based%20on%20ECG%20signal%20features%20to%20determine%20localization%20and%20extent%20of%20myocardial%20infarction%20using%20Body%20Surface%20Potential%20Map%20data&rft.btitle=2012%20Computing%20in%20Cardiology&rft.au=Safdarian,%20N.&rft.date=2012-09&rft.spage=505&rft.epage=508&rft.pages=505-508&rft.issn=0276-6574&rft.eissn=2325-8853&rft.isbn=1467320765&rft.isbn_list=9781467320764&rft_id=info:doi/&rft_dat=%3Cieee_6IE%3E6420441%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781467320757&rft.eisbn_list=9781467320771&rft.eisbn_list=1467320757&rft.eisbn_list=1467320773&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6420441&rfr_iscdi=true