A Simple Method to Detect Atrial Fibrillation Using RR Intervals

Implantable loop recorders have been developed for long-term monitoring of cardiac arrhythmia, but their accuracy for atrial fibrillation (AF) detection is unsatisfactory. We sought to develop and evaluate a simple method for detecting AF using RR intervals. The new AF detection algorithm is based o...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The American journal of cardiology 2011-05, Vol.107 (10), p.1494-1497
Hauptverfasser: Lian, Jie, PhD, Wang, Lian, MS, Muessig, Dirk, PhD
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1497
container_issue 10
container_start_page 1494
container_title The American journal of cardiology
container_volume 107
creator Lian, Jie, PhD
Wang, Lian, MS
Muessig, Dirk, PhD
description Implantable loop recorders have been developed for long-term monitoring of cardiac arrhythmia, but their accuracy for atrial fibrillation (AF) detection is unsatisfactory. We sought to develop and evaluate a simple method for detecting AF using RR intervals. The new AF detection algorithm is based on a map that plots RR intervals versus change of RR intervals (RdR). The map is divided by a grid with 25-ms resolution in 2 axes and nonempty cells are counted to classify AF and non-AF episodes. We evaluated the performance of the method using 4 PhysioNet databases: MIT-BIH AF database, MIT-BIH arrhythmia database, MIT-BIH normal sinus rhythm (NSR) database, and NSR RR interval database (total 145 patients, 1,826 hours NSR, 96 hours AF, and 11 hours other rhythms). Each record is divided into consecutive windows containing 32, 64, or 128 RR intervals. AF detection is performed for each window and classification results are compared to annotations. A window is labeled true AF if >1/2 of cycles in the window are annotated as AF or non-AF otherwise. The RdR map shows signature patterns corresponding to various heart rhythms. Optimal nonempty cell cut-off threshold for AF detection was determined by receiver operating characteristic curve analysis, which yields excellent sensitivity and specificity for window sizes 32 (94.4% and 92.6%, respectively), 64 (95.8% and 94.3%), and 128 (95.9% and 95.4%). In conclusion, a single metric derived from the RdR map can achieve robust AF detection within as few as 32 heart beats.
doi_str_mv 10.1016/j.amjcard.2011.01.028
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_864965392</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0002914911003407</els_id><sourcerecordid>2351934821</sourcerecordid><originalsourceid>FETCH-LOGICAL-c542t-25681f95a9f380a343aba951d1bb5ed148452a543b8f6d5b4c75989080fa72153</originalsourceid><addsrcrecordid>eNqFkl1rFTEQhoMo9lj9CcoiiFd7nMnHbnKjHlqrhYrQ2uuQzWY1634ck5xC_32znmOF3ggDQ-CZN--8DCEvEdYIWL3r12bsrQntmgLiGnJR-YisUNaqRIXsMVkBAC0VcnVEnsXY5yeiqJ6SI4qcAlR8RT5uiis_bgdXfHXp59wWaS5OXXI2FZsUvBmKM98EPwwm-XkqrqOffhSXl8X5lFy4MUN8Tp50ubkXh35Mrs8-fT_5Ul58-3x-srkoreA0lVRUEjsljOqYBMM4M41RAltsGuFa5JILagRnjeyqVjTc1kJJBRI6U1MU7Ji83etuw_x752LSo4_WZWOTm3dRy4qrSjBFM_n6AdnPuzBlcxmqBUUlVIbEHrJhjjG4Tm-DH0241Qh6CVj3-hCwXgLWkIvKPPfqIL5rRtfeT_1NNANvDoCJ1gxdMJP18R-3YPDH5Yc953JoN94FHa13k3WtDzl93c7-v1beP1Cwg598_vSXu3XxfmnUkWrQV8s1LMeACMA41OwODEWs6A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>867521959</pqid></control><display><type>article</type><title>A Simple Method to Detect Atrial Fibrillation Using RR Intervals</title><source>MEDLINE</source><source>Access via ScienceDirect (Elsevier)</source><creator>Lian, Jie, PhD ; Wang, Lian, MS ; Muessig, Dirk, PhD</creator><creatorcontrib>Lian, Jie, PhD ; Wang, Lian, MS ; Muessig, Dirk, PhD</creatorcontrib><description>Implantable loop recorders have been developed for long-term monitoring of cardiac arrhythmia, but their accuracy for atrial fibrillation (AF) detection is unsatisfactory. We sought to develop and evaluate a simple method for detecting AF using RR intervals. The new AF detection algorithm is based on a map that plots RR intervals versus change of RR intervals (RdR). The map is divided by a grid with 25-ms resolution in 2 axes and nonempty cells are counted to classify AF and non-AF episodes. We evaluated the performance of the method using 4 PhysioNet databases: MIT-BIH AF database, MIT-BIH arrhythmia database, MIT-BIH normal sinus rhythm (NSR) database, and NSR RR interval database (total 145 patients, 1,826 hours NSR, 96 hours AF, and 11 hours other rhythms). Each record is divided into consecutive windows containing 32, 64, or 128 RR intervals. AF detection is performed for each window and classification results are compared to annotations. A window is labeled true AF if &gt;1/2 of cycles in the window are annotated as AF or non-AF otherwise. The RdR map shows signature patterns corresponding to various heart rhythms. Optimal nonempty cell cut-off threshold for AF detection was determined by receiver operating characteristic curve analysis, which yields excellent sensitivity and specificity for window sizes 32 (94.4% and 92.6%, respectively), 64 (95.8% and 94.3%), and 128 (95.9% and 95.4%). In conclusion, a single metric derived from the RdR map can achieve robust AF detection within as few as 32 heart beats.</description><identifier>ISSN: 0002-9149</identifier><identifier>EISSN: 1879-1913</identifier><identifier>DOI: 10.1016/j.amjcard.2011.01.028</identifier><identifier>PMID: 21420064</identifier><identifier>CODEN: AJCDAG</identifier><language>eng</language><publisher>New York, NY: Elsevier Inc</publisher><subject>Algorithms ; Atrial Fibrillation - diagnosis ; Biological and medical sciences ; Cardiac arrhythmia ; Cardiac dysrhythmias ; Cardiology ; Cardiology. Vascular system ; Cardiovascular ; Circadian rhythm ; Comparative analysis ; Databases, Factual ; Electrocardiography ; Heart ; Humans ; Medical sciences ; Performance evaluation ; Sensitivity and Specificity</subject><ispartof>The American journal of cardiology, 2011-05, Vol.107 (10), p.1494-1497</ispartof><rights>Elsevier Inc.</rights><rights>2011 Elsevier Inc.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2011 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Sequoia S.A. May 15, 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c542t-25681f95a9f380a343aba951d1bb5ed148452a543b8f6d5b4c75989080fa72153</citedby><cites>FETCH-LOGICAL-c542t-25681f95a9f380a343aba951d1bb5ed148452a543b8f6d5b4c75989080fa72153</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.amjcard.2011.01.028$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=24200092$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21420064$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lian, Jie, PhD</creatorcontrib><creatorcontrib>Wang, Lian, MS</creatorcontrib><creatorcontrib>Muessig, Dirk, PhD</creatorcontrib><title>A Simple Method to Detect Atrial Fibrillation Using RR Intervals</title><title>The American journal of cardiology</title><addtitle>Am J Cardiol</addtitle><description>Implantable loop recorders have been developed for long-term monitoring of cardiac arrhythmia, but their accuracy for atrial fibrillation (AF) detection is unsatisfactory. We sought to develop and evaluate a simple method for detecting AF using RR intervals. The new AF detection algorithm is based on a map that plots RR intervals versus change of RR intervals (RdR). The map is divided by a grid with 25-ms resolution in 2 axes and nonempty cells are counted to classify AF and non-AF episodes. We evaluated the performance of the method using 4 PhysioNet databases: MIT-BIH AF database, MIT-BIH arrhythmia database, MIT-BIH normal sinus rhythm (NSR) database, and NSR RR interval database (total 145 patients, 1,826 hours NSR, 96 hours AF, and 11 hours other rhythms). Each record is divided into consecutive windows containing 32, 64, or 128 RR intervals. AF detection is performed for each window and classification results are compared to annotations. A window is labeled true AF if &gt;1/2 of cycles in the window are annotated as AF or non-AF otherwise. The RdR map shows signature patterns corresponding to various heart rhythms. Optimal nonempty cell cut-off threshold for AF detection was determined by receiver operating characteristic curve analysis, which yields excellent sensitivity and specificity for window sizes 32 (94.4% and 92.6%, respectively), 64 (95.8% and 94.3%), and 128 (95.9% and 95.4%). In conclusion, a single metric derived from the RdR map can achieve robust AF detection within as few as 32 heart beats.</description><subject>Algorithms</subject><subject>Atrial Fibrillation - diagnosis</subject><subject>Biological and medical sciences</subject><subject>Cardiac arrhythmia</subject><subject>Cardiac dysrhythmias</subject><subject>Cardiology</subject><subject>Cardiology. Vascular system</subject><subject>Cardiovascular</subject><subject>Circadian rhythm</subject><subject>Comparative analysis</subject><subject>Databases, Factual</subject><subject>Electrocardiography</subject><subject>Heart</subject><subject>Humans</subject><subject>Medical sciences</subject><subject>Performance evaluation</subject><subject>Sensitivity and Specificity</subject><issn>0002-9149</issn><issn>1879-1913</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkl1rFTEQhoMo9lj9CcoiiFd7nMnHbnKjHlqrhYrQ2uuQzWY1634ck5xC_32znmOF3ggDQ-CZN--8DCEvEdYIWL3r12bsrQntmgLiGnJR-YisUNaqRIXsMVkBAC0VcnVEnsXY5yeiqJ6SI4qcAlR8RT5uiis_bgdXfHXp59wWaS5OXXI2FZsUvBmKM98EPwwm-XkqrqOffhSXl8X5lFy4MUN8Tp50ubkXh35Mrs8-fT_5Ul58-3x-srkoreA0lVRUEjsljOqYBMM4M41RAltsGuFa5JILagRnjeyqVjTc1kJJBRI6U1MU7Ji83etuw_x752LSo4_WZWOTm3dRy4qrSjBFM_n6AdnPuzBlcxmqBUUlVIbEHrJhjjG4Tm-DH0241Qh6CVj3-hCwXgLWkIvKPPfqIL5rRtfeT_1NNANvDoCJ1gxdMJP18R-3YPDH5Yc953JoN94FHa13k3WtDzl93c7-v1beP1Cwg598_vSXu3XxfmnUkWrQV8s1LMeACMA41OwODEWs6A</recordid><startdate>20110515</startdate><enddate>20110515</enddate><creator>Lian, Jie, PhD</creator><creator>Wang, Lian, MS</creator><creator>Muessig, Dirk, PhD</creator><general>Elsevier Inc</general><general>Elsevier</general><general>Elsevier Limited</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TS</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>NAPCQ</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20110515</creationdate><title>A Simple Method to Detect Atrial Fibrillation Using RR Intervals</title><author>Lian, Jie, PhD ; Wang, Lian, MS ; Muessig, Dirk, PhD</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c542t-25681f95a9f380a343aba951d1bb5ed148452a543b8f6d5b4c75989080fa72153</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Atrial Fibrillation - diagnosis</topic><topic>Biological and medical sciences</topic><topic>Cardiac arrhythmia</topic><topic>Cardiac dysrhythmias</topic><topic>Cardiology</topic><topic>Cardiology. Vascular system</topic><topic>Cardiovascular</topic><topic>Circadian rhythm</topic><topic>Comparative analysis</topic><topic>Databases, Factual</topic><topic>Electrocardiography</topic><topic>Heart</topic><topic>Humans</topic><topic>Medical sciences</topic><topic>Performance evaluation</topic><topic>Sensitivity and Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lian, Jie, PhD</creatorcontrib><creatorcontrib>Wang, Lian, MS</creatorcontrib><creatorcontrib>Muessig, Dirk, PhD</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Physical Education Index</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>The American journal of cardiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lian, Jie, PhD</au><au>Wang, Lian, MS</au><au>Muessig, Dirk, PhD</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Simple Method to Detect Atrial Fibrillation Using RR Intervals</atitle><jtitle>The American journal of cardiology</jtitle><addtitle>Am J Cardiol</addtitle><date>2011-05-15</date><risdate>2011</risdate><volume>107</volume><issue>10</issue><spage>1494</spage><epage>1497</epage><pages>1494-1497</pages><issn>0002-9149</issn><eissn>1879-1913</eissn><coden>AJCDAG</coden><abstract>Implantable loop recorders have been developed for long-term monitoring of cardiac arrhythmia, but their accuracy for atrial fibrillation (AF) detection is unsatisfactory. We sought to develop and evaluate a simple method for detecting AF using RR intervals. The new AF detection algorithm is based on a map that plots RR intervals versus change of RR intervals (RdR). The map is divided by a grid with 25-ms resolution in 2 axes and nonempty cells are counted to classify AF and non-AF episodes. We evaluated the performance of the method using 4 PhysioNet databases: MIT-BIH AF database, MIT-BIH arrhythmia database, MIT-BIH normal sinus rhythm (NSR) database, and NSR RR interval database (total 145 patients, 1,826 hours NSR, 96 hours AF, and 11 hours other rhythms). Each record is divided into consecutive windows containing 32, 64, or 128 RR intervals. AF detection is performed for each window and classification results are compared to annotations. A window is labeled true AF if &gt;1/2 of cycles in the window are annotated as AF or non-AF otherwise. The RdR map shows signature patterns corresponding to various heart rhythms. Optimal nonempty cell cut-off threshold for AF detection was determined by receiver operating characteristic curve analysis, which yields excellent sensitivity and specificity for window sizes 32 (94.4% and 92.6%, respectively), 64 (95.8% and 94.3%), and 128 (95.9% and 95.4%). In conclusion, a single metric derived from the RdR map can achieve robust AF detection within as few as 32 heart beats.</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><pmid>21420064</pmid><doi>10.1016/j.amjcard.2011.01.028</doi><tpages>4</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0002-9149
ispartof The American journal of cardiology, 2011-05, Vol.107 (10), p.1494-1497
issn 0002-9149
1879-1913
language eng
recordid cdi_proquest_miscellaneous_864965392
source MEDLINE; Access via ScienceDirect (Elsevier)
subjects Algorithms
Atrial Fibrillation - diagnosis
Biological and medical sciences
Cardiac arrhythmia
Cardiac dysrhythmias
Cardiology
Cardiology. Vascular system
Cardiovascular
Circadian rhythm
Comparative analysis
Databases, Factual
Electrocardiography
Heart
Humans
Medical sciences
Performance evaluation
Sensitivity and Specificity
title A Simple Method to Detect Atrial Fibrillation Using RR Intervals
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T21%3A12%3A59IST&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=A%20Simple%20Method%20to%20Detect%20Atrial%20Fibrillation%20Using%20RR%20Intervals&rft.jtitle=The%20American%20journal%20of%20cardiology&rft.au=Lian,%20Jie,%20PhD&rft.date=2011-05-15&rft.volume=107&rft.issue=10&rft.spage=1494&rft.epage=1497&rft.pages=1494-1497&rft.issn=0002-9149&rft.eissn=1879-1913&rft.coden=AJCDAG&rft_id=info:doi/10.1016/j.amjcard.2011.01.028&rft_dat=%3Cproquest_cross%3E2351934821%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=867521959&rft_id=info:pmid/21420064&rft_els_id=S0002914911003407&rfr_iscdi=true