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Article: New Bayesian discriminator for detection of atrial tachyarrhythmias

TitleNew Bayesian discriminator for detection of atrial tachyarrhythmias
Authors
KeywordsAtrium
Fibrillation
Intervals
Pacemakers
Tachyarrhythmias
Issue Date2002
PublisherLippincott Williams & Wilkins. The Journal's web site is located at http://circ.ahajournals.org
Citation
Circulation, 2002, v. 105 n. 12, p. 1472-1479 How to Cite?
AbstractBackground - Accurate, rapid detection of atrial tachyarrhythmias has important implications in the use of implantable devices for treatment of cardiac arrhythmia. Currently available detection algorithms for atrial tachyarrhythmias, which use the single-index method, have limited sensitivity and specificity. Methods and Results - In this study, we evaluated the performance of a new Bayesian discriminator algorithm in the detection of atrial fibrillation (AF), atrial flutter (AFL), and sinus rhythm (SR). Bipolar recording of 364 rhythms (AF=156, AFL=88, SR=120) at the high right atrium were collected from 20 patients who underwent electrophysiological procedures. After initial signal processing, a column vector of 5 features for each rhythm were established, based on the regularity, rate, energy distribution, percent time of quiet interval, and baseline reaching of the rectified autocorrelation coefficient functions. Rhythm identification was obtained by use of Bayes decision rule and assumption of Gaussian distribution. For the new Bayesian discriminator, the overall sensitivity for detection of SR, AF, and AFL was 97%, 97%, and 94%, respectively; and the overall specificity for detection of SR, AF, and AFL was 98%, 98%, and 99%, respectively. The overall accuracy of detection of SR, AF, and AFL was 98%, 97% and 98%, respectively. Furthermore, sensitivity, specificity, and accuracy of this algorithm were not affected by a range of white Gaussian noises with different intensities. Conclusions - This new Bayesian discriminator algorithm, based on Bayes decision of multiple features of atrial electrograms, allows rapid on-line and accurate (98%) detection of AF with robust anti-noise performance.
Persistent Identifierhttp://hdl.handle.net/10722/78489
ISSN
2015 Impact Factor: 17.047
2015 SCImago Journal Rankings: 7.853
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorXu, Wen_HK
dc.contributor.authorTse, HFen_HK
dc.contributor.authorChan, FHYen_HK
dc.contributor.authorFung, PCWen_HK
dc.contributor.authorLee, KLFen_HK
dc.contributor.authorLau, CPen_HK
dc.date.accessioned2010-09-06T07:43:28Z-
dc.date.available2010-09-06T07:43:28Z-
dc.date.issued2002en_HK
dc.identifier.citationCirculation, 2002, v. 105 n. 12, p. 1472-1479en_HK
dc.identifier.issn0009-7322en_HK
dc.identifier.urihttp://hdl.handle.net/10722/78489-
dc.description.abstractBackground - Accurate, rapid detection of atrial tachyarrhythmias has important implications in the use of implantable devices for treatment of cardiac arrhythmia. Currently available detection algorithms for atrial tachyarrhythmias, which use the single-index method, have limited sensitivity and specificity. Methods and Results - In this study, we evaluated the performance of a new Bayesian discriminator algorithm in the detection of atrial fibrillation (AF), atrial flutter (AFL), and sinus rhythm (SR). Bipolar recording of 364 rhythms (AF=156, AFL=88, SR=120) at the high right atrium were collected from 20 patients who underwent electrophysiological procedures. After initial signal processing, a column vector of 5 features for each rhythm were established, based on the regularity, rate, energy distribution, percent time of quiet interval, and baseline reaching of the rectified autocorrelation coefficient functions. Rhythm identification was obtained by use of Bayes decision rule and assumption of Gaussian distribution. For the new Bayesian discriminator, the overall sensitivity for detection of SR, AF, and AFL was 97%, 97%, and 94%, respectively; and the overall specificity for detection of SR, AF, and AFL was 98%, 98%, and 99%, respectively. The overall accuracy of detection of SR, AF, and AFL was 98%, 97% and 98%, respectively. Furthermore, sensitivity, specificity, and accuracy of this algorithm were not affected by a range of white Gaussian noises with different intensities. Conclusions - This new Bayesian discriminator algorithm, based on Bayes decision of multiple features of atrial electrograms, allows rapid on-line and accurate (98%) detection of AF with robust anti-noise performance.en_HK
dc.languageengen_HK
dc.publisherLippincott Williams & Wilkins. The Journal's web site is located at http://circ.ahajournals.orgen_HK
dc.relation.ispartofCirculationen_HK
dc.subjectAtriumen_HK
dc.subjectFibrillationen_HK
dc.subjectIntervalsen_HK
dc.subjectPacemakersen_HK
dc.subjectTachyarrhythmiasen_HK
dc.subject.meshAlgorithms-
dc.subject.meshBayes Theorem-
dc.subject.meshHeart Atria - physiopathology-
dc.subject.meshSignal Processing, Computer-Assisted-
dc.subject.meshTachycardia - diagnosis - physiopathology-
dc.titleNew Bayesian discriminator for detection of atrial tachyarrhythmiasen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0009-7322&volume=105&issue=12&spage=1472&epage=1479&date=2002&atitle=New+Bayesian+discriminator+for+detection+of+atrial+tachyarrhythmiasen_HK
dc.identifier.emailXu, W: wcxu@eee.hku.hken_HK
dc.identifier.emailTse, HF: hftse@hkucc.hku.hken_HK
dc.identifier.authorityXu, W=rp00198en_HK
dc.identifier.authorityTse, HF=rp00428en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1161/01.CIR.0000012349.14270.54en_HK
dc.identifier.pmid11914257-
dc.identifier.scopuseid_2-s2.0-0037177184en_HK
dc.identifier.hkuros72145en_HK
dc.identifier.hkuros100795-
dc.identifier.hkuros115092-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0037177184&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume105en_HK
dc.identifier.issue12en_HK
dc.identifier.spage1472en_HK
dc.identifier.epage1479en_HK
dc.identifier.isiWOS:000174686900025-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridXu, W=7404428876en_HK
dc.identifier.scopusauthoridTse, HF=7006070805en_HK
dc.identifier.scopusauthoridChan, FHY=7202586429en_HK
dc.identifier.scopusauthoridFung, PCW=7101613315en_HK
dc.identifier.scopusauthoridLee, KLF=7501505962en_HK
dc.identifier.scopusauthoridLau, CP=7401968501en_HK

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