| Selection of myocardial electrogram features for use by implantable devices. | |
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MedLine Citation:
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PMID: 8258439 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Implantable devices that terminate ventricular tachycardia must be capable of correctly classifying heart rhythms to a high degree of reliability. We evaluated the relative discriminating power of several myocardial electrogram (ME) features in six human subjects by reducing the order of their corresponding feature spaces using three different optimization methods: 1) minimizing univariate Bayes error rates (univariate parametric), 2) maximizing the Kullback divergence (multivariate parametric), and 3) pruning classification trees (nonparametric). We found that although the composition of the optimal subspaces varied considerably from one subject to another, one frequency domain feature was common to most of the optimal subspaces. |
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Authors:
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W J Gibb; D M Auslander; J C Griffin |
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Publication Detail:
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Type: Journal Article; Research Support, U.S. Gov't, P.H.S. |
Journal Detail:
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Title: IEEE transactions on bio-medical engineering Volume: 40 ISSN: 0018-9294 ISO Abbreviation: IEEE Trans Biomed Eng Publication Date: 1993 Aug |
Date Detail:
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Created Date: 1994-01-19 Completed Date: 1994-01-19 Revised Date: 2009-11-11 |
Medline Journal Info:
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Nlm Unique ID: 0012737 Medline TA: IEEE Trans Biomed Eng Country: UNITED STATES |
Other Details:
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Languages: eng Pagination: 727-35 Citation Subset: IM |
Affiliation:
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Cardiovascular Research Institute, University of California, San Francisco 94143. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Bayes Theorem Decision Trees Electrocardiography / instrumentation, methods*, statistics & numerical data Equipment Design Heart Rate* Humans Multivariate Analysis Pacemaker, Artificial* / statistics & numerical data Regression Analysis Sinoatrial Node / physiology Tachycardia, Atrioventricular Nodal Reentry / diagnosis, physiopathology, therapy Ventricular Function |
| Grant Support | |
ID/Acronym/Agency:
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HL35008/HL/NHLBI NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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