| P-wave morphology assessment by a gaussian functions-based model in atrial fibrillation patients. | |
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MedLine Citation:
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PMID: 17405373 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Aim of this study was to present a P-wave model, based on a linear combination of Gaussian functions, to quantify morphological aspects of P-wave in patients prone to atrial fibrillation (AF). Five-minute ECG recordings were performed in 25 patients with permanent dual chamber pacemakers. Patients were divided into high-risk and low-risk groups, including patients with and without AF episodes in the last 6 mo preceding the study, respectively. ECG signals were acquired using a 32-lead mapping system for high-resolution biopotential measurement (ActiveTwo, Biosemi, The Netherlands, sample frequency 2 kHz, 24-bit resolution). Up to 8 Gaussian models have been computed for each averaged P-wave extracted from every lead. The P-wave morphology was evaluated by extracting seven parameters. Classical time-domain parameters, based on P-wave duration estimation, have been also estimated. We found that the P-wave morphology can be effectively modeled by a linear combination of Gaussian functions. In addition, the combination of time-domain and morphological parameters extracted from the Gaussian function-based model of the P-wave improves the identification of patients having different risks of developing AF. |
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Authors:
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Federica Censi; G Calcagnini; C Ricci; R P Ricci; M Santini; A Grammatico; P Bartolini |
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Publication Detail:
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Type: Evaluation Studies; Journal Article |
Journal Detail:
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Title: IEEE transactions on bio-medical engineering Volume: 54 ISSN: 0018-9294 ISO Abbreviation: IEEE Trans Biomed Eng Publication Date: 2007 Apr |
Date Detail:
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Created Date: 2007-04-04 Completed Date: 2007-04-24 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: 663-72 Citation Subset: IM |
Affiliation:
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Department of Technologies and Health, Istituto Superiore di Sanità, Rome 00161, Italy. censi@iss.it |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Aged Algorithms* Artificial Intelligence Atrial Fibrillation / diagnosis*, physiopathology* Computer Simulation Diagnosis, Computer-Assisted / methods* Electrocardiography / methods* Female Humans Male Models, Cardiovascular* Models, Statistical Normal Distribution Pattern Recognition, Automated / methods* Reproducibility of Results Sensitivity and Specificity |
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