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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2020-Jun-29
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  3/2020 - 6

Effective Wavelet Algorithm for an Automatic Detection of Atrial Fibrillation

ARVINTI, B. See more information about ARVINTI, B. on SCOPUS See more information about ARVINTI, B. on IEEExplore See more information about ARVINTI, B. on Web of Science, ISAR, A. See more information about  ISAR, A. on SCOPUS See more information about  ISAR, A. on SCOPUS See more information about ISAR, A. on Web of Science, COSTACHE, M. See more information about COSTACHE, M. on SCOPUS See more information about COSTACHE, M. on SCOPUS See more information about COSTACHE, M. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,545 KB) | Citation | Downloads: 45 | Views: 68

Author keywords
adaptive algorithms, biomedical signal processing, performance evaluation, threshold, wavelet

References keywords
fibrillation(13), atrial(13), wavelet(7), cardiology(6), wavelets(4), transform(4), signals(4), optim(4), heart(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-08-31
Volume 20, Issue 3, Year 2020, On page(s): 49 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.03006
Web of Science Accession Number: 000564453800006
SCOPUS ID: 85090361684

Abstract
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Cardiac anomalies are usually marked through irregular cardiac cycles. Atrial fibrillation is given through a rapid beating of the atria, announcing a possible heart failure or stroke. Electrocardiograms are an efficient way of supervising the electric activity of the heart. We have developed an effective, simple to implement automatic detection algorithm for identifying changes of the cardiac rhythm. The algorithm is based on wavelets and an enhanced time domain thresholding procedure. We take into account a variation of the electrocardiograms amplitudes, to avoid loss of clinical features. The interval between beats is computed and provided for a reliable diagnosis. The results are validated both with objective evaluation criteria and displayed graphically, assisting the medical diagnosis procedure.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 6,248 TCR
SCOPUS® Citations for all references: 8,578 TCR

Web of Science® Average Citations per reference: 208 ACR
SCOPUS® Average Citations per reference: 286 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2020-09-26 11:39 in 185 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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