Early prediction of Paroxysmal Atrial Fibrillation using frequency domain measures of heart rate variability

Paroxysmal Atrial Fibrillation (PAF) is a very common heart disease caused by irregular impulses of atrial tissue in adult. Diagnosing in the early stages of this disorder is very important for the patients to stop the progression of the disease and to improve the life quality. In this study, it is aimed to predict the PAF event before the realization of the PAF which in 5 minutes for the PAF patients. 30-minute data used in the study were divided into 5-minute parts. Fast Fourier Transform of frequency domain measures of heart rate variability obtained easily and practically is used for each part. The statistical significances among segments and discriminating performances of k-Nearest Neighbors classifier were obtained for each segment using these measurements. Consequently, As a result of statistical analysis, it is shown that patients may be warned 12.5 minutes earlier than a PAF attack. © 2016 IEEE.

Eser Adı
[dc.title]
Early prediction of Paroxysmal Atrial Fibrillation using frequency domain measures of heart rate variability
Yazar
[dc.contributor.author]
Narin, Ali
Yazar
[dc.contributor.author]
İşler, Yalçın
Yazar
[dc.contributor.author]
Özer, Mahmut
Yayın Yılı
[dc.date.issued]
2017
Yayıncı
[dc.publisher]
Institute of Electrical and Electronics Engineers Inc.
Yayın Türü
[dc.type]
proceedings
Açıklama
[dc.description]
2016 Medical Technologies National Conference, TIPTEKNO 2016 -- 27 October 2016 through 29 October 2016 -- -- 126633
Özet
[dc.description.abstract]
Paroxysmal Atrial Fibrillation (PAF) is a very common heart disease caused by irregular impulses of atrial tissue in adult. Diagnosing in the early stages of this disorder is very important for the patients to stop the progression of the disease and to improve the life quality. In this study, it is aimed to predict the PAF event before the realization of the PAF which in 5 minutes for the PAF patients. 30-minute data used in the study were divided into 5-minute parts. Fast Fourier Transform of frequency domain measures of heart rate variability obtained easily and practically is used for each part. The statistical significances among segments and discriminating performances of k-Nearest Neighbors classifier were obtained for each segment using these measurements. Consequently, As a result of statistical analysis, it is shown that patients may be warned 12.5 minutes earlier than a PAF attack. © 2016 IEEE.
Kayıt Giriş Tarihi
[dc.date.accessioned]
2019-12-23
Açık Erişim Tarihi
[dc.date.available]
2019-12-23
Yayın Dili
[dc.language.iso]
tur
Konu Başlıkları
[dc.subject]
early prediction
Konu Başlıkları
[dc.subject]
fast fourier transform
Konu Başlıkları
[dc.subject]
heart rate variability
Konu Başlıkları
[dc.subject]
paroxysmal atrial fibrillation
Künye
[dc.identifier.citation]
Narin, A., İşler, Y. ve Özer, M. (2016). Early prediction of Paroxysmal Atrial Fibrillation using frequency domain measures of heart rate variability. 2016 Medical Technologies National Congress (TIPTEKNO) içinde (ss. 1–4). doi:10.1109/TIPTEKNO.2016.7863110
Haklar
[dc.rights]
info:eu-repo/semantics/closedAccess
Alternatif Başlık
[dc.title.alternative]
Kalp hızı değişkenliği frekans alanı ölçümleri ile paroksismal atriyal fibrilasyon atağının önceden kestirimi
Dergi Adı
[dc.relation.journal]
2016 Medical Technologies National Conference, TIPTEKNO 2016
Tek Biçim Adres
[dc.identifier.uri]
https://dx.doi.org/10.1109/TIPTEKNO.2016.7863110
Tek Biçim Adres
[dc.identifier.uri]
https://hdl.handle.net/20.500.12628/5239
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Görüntülenme
16
09.12.2022 tarihinden bu yana
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1
09.12.2022 tarihinden bu yana
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09 Şubat 2024 19:57
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patients statistical minutes obtained disease discriminating segments significances attack practically easily variability performances k-Nearest Consequently analysis result warned measures measurements Neighbors segment classifier earlier Paroxysmal domain tissue important disorder stages Diagnosing atrial improve impulses irregular
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