Effect of linear and non-linear measurements of heart rate variability in prediction of PAF attack

Paroxysmal Atrial Fibrillation (PAF) is a very common rhythm disorder that causes rapid and irregular impulses in the heart. In this study, it is aimed to determine whether patients can be warned before PAF events. 30-minute HRV data used in this study. Each piece of data was divided into 10 pieces of 5-minute parts. Time domain measurements from linear measurements of HRV and Poincare measurements from nonlinear measurements of HRV were used for each segment. Detecting performances were measured for each segment using k-nearest neighbor classifier. Particularly linear measurements have been shown to achieve up to 82% success in predicting PAF attack and was observed that PAF attack could be detected 12,5 minutes earlier. © 2017 IEEE.

Eser Adı
[dc.title]
Effect of linear and non-linear measurements of heart rate variability in prediction of PAF attack
Yazar
[dc.contributor.author]
Narin, Ali
Yazar
[dc.contributor.author]
Özer, Mahmut
Yazar
[dc.contributor.author]
İşler, Yalçın
Yayın Yılı
[dc.date.issued]
2017
Yayıncı
[dc.publisher]
Institute of Electrical and Electronics Engineers Inc.
Yayın Türü
[dc.type]
proceedings
Açıklama
[dc.description]
25th Signal Processing and Communications Applications Conference, SIU 2017 -- 15 May 2017 through 18 May 2017 -- -- 128703
Özet
[dc.description.abstract]
Paroxysmal Atrial Fibrillation (PAF) is a very common rhythm disorder that causes rapid and irregular impulses in the heart. In this study, it is aimed to determine whether patients can be warned before PAF events. 30-minute HRV data used in this study. Each piece of data was divided into 10 pieces of 5-minute parts. Time domain measurements from linear measurements of HRV and Poincare measurements from nonlinear measurements of HRV were used for each segment. Detecting performances were measured for each segment using k-nearest neighbor classifier. Particularly linear measurements have been shown to achieve up to 82% success in predicting PAF attack and was observed that PAF attack could be detected 12,5 minutes earlier. © 2017 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]
paroxysmal atrial fibrillation
Konu Başlıkları
[dc.subject]
poincare plot
Konu Başlıkları
[dc.subject]
prediction
Konu Başlıkları
[dc.subject]
time domain measures
Künye
[dc.identifier.citation]
Narin, A., Özer, M. ve İşler, Y. (2017). Effect of linear and non-linear measurements of heart rate variability in prediction of PAF attack. 2017 25th Signal Processing and Communications Applications Conference (SIU) içinde (ss. 1–4). doi:10.1109/SIU.2017.7960358
Haklar
[dc.rights]
info:eu-repo/semantics/closedAccess
Alternatif Başlık
[dc.title.alternative]
Kalp hızı değişkenliği doğrusal ve doğrusal olmayan ölçümlerinin PAF atağı tespitine etkisi
Dergi Adı
[dc.relation.journal]
2017 25th Signal Processing and Communications Applications Conference, SIU 2017
Tek Biçim Adres
[dc.identifier.uri]
https://dx.doi.org/10.1109/SIU.2017.7960358
Tek Biçim Adres
[dc.identifier.uri]
https://hdl.handle.net/20.500.12628/5328
Görüntülenme Sayısı ( Şehir )
Görüntülenme Sayısı ( Ülke )
Görüntülenme Sayısı ( Zaman Dağılımı )
Görüntülenme
18
09.12.2022 tarihinden bu yana
İndirme
1
09.12.2022 tarihinden bu yana
Son Erişim Tarihi
08 Şubat 2024 00:44
Google Kontrol
Tıklayınız
measurements attack linear segment neighbor measured nonlinear performances Poincare k-nearest Detecting Paroxysmal classifier detected earlier minutes Particularly observed predicting success achieve domain causes impulses irregular disorder rhythm common Fibrillation determine 5-minute pieces Atrial divided whether
6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında yükümlülüklerimiz ve çerez politikamız hakkında bilgi sahibi olmak için alttaki bağlantıyı kullanabilirsiniz.

creativecommons
Bu site altında yer alan tüm kaynaklar Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.
Platforms