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.
Yazar |
Narin, Ali İşler, Yalçın Özer, Mahmut |
Yayın Türü | Proceedings |
Tek Biçim Adres | https://hdl.handle.net/20.500.12628/5239 |
Tek Biçim Adres | 10.1109/TIPTEKNO.2016.7863110 |
Konu Başlıkları |
early prediction
fast fourier transform heart rate variability paroxysmal atrial fibrillation |
Koleksiyonlar |
Fakülteler Mühendislik Fakültesi Elektrik - Elektronik Mühendisliği Bölümü Bildiri Koleksiyonu (Elektrik - Elektronik Mühendisliği Bölümü) Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed | SOBİAD Scopus İndeksli Yayınlar Koleksiyonu Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed | SOBİAD WoS İndeksli Yayınlar Koleksiyonu |
Dergi Adı | 2016 Medical Technologies National Conference, TIPTEKNO 2016 |
Sayfalar | - |
Yayın Yılı | 2017 |
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 |