Unsupervised Classification of Premature Ventricular Contractions Based on RR Interval and Heartbeat Morphology
Nema prikaza
Autori
Atanasoski, VladimirIvanović, Marija D.
Marinković, Miloš
Gligorić, Goran
Bojović, Boško
Shvilkin, Alexei V.
Petrović, Jovana S.
Konferencijski prilog (Objavljena verzija)
,
© 2018 IEEE
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Accurate automated detection of premature ventricular contractions from electrocardiogram requires a training set or expert intervention. We propose a fully automated unsupervised detection method. The algorithm first clusters morphologically similar heartbeats and then performs classification based on RR intervals and morphology. Tests on clinically recorded datasets show sensitivity of 94.7%, specificity of 99.6% and accuracy of 99.5%. © 2018 IEEE.
Ključne reči:
automated detection / electrocardiogram / premature ventricular contractionsIzvor:
2018 14th Symposium on Neural Networks and Applications (NEUREL), 2018, 1-6Izdavač:
- IEEE
Finansiranje / projekti:
- Capturing and quantitative analysis of multi-scale multi-channel diagnostic data. (EU-H2020-691051)
- Fotonika mikro i nano strukturnih materijala (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-45010)
DOI: 10.1109/NEUREL.2018.8586997
ISBN: 978-1-5386-6974-7
Scopus: 2-s2.0-85060914279
Kolekcije
Institucija/grupa
VinčaTY - CONF AU - Atanasoski, Vladimir AU - Ivanović, Marija D. AU - Marinković, Miloš AU - Gligorić, Goran AU - Bojović, Boško AU - Shvilkin, Alexei V. AU - Petrović, Jovana S. PY - 2018 UR - https://ieeexplore.ieee.org/document/8586997/ UR - https://vinar.vin.bg.ac.rs/handle/123456789/8050 AB - Accurate automated detection of premature ventricular contractions from electrocardiogram requires a training set or expert intervention. We propose a fully automated unsupervised detection method. The algorithm first clusters morphologically similar heartbeats and then performs classification based on RR intervals and morphology. Tests on clinically recorded datasets show sensitivity of 94.7%, specificity of 99.6% and accuracy of 99.5%. © 2018 IEEE. PB - IEEE C3 - 2018 14th Symposium on Neural Networks and Applications (NEUREL) C3 - 14th Symposium on Neural Networks and Applications (NEUREL) (2018) T1 - Unsupervised Classification of Premature Ventricular Contractions Based on RR Interval and Heartbeat Morphology SP - 1 EP - 6 DO - 10.1109/NEUREL.2018.8586997 ER -
@conference{ author = "Atanasoski, Vladimir and Ivanović, Marija D. and Marinković, Miloš and Gligorić, Goran and Bojović, Boško and Shvilkin, Alexei V. and Petrović, Jovana S.", year = "2018", abstract = "Accurate automated detection of premature ventricular contractions from electrocardiogram requires a training set or expert intervention. We propose a fully automated unsupervised detection method. The algorithm first clusters morphologically similar heartbeats and then performs classification based on RR intervals and morphology. Tests on clinically recorded datasets show sensitivity of 94.7%, specificity of 99.6% and accuracy of 99.5%. © 2018 IEEE.", publisher = "IEEE", journal = "2018 14th Symposium on Neural Networks and Applications (NEUREL), 14th Symposium on Neural Networks and Applications (NEUREL) (2018)", title = "Unsupervised Classification of Premature Ventricular Contractions Based on RR Interval and Heartbeat Morphology", pages = "1-6", doi = "10.1109/NEUREL.2018.8586997" }
Atanasoski, V., Ivanović, M. D., Marinković, M., Gligorić, G., Bojović, B., Shvilkin, A. V.,& Petrović, J. S.. (2018). Unsupervised Classification of Premature Ventricular Contractions Based on RR Interval and Heartbeat Morphology. in 2018 14th Symposium on Neural Networks and Applications (NEUREL) IEEE., 1-6. https://doi.org/10.1109/NEUREL.2018.8586997
Atanasoski V, Ivanović MD, Marinković M, Gligorić G, Bojović B, Shvilkin AV, Petrović JS. Unsupervised Classification of Premature Ventricular Contractions Based on RR Interval and Heartbeat Morphology. in 2018 14th Symposium on Neural Networks and Applications (NEUREL). 2018;:1-6. doi:10.1109/NEUREL.2018.8586997 .
Atanasoski, Vladimir, Ivanović, Marija D., Marinković, Miloš, Gligorić, Goran, Bojović, Boško, Shvilkin, Alexei V., Petrović, Jovana S., "Unsupervised Classification of Premature Ventricular Contractions Based on RR Interval and Heartbeat Morphology" in 2018 14th Symposium on Neural Networks and Applications (NEUREL) (2018):1-6, https://doi.org/10.1109/NEUREL.2018.8586997 . .