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Detection of Atrial Fibrillation from Short ECGs: Minimalistic Complexity Analysis for Feature-Based Classifiers
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0002-6032-6155
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-0069-640x
Umeå University, Umeå, Sweden.
2018 (English)In: Computing in Cardiology 2018: Proceedings / [ed] Christine Pickett; Cristiana Corsi; Pablo Laguna; Rob MacLeod, IEEE, 2018Conference paper, Published paper (Refereed)
Abstract [en]

In order to facilitate data-driven solutions for early detection of atrial fibrillation (AF), the 2017 CinC conference challenge was devoted to automatic AF classification based on short ECG recordings. The proposed solutions concentrated on maximizing the classifiers F 1 score, whereas the complexity of the classifiers was not considered. However, we argue that this must be addressed as complexity places restrictions on the applicability of inexpensive devices for AF monitoring outside hospitals. Therefore, this study investigates the feasibility of complexity reduction by analyzing one of the solutions presented for the challenge.

Place, publisher, year, edition, pages
IEEE, 2018.
Series
Computing in Cardiology Conference (CinC), E-ISSN 2325-887X ; 45
National Category
Computer Sciences Cardiology and Cardiovascular Disease
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-86224DOI: 10.22489/CinC.2018.147ISI: 000482598700249Scopus ID: 2-s2.0-85068742924OAI: oai:DiVA.org:ltu-86224DiVA, id: diva2:1576744
Conference
45th Computing in Cardiology (CinC 2018), Maastricht, The Netherlands, September 23-26, 2018
Note

ISBN för värdpublikation: 978-1-7281-0958-9;

Finansiär: PERCCOM Erasmus Mundus Program of the European Union(PERCCOM-FPA 2013-0231)

Available from: 2021-07-01 Created: 2021-07-01 Last updated: 2025-02-10Bibliographically approved

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Kleyko, DenisOsipov, Evgeny

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