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Comparison of publicly available beat detection algorithms performanances on the ECGs obtained by a patch ECG device
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-0545-2335
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-2457-3079
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1940-1747
Jolef Stefan Inst, Dept Inst Commun Syst, Ljubljana, Slovenia..
2019 (English)In: 2019 42ND INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO) / [ed] Koricic, M Butkovic, Z Skala, K Car, Z CicinSain, M Babic, S Sruk, V Skvorc, D Ribaric, S Gros, S Vrdoljak, B Mauher, M Tijan, E Pale, P Huljenic, D Grbac, TG Janjic, M, IEEE , 2019, p. 275-278Conference paper, Published paper (Refereed)
Abstract [en]

Eight ECG beat detection algorithms, from the PhysioNet's WFDR and Cardiovascular Signal toolboxes, were tested on twenty measurements, obtained by the Savvy patch ECG device, for their accuracy in beat detection. On each subject, one measurement is obtained while sitting and one while running. Each measurement lasted from thirty seconds to one minute. The measurements obtained while running were more challenging for all the algorithms, as most of them almost perfectly detected all the beats on the measurements obtained in sitting position. However, when applied on the measurements obtained while running, all the algorithms have performed with decreased accuracy. Considering overall percentage of the faulty detected peaks, the four best algorithms were jqrs, from the Cardiovascular Signal Toolbox, and ecgpuwave, gqrs, and wqrs, from the WEDB Toolbox, with percentages of faulty detected beats 1.7, 2.3, 2.9, and 3, respectively.

Place, publisher, year, edition, pages
IEEE , 2019. p. 275-278
Keywords [en]
Patch ECG, R-peaks, heat detection, heart rate, telemonitoring, remote health monitoring
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-45375ISI: 000484544500052ISBN: 978-953-233-098-4 (print)OAI: oai:DiVA.org:mdh-45375DiVA, id: diva2:1357333
Conference
2019 42ND INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO)
Available from: 2019-10-03 Created: 2019-10-03 Last updated: 2022-11-09Bibliographically approved

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Tomasic, IvanPetrovic, NikolaLindén, Maria

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