mdh.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Comparison of publicly available beat detection algorithms performances on the ECGs obtained by a patch ECG device
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-2457-3079
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0003-1940-1747
Jožef Stefan Institute, Department of Communication Systems, Ljubljana, Slovenia.
2019 (engelsk)Inngår i: 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2019, s. 275-278Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Eight ECG beat detection algorithms, from the PhysioNet's WFDB 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 WFDB Toolbox, with percentages of faulty detected beats 1.7, 2.3, 2.9, and 3, respectively. 

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers Inc. , 2019. s. 275-278
Emneord [en]
Beat detection, Heart rate, Patch ECG, R-peaks, Remote health monitoring, Telemonitoring, Electrocardiography, Microelectronics, Telemedicine, Heart rates, Tele-monitoring, Signal detection
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-45016DOI: 10.23919/MIPRO.2019.8756769Scopus ID: 2-s2.0-85070300696ISBN: 9789532330984 (tryckt)OAI: oai:DiVA.org:mdh-45016DiVA, id: diva2:1343081
Konferanse
42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019, 20 May 2019 through 24 May 2019
Tilgjengelig fra: 2019-08-15 Laget: 2019-08-15 Sist oppdatert: 2019-08-15bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Personposter BETA

Tomasic, IvanPetrovic, NikolaLindén, Maria

Søk i DiVA

Av forfatter/redaktør
Tomasic, IvanPetrovic, NikolaLindén, Maria
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 49 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf