QRS detection in single-lead, telehealth electrocardiogram signals: Benchmarking open-source algorithms
The Neurokit and University of New South Wales QRS detectors performed best in this study. These performed sufficiently well on high-quality telehealth ECGs, but not on low-quality ECGs. This demonstrates the need to handle low-quality ECGs appropriately to ensure only ECGs which can be accurately analysed are used for clinical decision making.
Authors
- Stephan Jonas (ORCID: https://orcid.org/0000-0002-3687-6165)
- Kate Williams (ORCID: https://orcid.org/0000-0002-6188-9363)
- Florian Kristof
- Gregory Y.H. Lip (ORCID: https://orcid.org/0000-0002-7566-1626)
- Jonathan Mant (ORCID: https://orcid.org/0000-0002-9531-0268)
- Maximilian Kapsecker (ORCID: https://orcid.org/0000-0002-3907-0749)
- Hannah Clair Lindén
- Peter Charlton (ORCID: https://orcid.org/0000-0003-3836-8655)
- Andrew Dymond
- James Brimicombe (ORCID: https://orcid.org/0000-0002-3443-3256)
- Martín Cowie (ORCID: https://orcid.org/0000-0001-7457-2552)
- Zixuan Ding (ORCID: https://orcid.org/0009-0002-2337-3398)
- Leon Nissen (ORCID: https://orcid.org/0009-0009-3884-0850)
Institutions
- University of Liverpool (GB)
- King's College London (GB)
- University of Cambridge (GB)
- University Hospital Bonn (DE)
- Liverpool Heart and Chest Hospital (GB)
- Zenicor Medical Systems (Sweden) (SE)
- Technical University of Munich (DE)
- Liverpool John Moores University (GB)
- Aalborg University (DK)
Publication Details
- Journal
- PLOS Digital Health
- Published
- 2024-08-13
- DOI
- https://doi.org/10.1371/journal.pdig.0000538
- Citations
- 9
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 3.62
Funders
- AstraZeneca
- National Institute for Health and Care Research
- British Heart Foundation
- Medical Research Council
- Programme Grants for Applied Research
- NIHR School for Primary Care Research