Continuous heart rate measurements in patients with cardiac disease: Device comparison and development of a novel artefact removal procedure
While ECG-based monitors provide HR data with clinical acceptable accuracy, PPG-based monitors present accuracy challenges. Our machine learning procedure showed potential to filter unreliable PPG-based HR data, which could help measure physical activity intensity in cardiac disease continuously.
Authors
- Hein Heidbüchel (ORCID: https://orcid.org/0000-0001-9301-8127)
- Kris Laukens (ORCID: https://orcid.org/0000-0002-8217-2564)
- Emeline M. Van Craenenbroeck (ORCID: https://orcid.org/0000-0001-7686-2668)
- L Knaepen (ORCID: https://orcid.org/0000-0003-2816-1896)
- S Naessens
- P Vermunicht (ORCID: https://orcid.org/0000-0001-5922-2095)
- Wendy Hens (ORCID: https://orcid.org/0000-0002-9881-6248)
- Juan Sebastian Piedrahita Giraldo (ORCID: https://orcid.org/0000-0002-1691-2915)
- Lien Desteghe (ORCID: https://orcid.org/0000-0001-8641-4658)
- K Makayed
- Christophe Buyck (ORCID: https://orcid.org/0009-0005-4214-9932)
Institutions
- University of Antwerp (BE)
- Jessa Hospital (BE)
- Antwerp University Hospital (BE)
- Biomedical Informatics Research Center Antwerp (BE)
- Hasselt University (BE)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251337598
- Citations
- 2
- Primary Topic
- Heart Rate Variability and Autonomic Control
- Type
- article
- Field-Weighted Citation Impact
- 2.78
Funders
- Fonds Wetenschappelijk Onderzoek