Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin
A neural network trained on ground truth PPG data collected during EP studies could distinguish between supraventricular or ventricular origin from PPG waveforms alone.
Authors
- Martin Manninger (ORCID: https://orcid.org/0000-0002-0545-4373)
- Astrid N L Hermans (ORCID: https://orcid.org/0000-0002-9034-1479)
- Gernot Plank (ORCID: https://orcid.org/0000-0002-7380-6908)
- Sevasti‐Maria Chaldoupi (ORCID: https://orcid.org/0000-0003-3938-6193)
- Andreas Zirlik (ORCID: https://orcid.org/0000-0001-6290-3297)
- Thomas Pock (ORCID: https://orcid.org/0000-0001-6120-1058)
- Kevin Vernooy (ORCID: https://orcid.org/0000-0002-8818-5964)
- Douglas S. Scherr (ORCID: https://orcid.org/0000-0001-5868-5493)
- Jonas L. Isaksen (ORCID: https://orcid.org/0000-0003-3227-1131)
- Jørgen K. Kanters (ORCID: https://orcid.org/0000-0002-3267-4910)
- Dominik Linz (ORCID: https://orcid.org/0000-0003-4893-0824)
- Anton J. Prassl (ORCID: https://orcid.org/0000-0002-1920-1377)
- Rachel M.A. ter Bekke (ORCID: https://orcid.org/0000-0003-4278-0132)
- Justin Luermans (ORCID: https://orcid.org/0000-0001-9598-2286)
- Ingmar Lercher
Institutions
- University of Copenhagen (DK)
- Medical University of Graz (AT)
- Maastricht University Medical Centre (NL)
- Maastricht University (NL)
- Graz University of Technology (AT)
- University of San Francisco (US)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-04-20
- DOI
- https://doi.org/10.1016/j.cmpb.2025.108798
- Citations
- 1
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.67