Manifold Learning Approaches for Characterizing Photoplethysmographic Signals
Low dimensional representations provide a compact and task relevant encoding of PPG signals that enhances classification and detection performance in multiple scenarios. While interpretability gains remain task-dependent, these findings support the utility of embedding-based approaches in biomedical signal analysis and their robustness across modalities and noise conditions.
Authors
- José Luis Rojo‐Álvarez (ORCID: https://orcid.org/0000-0003-0426-8912)
- Francisco-Manuel Melgarejo-Meseguer (ORCID: https://orcid.org/0000-0001-6916-6082)
- Enrique Feito-Casares
- Alejandro Cobo (ORCID: https://orcid.org/0009-0007-7967-6837)
- Luis Baumela
Institutions
- Universidad Rey Juan Carlos (ES)
Publication Details
- Journal
- IEEE Transactions on Biomedical Engineering
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tbme.2025.3625858
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00