3 papers
eess.SP2026
Effect of Photoplethysmogram Artifacts on Uncertainty in Atrial Fibrillation Detection
Andrius Sološenko, Enikö Vargova, Loïc Coquelin +2
Detection of atrial fibrillation (AF) from photoplethysmogram (PPG) is highly sensitive to artifacts, yet their effect on uncertainty of different AF detectors remains poorly under…
cs.LG2026
Benchmark Problems and Benchmark Datasets for the evaluation of Machine and Deep Learning methods on Photoplethysmography signals: the D4 report from the QUMPHY project
Urs Hackstein, Jordi Alastruey, Philip Aston +13
This report is part of the Qumphy project (22HLT01 Qumphy) that is funded by the European Union and is dedicated to the development of measures to quantify the uncertainties associ…
cs.LG2026
Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches
Mohammad Moulaeifard, Loic Coquelin, Mantas RinkeviÄius +13
Photoplethysmography (PPG) is a widely used non-invasive physiological sensing technique, suitable for various clinical applications. Such clinical applications are increasingly su…