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Temporal Phenotyping of Paroxysmal Atrial Fibrillation Reveals Prognostic Circadian Subtypes
This work represents a close collaboration between the following authors: Shany Brimer Biton, Jonathan Sobel, Anat Reiner Benaim, Eran Zvuloni, Ronit Almog, Julien Oster, Izhar Laufer, Ilan Green, Mahmoud Suleiman, Kenta Tsutsui, Leif Sörnmo, and Joachim A. Behar. URL: [] GitHub: The collaboration brings together expertise from the Faculty of Biomedical Engineering at the Technion (Israel); Geneva University Hospitals and the University of Geneva (Switzerland); Ben-Gurion Uni
Joachim Behar
Dec 24, 2025


uPVC-Net: A Universal Premature Ventricular Contraction Detection Deep Learning Algorithm
By Hagai Hamami, Yosef Solewicz, Daniel Zur, Yonatan Kleerekoper and Joachim A. Behar URL: https://arxiv.org/abs/2506.11238 Premature Ventricular Contractions (PVCs) are among the most common abnormal heartbeats, yet they are notoriously difficult to detect automatically. Their appearance shifts across patients, lead configurations, sensor types, and recording environments. This variability has long prevented PVC detection algorithms from reaching the level of robustness requ

Dr. Hagai Hamami
Dec 12, 2025


DUDE: Deep unsupervised domain adaptation using variable nEighborsfor physiological time series analysis
By Jeremy Levy, Noam Ben-Moshe, Uri Shalit, and Joachim A. Behar. Publication: https://iopscience.iop.org/article/10.1088/1361-6579/ae2231/meta Deep learning has changed the way we analyze physiological time-series such as ECG, SpO₂, and PPG signals. Modern neural networks routinely match and sometimes exceed expert performance in clinical tasks, from detecting atrial fibrillation to staging sleep. But there’s a catch: these models often break when moved from one patient popu

Joachim A. Behar
Dec 12, 2025


The challenge in finding a simple, accurate, reliable, and affordable tool for the objective assessment of excessive daytime sleepiness (EDS)
Oksenberg et al 2025 Physiol. Meas. https://doi.org/10.1088/1361-6579/ae2b4b Why Measuring Daytime Sleepiness Is So Hard and How Wearable Technology Could Help Excessive daytime sleepiness (EDS) is far more than feeling a little tired. It’s a physiological state that affects millions of people, impairing attention, slowing reaction time, and increasing the risk of accidents. For patients with sleep disorders like obstructive sleep apnea (OSA), EDS can be the most debilitating

Joachim A. Behar
Dec 11, 2025


Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers
By Márton Áron Goda, Helen Badge, Jasmeen Khan, Yosef Solewicz, Moran Davoodi, Rumbidzai Teramayi, Dennis Cordato, Longting Lin, Lauren Christie, Christopher Blair, Gagan Sharma, Mark Parsons and Joachim A Behar This study represents a joint collaboration between Pázmány Péter Catholic University’s Faculty of Information Technology and Bionics (Hungary), the Faculty of Biomedical Engineering at the Technion–Israel Institute of Technology (Israel), and the Ingham Institute for

Joachim A. Behar
Dec 10, 2025
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