ID: 4345715 PPG-BASED AF DETECTION WITH DEEP LEARNING FROM WEARABLE DEVICES: A SCALABLE MODEL FOR PASSIVE AF MONITORING
Wearable technology is reshaping how we detect atrial fibrillation (AF). Unlike ECG, which demands user engagement and active capture, photoplethysmography (PPG) offers a painless, continuous way to monitor heart rhythms with passive sensing.
Authors
- Cong Zhao (ORCID: https://orcid.org/0000-0002-1017-9118)
- Amitabh C. Pandey (ORCID: https://orcid.org/0000-0002-1541-7023)
- Yunsung Chung
- Fengling Han (ORCID: https://orcid.org/0000-0001-8756-7197)
- Hadi Younes (ORCID: https://orcid.org/0000-0002-7202-1164)
- Estelle Taki
- Omar Kreidieh (ORCID: https://orcid.org/0000-0001-6189-2821)
- Yingshuo Liu (ORCID: https://orcid.org/0000-0003-4780-8384)
- Ghassan Bidaoui (ORCID: https://orcid.org/0000-0002-3562-7386)
- Hongyu Miao (ORCID: https://orcid.org/0000-0002-4131-3164)
- Chanho Lim (ORCID: https://orcid.org/0000-0001-9998-5601)
- Michel Abou Khalil (ORCID: https://orcid.org/0009-0007-2038-7678)
- Mayana Bsoul
- Nassir Marrouche (ORCID: https://orcid.org/0000-0003-0970-9182)
- Mohammad Montaser Atasi (ORCID: https://orcid.org/0009-0008-2046-209X)
- Christian M. Massad (ORCID: https://orcid.org/0009-0002-3441-0617)
- Swati Rao (ORCID: https://orcid.org/0000-0001-8460-8408)
- Yishi Jia
- Abboud Hassan (ORCID: https://orcid.org/0009-0001-4263-9553)
Publication Details
- Journal
- Heart Rhythm O2
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1016/j.hroo.2025.07.101
- Primary Topic
- Anomaly Detection Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00