Work

Id: 4345715 Ppg-based Af Detection With Deep Learning From Wearable Devices: a Scalable Model for Passive Af Monitoring

Year: 2025

Type: article

Abstract: 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.

Source: Heart Rhythm O2

DOI: 10.1016/j.hroo.2025.07.101

Authors: Yingshuo Liu, Chanho Lim, Estelle Taki, Michel Abou Khalil, Christian M. Massad, Yishi Jia, Abboud Hassan, Cong Zhao, Hadi Younes, Ghassan Bidaoui, Mayana Bsoul, Mohammad Montaser Atasi, Yunsung Chung, Hongyu Miao, Amitabh C. Pandey, Swati Rao, Omar Kreidieh, Han Feng, Nassir F. Marrouche

Language: English

Topic: Non-Invasive Vital Sign Monitoring

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,150

OpenAlex ID: W4413963525

FWCI:

Cites:

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