Cited by 94Non-Invasive Vital Sign MonitoringECG Monitoring and AnalysisEmotion and Mood Recognition

High-Throughput, Contact-Free Detection of Atrial Fibrillation From Video With Deep Learning

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Yan, Bryan P., Lai, William H. S., Chan, Christy K. Y., Au, Alex C. K., Freedman, Ben, Poh, Yukkee C., Poh, Ming-Zher·2020·JAMA Cardiology

Abstract

A, Example video recording of 5 patients arranged in 1 of the 32 different heart rhythm permutations with extracted facial photoplethysmographic (FPPG) signals and reference electrocardiogram (ECG) traces.B, The 5-participant binary (atrial fibrillation [AF]/sinus rhythm [SR]) matrix.

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Crossref · 10.1001/jamacardio.2019.4004

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References 4 · Cited by 94

Authors
Yan, B. P., Lai, W. H. S., Chan, C. K. Y., Au, A. C. K., Freedman, B., Poh, Y. C., & Poh, M.-Z.
Affiliations
  • Chinese University of Hong Kong (HK)
  • Prince of Wales Hospital (CN)
  • The University of Sydney (AU)
  • Cardiio Inc, Cambridge, Massachusetts
Corresponding author
Yan, Bryan P.
Venue
JAMA Cardiology
Published
2020-01-01
Volume
5
Issue
1
Pages
105
ISSN
2380-6583 (ISSN-L)
OpenAlex
W2991446963
Cited by
94
References
4
Citations by year
2026: 2 · 2025: 13 · 2024: 13 · 2023: 12 · 2022: 15 · 2021: 25 · 2020: 12 · 2019: 2
FWCI
4.75
Type
journal article
Language
en
Open access
Locations
  • JAMA Cardiology (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
Keywords
atrial fibrillation, photoplethysmography, non-contact vital sign monitoring, deep learning, high-throughput detection, electrocardiogram comparison, sinus rhythm
MeSH terms
Proof of Concept Study, Deep Learning, Adult, Aged, Aged, 80 and over, Atrial Fibrillation, Electrocardiography, Face, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Video Recording, Reproducibility of Results, Case-Control Studies, Neural Networks, Computer, Photoplethysmography

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