Contact‐Free Screening of Atrial Fibrillation by a Smartphone Using Facial Pulsatile Photoplethysmographic Signals

Contact‐Free Screening of Atrial Fibrillation by a Smartphone Using Facial Pulsatile Photoplethysmographic Signals

Background We aimed to evaluate a novel method of atrial fibrillation (AF) screening using an iPhone camera to detect and analyze photoplethysmographic signals from the face without physical contact by extracting subtle beat‐to‐beat variations of skin color that reflect the cardiac pulsatile signal....

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Bibliographic Details
Published in:Journal of the American Heart Association Vol. 7; no. 8
Main Authors: Yan, Bryan P., Lai, William H. S., Chan, Christy K. Y., Chan, Stephen Chun‐Hin, Chan, Lok‐Hei, Lam, Ka‐Ming, Lau, Ho‐Wang, Ng, Chak‐Ming, Tai, Lok‐Yin, Yip, Kin‐Wai, To, Olivia T. L., Freedman, Ben, Poh, Yukkee C., Poh, Ming‐Zher
Format: Journal Article
Language:English
Published: England John Wiley and Sons Inc 17-04-2018
Wiley
Subjects:
Aged
Algorithms
atrial fibrillation
Atrial Fibrillation - diagnosis
Atrial Fibrillation - physiopathology
Electrocardiography
Equipment Design
Face - physiopathology
Female
Heart Rate - physiology
Humans
Male
Mass Screening - methods
Mobile Applications
mobile apps
Original Research
photoplethysmography
Photoplethysmography - methods
Predictive Value of Tests
Reproducibility of Results
Retrospective Studies
screening
Smartphone
mobile apps
atrial fibrillation
screening
smartphone
photoplethysmography
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Summary:Background We aimed to evaluate a novel method of atrial fibrillation (AF) screening using an iPhone camera to detect and analyze photoplethysmographic signals from the face without physical contact by extracting subtle beat‐to‐beat variations of skin color that reflect the cardiac pulsatile signal. Methods and Results Patients admitted to the cardiology ward of the hospital for clinical reasons were recruited. Simultaneous facial and fingertip photoplethysmographic measurements were obtained from 217 hospital inpatients (mean age, 70.3±13.9 years; 71.4% men) facing the front camera and with an index finger covering the back camera of 2 independent iPhones before a 12‐lead ECG was recorded. Backdrop and background light intensity was monitored during signal acquisition. Three successive 20‐second (total, 60 seconds) recordings were acquired per patient and analyzed for heart rate regularity by Cardiio Rhythm (Cardiio Inc, Cambridge, MA) smartphone application. Pulse irregularity in ≥1 photoplethysmographic readings or 3 uninterpretable photoplethysmographic readings were considered a positive AF screening result. AF was present on 12‐lead ECG in 34.6% (n=75/217) patients. The Cardiio Rhythm facial photoplethysmographic application demonstrated high sensitivity (95%; 95% confidence interval, 87%–98%) and specificity (96%; 95% confidence interval, 91%–98%) in discriminating AF from sinus rhythm compared with 12‐lead ECG. The positive and negative predictive values were 92% (95% confidence interval, 84%–96%) and 97% (95% confidence interval, 93%–99%), respectively. Conclusions Detection of a facial photoplethysmographic signal to determine pulse irregularity attributable to AF is feasible. The Cardiio Rhythm smartphone application showed high sensitivity and specificity, with low negative likelihood ratio for AF from facial photoplethysmographic signals. The convenience of a contact‐free approach is attractive for community screening and has the potential to be useful for distant AF screening.
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Preliminary work related to this study (Abstract 17351; Circulation. 2016;134:A17351‐A) was presented at the American Heart Association Scientific Sessions, November 12 to 16, 2016, in New Orleans, LA.
ISSN:2047-9980
2047-9980
DOI:10.1161/JAHA.118.008585