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Accepted for/Published in: JMIR Formative Research

Date Submitted: Feb 14, 2022
Open Peer Review Period: Feb 14, 2022 - Feb 22, 2022
Date Accepted: Apr 28, 2022
Date Submitted to PubMed: Apr 28, 2022
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Atrial Fibrillation Detection With an Analog Smartwatch: Prospective Clinical Study and Algorithm Validation

Campo D, Elie V, de Gallard T, Bartet P, Morichau-Beauchant T, Genain N, Fayol A, Fouassier D, Pasteur-Rousseau A, Puymirat E, Nahum J

Atrial Fibrillation Detection With an Analog Smartwatch: Prospective Clinical Study and Algorithm Validation

JMIR Form Res 2022;6(11):e37280

DOI: 10.2196/37280

PMID: 35481559

PMCID: 9675016

Validation of an algorithm for atrial fibrillation detection with an analog smartwatch: prospective interventional clinical study

  • David Campo; 
  • Valery Elie; 
  • Tristan de Gallard; 
  • Pierre Bartet; 
  • Tristan Morichau-Beauchant; 
  • Nicolas Genain; 
  • Antoine Fayol; 
  • David Fouassier; 
  • Adrien Pasteur-Rousseau; 
  • Etienne Puymirat; 
  • Julien Nahum

ABSTRACT

Background:

Atrial Fibrillation (AF) affects one to 4% of the World’s population and is one of the major causes of stroke, heart failure, sudden death, and cardiovascular morbidity. It can be difficult to diagnose when asymptomatic or in the paroxysmal stage, and its natural history is not well understood. New wearables and connected devices offer an opportunity to improve on this situation.

Objective:

To validate an algorithm for the automatic detection of AF from a single-lead electrocardiogram (ECG) taken with an analog watch.

Methods:

Eligible patients were recruited from 4 sites in Paris and its suburb area. Simultaneous 1-lead ECG captured by Withings smartwatch with embedded algorithm were recorded with 12-lead reference ECG. Automatic AF detection performance and algorithm-generated 1-lead ECG quality (visibility, polarity, interval durations, heart rate) were assessed. Sensitivity and specificity of the algorithm to detect AF and to discriminate if from normal sinus rhythm (NSR) were calculated.

Results:

Two hundred and sixty two patients were included in the final analysis: 100 AF, 113 NSR, 45 Other arrhythmia, 4 presented unreadable ECGs. Mean age was of 74.3 years ± 12.3 in the AF group versus 61.8 years old ± 14.3 and 66.9 years old ± 15.2 in the NSR and other arrhythmia groups respectively. 6.9% (18/262) were classified as “Noise” by the algorithm. Excluding “Other” arrhythmia and “Noise”, the sensitivity to detect AF was of SeAF/NSR = 0.963 (0.894), and specificity of SpAF/NSR = 1.000 (0.967). Visibility and polarity accuracies (1-lead ECG vs 12-lead ECG) were of: P-waves: 96.9%/100%, QRS-complexes: 99.2%/98.8%, and T-waves: 91.2%/99.5% respectively. P-wave visibility accuracy was of 99% (99/100) in AF patients and of 95.7% (155/162) when excluding AF patients. Except for QT, mean difference absolute values for difference in PR duration and QRS width were below 3ms and more than 97% of these differences were below 40ms. Difference between HR calculated by the algorithm and device 1-lead ECG read by cardiologists being of 0.55 bpm ± 6.46.

Conclusions:

Withings algorithm demonstrated great diagnostic performance for AF detection. 1-lead generated ECG also demonstrated good quality for physician use in daily routine care. Clinical Trial: ClinicalTrials.gov registration number: NCT04351386


 Citation

Please cite as:

Campo D, Elie V, de Gallard T, Bartet P, Morichau-Beauchant T, Genain N, Fayol A, Fouassier D, Pasteur-Rousseau A, Puymirat E, Nahum J

Atrial Fibrillation Detection With an Analog Smartwatch: Prospective Clinical Study and Algorithm Validation

JMIR Form Res 2022;6(11):e37280

DOI: 10.2196/37280

PMID: 35481559

PMCID: 9675016

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