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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jun 28, 2018
Open Peer Review Period: Jul 3, 2018 - Aug 28, 2018
Date Accepted: Feb 17, 2019
(closed for review but you can still tweet)

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

Diagnostic Performance of a Smart Device With Photoplethysmography Technology for Atrial Fibrillation Detection: Pilot Study (Pre-mAFA II Registry)

Fan YY, Li YG, Li J, Wang H, Shi XM, Cheng WK, Shan ZL, Wang YT, Guo Y

Diagnostic Performance of a Smart Device With Photoplethysmography Technology for Atrial Fibrillation Detection: Pilot Study (Pre-mAFA II Registry)

JMIR Mhealth Uhealth 2019;7(3):e11437

DOI: 10.2196/11437

PMID: 30835243

PMCID: 6423467

Diagnostic performance of a smart device-based algorithm for atrial fibrillation detection: A pilot study of AF screening (Pre-mAFA II registry)

  • Yong-Yan Fan; 
  • Yan-Guang Li; 
  • Jian Li; 
  • Hao Wang; 
  • Xiang-Ming Shi; 
  • Wen-Kun Cheng; 
  • Zhao-Liang Shan; 
  • Yu-Tang Wang; 
  • Yutao Guo

ABSTRACT

Background:

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. The asymptomatic nature and paroxysmal frequency of AF lead to suboptimal early detection. A novel technology, photoplethysmography (PPG), has been developed for AF screening. However, there has been limited validation of smartphone and smart band applications with PPG compared to 12-lead electrocardiograms (ECG).

Objective:

We investigated the feasibility and accuracy of a smartphone- and smart band-based algorithm (PRO AF PPG) for AF detection using pulse data measured by PPG.

Methods:

One hundred twelve consecutive inpatients were recruited from the Chinese PLA General Hospital from 15 March to 1 April 2018. Participants were simultaneously tested with smartphones (HUAWEI Mate 9, HUAWEI Honor 7X), smart bands (HUAWEI Band 2), and 12-lead ECG for 3 minutes.

Results:

One hundred eight patients (56 with normal sinus rhythm, 52 with persistent AF) were enrolled in the final analysis after excluding 4 patients with unclear cardiac rhythms. The corresponding sensitivity and specificity of the smart band PPG were 95.36% (95% confidential interval, CI 92.00-97.40%) and 99.70% (95% CI 98.08-99.98%), respectively. The positive predictive value of the smart band PPG was 99.63% (95% CI 97.61-99.98%), the negative predictive value was 96.24% (95% CI 93.50-97.90%), and the accuracy was 97.72% (95% CI 96.11-98.70%). Moreover, the diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of smartphones with PPG for AF detection were over 94%. There was no significant difference after further statistical analysis of the results from the different smart devices compared with the gold-standard ECG (P=.999).

Conclusions:

The algorithm based on smartphones and smart bands with PPG demonstrated good performance in detecting AF and may represent a convenient tool for AF detection in at-risk individuals, allowing widespread screening of AF in the population. Clinical Trial: The present study was registered in the Chinese Clinical Trial Registry, International Clinical Trials Registry Platform of the World Health Organization (ChiCTR-OOC-17014138).


 Citation

Please cite as:

Fan YY, Li YG, Li J, Wang H, Shi XM, Cheng WK, Shan ZL, Wang YT, Guo Y

Diagnostic Performance of a Smart Device With Photoplethysmography Technology for Atrial Fibrillation Detection: Pilot Study (Pre-mAFA II Registry)

JMIR Mhealth Uhealth 2019;7(3):e11437

DOI: 10.2196/11437

PMID: 30835243

PMCID: 6423467

Per the author's request the PDF is not available.

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