Diagnostic Accuracy of a Novel Mobile Phone Application for the Detection and Monitoring of Atrial Fibrillation

Guy Rozen, Jeena Vaid, Seyed Mohammadreza Hosseini, M. Ihsan Kaadan, Allon Rafael, Attila Roka, Yukkee C. Poh, Ming Zher Poh, Edwin Kevin Heist, Jeremy Neil Ruskin

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in adults, associated with significant morbidity, increased mortality, and rising health-care costs. Simple and available tools for the accurate detection of arrhythmia recurrence in patients after electrical cardioversion (CV) or ablation procedures for AF can help to guide therapeutic decisions. We conducted a prospective, single-center study to evaluate the accuracy of Cardiio Rhythm Mobile Application (CRMA) for AF detection. Patients >18 years of age who were scheduled for elective CV for AF were enrolled in the study. CRMA finger pulse recordings, utilizing an iPhone camera, were obtained before (pre-CV) and after (post-CV) the CV. The findings were validated against surface electrocardiograms. Ninety-eight patients (75.5% men), mean age of 67.7 ± 10.5 years, were enrolled. No electrocardiogram for validation was available in 1 case. Pre-CV CRMA readings were analyzed in 97 of the 98 patients. Post-CV CRMA readings were analyzed for 92 of 93 patients who underwent CV. One patient left before the recording was obtained. The Cardiio Rhythm Mobile Application correctly identified 94 of 101 AF recordings (93.1%) as AF and 80 of 88 non-AF recordings (90.1%) as non-AF. The sensitivity was 93.1% (95% confidence interval [CI] = 86.9% to 97.2%) and the specificity was 90.9% (95% CI = 82.9% to 96.0%). The positive predictive value was 92.2% (95% CI = 85.8% to 95.8%) and the negative predictive value was 92.0% (95% CI = 94.8% to 95.9%). In conclusion, the CRMA demonstrates promising potential in accurate detection and discrimination of AF from normal sinus rhythm in patients with a history of AF.

Original languageEnglish (US)
Pages (from-to)1187-1191
Number of pages5
JournalAmerican Journal of Cardiology
Issue number10
StatePublished - May 15 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine


Dive into the research topics of 'Diagnostic Accuracy of a Novel Mobile Phone Application for the Detection and Monitoring of Atrial Fibrillation'. Together they form a unique fingerprint.

Cite this