PULSE-SMART: Pulse-Based Arrhythmia Discrimination Using a Novel Smartphone Application

UMMS Affiliation

Department of Medicine, Division of Cardiovascular Medicine; Department of Quantitative Health Sciences; Department of Emergency Medicine; School of Medicine; Graduate School of Biomedical Sciences; MD/PhD Program

Publication Date


Document Type



Cardiology | Cardiovascular Diseases | Diagnosis | Health Information Technology | Medical Physiology | Translational Medical Research


BACKGROUND: Atrial fibrillation (AF) is a common and dangerous rhythm abnormality. Smartphones are increasingly used for mobile health applications by older patients at risk for AF and may be useful for AF screening.

OBJECTIVES: To test whether an enhanced smartphone app for AF detection can discriminate between sinus rhythm (SR), AF, premature atrial contractions (PACs), and premature ventricular contractions (PVCs).

METHODS: We analyzed two hundred and nineteen 2-minute pulse recordings from 121 participants with AF (n = 98), PACs (n = 15), or PVCs (n = 15) using an iPhone 4S. We obtained pulsatile time series recordings in 91 participants after successful cardioversion to sinus rhythm from preexisting AF. The PULSE-SMART app conducted pulse analysis using 3 methods (Root Mean Square of Successive RR Differences; Shannon Entropy; Poincare plot). We examined the sensitivity, specificity, and predictive accuracy of the app for AF, PAC, and PVC discrimination from sinus rhythm using the 12-lead EKG or 3-lead telemetry as the gold standard. We also administered a brief usability questionnaire to a subgroup (n = 65) of app users.

RESULTS: The smartphone-based app demonstrated excellent sensitivity (0.970), specificity (0.935), and accuracy (0.951) for real-time identification of an irregular pulse during AF. The app also showed good accuracy for PAC (0.955) and PVC discrimination (0.960). The vast majority of surveyed app users (83%) reported that it was "useful" and "not complex" to use.

CONCLUSION: A smartphone app can accurately discriminate pulse recordings during AF from sinus rhythm, PACs, and PVCs.


UMCCTS funding

DOI of Published Version



J Cardiovasc Electrophysiol. 2016 Jan;27(1):51-7. doi: 10.1111/jce.12842. Epub 2015 Nov 13. Link to article on publisher's site

Journal/Book/Conference Title

Journal of cardiovascular electrophysiology


Co-author Apurv Soni is a medical student in the MD/PhD Program at UMass Medical School.

Related Resources

Link to Article in PubMed

PubMed ID