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. 2016 Jan;27(1):51-7.
doi: 10.1111/jce.12842. Epub 2015 Nov 13.

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

David D McMANUS  1   2   3 , Jo Woon Chong  3 , Apurv Soni  2 , Jane S Saczynski  1   2 , Nada Esa  1 , Craig Napolitano  1 , Chad E Darling  4 , Edward Boyer  4 , Rochelle K Rosen  5 , Kevin C Floyd  1 , Ki H Chon  6
Affiliations

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

David D McMANUS et al. J Cardiovasc Electrophysiol. 2016 Jan.

Abstract

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.

Keywords: atrial fibrillation; detection; premature beats; smartphone; technology.

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Figures

Figure 1
Figure 1
A prototype of the Pulse Waveform Analysis Application running on an iPhone 4S. From left to right: iPhone 4S camera; fingertip applied to iPhone 4S camera; a representative recording from a patient in atrial fibrillation; a representative recording from a patient in normal sinus rhythm.
Figure 2
Figure 2
A flowchart of the Pulse Waveform Analysis Algorithm
Figure 3
Figure 3
a): Comparison of ECG RR intervals to pulse intervals obtained from an iPhone; b): an example illustrating how a premature atrial contraction results in a longer duration pulse interval and larger amplitude pulse beat when compared to a normal pulse beat.(12)
Figure 4
Figure 4
Distribution of the nested (n=65) usability assessment for A) Perceived ease of use and B) Importance.
See this image and copyright information in PMC

Comment in

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