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Smartphone app may enhance AF detection
An iPhone 4S application that incorporates a two-step algorithm can accurately distinguish pulse recordings during atrial fibrillation from sinus rhythm, research published in HeartRhythm indicates.
"A large percentage of older individuals have reported a willingness to use their mobile phones for health management," David D. McManus, MD, ScM FACC, FHRS, of the cardiac electrophysiology section, cardiovascular medicine division, department of medicine, University of Massachusetts Medical School in Worcester, and colleagues wrote in the paper. A smartphone-based application is an inexpensive instrument for pulse analysis and provides patients with AF with ready access, they added.
In a prospectively recruited cohort of 76 adults undergoing cardioversion for AF, the researchers obtained pulsatile time series recordings before and after cardioversion using the iPhone 4S camera. A smartphone application conducted real-time pulse analysis using two statistical methods: Root Mean Square of Successive RR Differences (RMSSD/mean) and Shannon Entropy (ShE). The researchers assessed sensitivity, specificity and predictive accuracy of both algorithms using the 12-lead ECG as the gold standard.
RMSDD/mean and ShE were higher when participants were in AF compared with sinus rhythm. The two methods were inversely related to AF in regression models adjusting for key factors such as heart rate and BP.
“An algorithm combining the two statistical methods demonstrated excellent sensitivity (0.962), specificity (0.975), and accuracy (0.968) for beat-to-beat discrimination of an irregular pulse during AF from sinus rhythm,” the researchers wrote.
"Since our application is accurate and real-time realizable using hardware that already exists within a standard smartphone, we believe that this software could be effectively an inexpensively used to improve AF detection in the general population."
Disclosure: McManus, Lee and Chon have ownership stake in DxMe. Chon has a patent on the algorithm. This work was funded in part by the office of Naval Research and NIH.