WORCESTER, MASSACHUSETTS. The gold standard for detecting atrial fibrillation (AF) is the
12-lead electrocardiogram (ECG). Whilst this is an excellent choice for AF diagnosis
in a hospital or clinical setting, it is not practical for afibbers who wish to determine
whether or not they are actually experiencing an episode at a particular point in time.
A team of electrophysiologists, engineers, and mathematicians associated with the
University of Massachusetts and Worcester Polytechnic Institute now propose that a
smartphone can be used to quickly and accurately determine whether an afibber is
in AF or in normal sinus rhythm (NSR). The user places their right index or second
finger on the smartphone camera for 2 minutes. Applications software built into the
phone uses some fairly complicated algorithms (root mean square of successive RR
differences and Shannon entropy) to analyse the pulse waves picked up by the camera
and then displays pulse rate and indicates whether one is in AF or NSR.
The team tested their idea on 76 persistent afibbers scheduled for cardioversion
using an iPhone 4S. The average age of the study participants was 65 years, 59% were male,
and 40% had either coronary artery disease or heart failure. Clinical characteristics
and algorithm means before and after cardioversion were as follows:
The algorithm combining RMSSD/mean and Shannon entropy was 100% accurate in diagnosing
irregular pulse and 96% accurate in diagnosing NSR. The researchers conclude that the
iPhone 4S equipped with the new app reliably distinguishes an irregular pulse (AF) from
pulse wave forms obtained during NSR.
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