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Dataset Information

Smart detection of atrial fibrillation†.


ABSTRACT:

Aims

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, and its paroxysmal nature makes its detection challenging. In this trial, we evaluated a novel App for its accuracy to differentiate between patients in AF and patients in sinus rhythm (SR) using the plethysmographic sensor of an iPhone 4S and the integrated LED only.

Methods and results

For signal acquisition, we used an iPhone 4S, positioned with the camera lens and LED light on the index fingertip. A 5 min video file was recorded with the pulse wave extracted from the green light spectrum of the signal. RR intervals were automatically identified. For discrimination between AF and SR, we tested three different statistical methods. Normalized root mean square of successive differen

SUBMITTER: Krivoshei L 

PROVIDER: S-EPMC5437701 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature