Reducing the burden of inconclusive smart device single-lead ECG tracings via a novel artificial intelligence algorithm.

ABSTRACT:

Background

Multiple smart devices capable of automatically detecting atrial fibrillation (AF) based on single-lead electrocardiograms (SL-ECG) are presently available. The rate of inconclusive tracings by manufacturers' algorithms is currently too high to be clinically useful.

Method

This is a prospective, observational study enrolling patients presenting to a cardiology service at a tertiary referral center. We assessed the clinical value of applying a smart device artificial intelligence (AI)-based algorithm for detecting AF from 4 commercially available smart devices (AliveCor KardiaMobile, Apple Watch 6, Fitbit Sense, and Samsung Galaxy Watch3). Patients underwent a nearly simultaneous 12-lead ECG and 4 smart device SL-ECGs. The novel AI algorithm (PulseAI, Belfast, Unit

SUBMITTER: Weidlich S 

PROVIDER: S-EPMC10879015 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature