Performance of a medical smartband with photoplethysmography technology and artificial intelligence algorithm to detect atrial fibrillation.

ABSTRACT:

Background

Atrial fibrillation (AF) is a prevalent arrhythmia with significant public health implications, including increased risk of stroke and mortality. Early detection is challenging but crucial for managing complications. Wearable technology with photoplethysmography (PPG) offers a potential solution for long-term, non-invasive monitoring. This study aims to evaluate the performance of three artificial intelligence (AI) algorithms (Happitech, Preventicus, and Philips Biosensing AF) in detecting AF using PPG signals from a medical smartband and compare it with the gold standard electrocardiogram (ECG).

Methods

A medical smartband equipped with PPG technology was used to collect cardiovascular data from patients with and without AF. The sensitivity and specificity of the

SUBMITTER: Blok S 

PROVIDER: S-EPMC11811644 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature