Current Advancement in Diagnosing Atrial Fibrillation by Utilizing Wearable Devices and Artificial Intelligence: A Review Study

Overview

Journal Diagnostics (Basel)

Specialty Radiology

Date 2022 Mar 25

PMID 35328243

Authors

Yu-Chiang Wang

Xiaobo Xu

Adrija Hajra

Samuel Apple

Amrin Kharawala

Gustavo Duarte

Wasla Liaqat

Yiwen Fu

Weijia Li

Yiyun Chen

Robert T Faillace

Affiliations

Soon will be listed here.

Abstract

Atrial fibrillation (AF) is a common arrhythmia affecting 8-10% of the population older than 80 years old. The importance of early diagnosis of atrial fibrillation has been broadly recognized since arrhythmias significantly increase the risk of stroke, heart failure and tachycardia-induced cardiomyopathy with reduced cardiac function. However, the prevalence of atrial fibrillation is often underestimated due to the high frequency of clinically silent atrial fibrillation as well as paroxysmal atrial fibrillation, both of which are hard to catch by routine physical examination or 12-lead electrocardiogram (ECG). The development of wearable devices has provided a reliable way for healthcare providers to uncover undiagnosed atrial fibrillation in the population, especially those most at risk. Furthermore, with the advancement of artificial intelligence and machine learning, the technology is now able to utilize the database in assisting detection of arrhythmias from the data collected by the devices. In this review study, we compare the different wearable devices available on the market and review the current advancement in artificial intelligence in diagnosing atrial fibrillation. We believe that with the aid of the progressive development of technologies, the diagnosis of atrial fibrillation shall be made more effectively and accurately in the near future.

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