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Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study.
JMIR Form Res
January 2025
Limburg Clinical Research Center/Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium.
Background: Consumer-oriented wearable devices (CWDs) such as smartphones and smartwatches have gained prominence for their ability to detect atrial fibrillation (AF) through proprietary algorithms using electrocardiography or photoplethysmography (PPG)-based digital recordings. Despite numerous individual validation studies, a direct comparison of interdevice performance is lacking.
Objective: This study aimed to evaluate and compare the ability of CWDs to distinguish between sinus rhythm and AF.
Comparison of 6-lead smartphone ECG and 12-lead ECG in athletes and a genetic heart disease population.
Expert Rev Med Devices
December 2024
Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Background: Smartphone electrocardiograms (iECGs) are an innovative method of capturing transient arrhythmias that are occasionally experienced by athletes. This study aimed to assess the accuracy of a 6-lead iECG compared with 12-lead ECG in athletes and those with known genetic heart disease (positive controls).
Research Design And Methods: Each participant had a resting 12-lead ECG (supine) and a 30 s 6-lead iECG (seated) taken within 2 h.
An Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images: PRESENT SHD.
medRxiv
December 2024
Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
Background: Identifying structural heart diseases (SHDs) early can change the course of the disease, but their diagnosis requires cardiac imaging, which is limited in accessibility.
Objective: To leverage images of 12-lead ECGs for automated detection and prediction of multiple SHDs using an ensemble deep learning approach.
Methods: We developed a series of convolutional neural network models for detecting a range of individual SHDs from images of ECGs with SHDs defined by transthoracic echocardiograms (TTEs) performed within 30 days of the ECG at the Yale New Haven Hospital (YNHH).
Diagnostic Accuracy of a Novel Wireless, Bluetooth-Enabled Simultaneous 12-Lead Portable ECG Device Compared with Standard ECG in Preoperative Patient Population.
Ann Card Anaesth
October 2024
Department of Cardiology, Seth Nandlal Dhoot Hospital, Aurangabad, Maharashtra, India.
Remote rhythm monitoring using a photoplethysmography smartphone application after cardioversion for atrial fibrillation.
Eur Heart J Digit Health
July 2024
Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, Thomas Drive, Liverpool L14 3PE, UK.
Article Synopsis
- Direct current cardioversion (DCCV) is a procedure used to treat atrial fibrillation, and a study compared follow-up methods between remote photoplethysmography (PPG) and traditional 12-lead electrocardiograms (ECG).
- The analysis involved 416 patients, showing high compliance rates for both methods, but PPG was more cost-effective, saving money and travel time for patients while also reducing carbon emissions.
- Ultimately, the study concluded that remote PPG monitoring is a practical alternative for post-DCCV arrhythmia follow-up, with no safety concerns reported.
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