Six-lead device superior to single-lead smartwatch ECG in atrial fibrillation detection

2025 Japanese Heart Rhythm Society / Japanese Circulation Society Consensus Statement on the Appropriate Use of Ambulatory and Wearable Electrocardiographs

Recently, some clinicians have been diagnosing and treating arrhythmias on the basis of electrocardiogram (ECG) devices with low accuracy. In Europe and the US, several statements on the use of ECGs have already been published by related academic societies. In addition, with the relaxation of regulations on media advertising ambulatory/wearable ECG devices, the frequency of use of simple ECG devices by the general public will increase in the future. Therefore, this statement describes the functions and features of non-invasive ambulatory or wearable ECG devices that have been approved as medical devices in Japan (and that can record ECGs remotely), as well as points to note when using them; provides an overview of data storage and security for ambulatory/wearable ECG devices and implantable loop recorders (ILRs), as well as discussing differences between their use and the use of non-invasive ambulatory/wearable ECG devices; and provides classes of recommendation for the use of these devices and their evaluation for each arrhythmia type or condition. We describe lead-based ambulatory ECG devices (classical 24-h Holter ECG monitoring), handheld ECG devices, handheld-based ECG devices using a smartphone, wearable ECG devices (smartwatch and garment ECG devices), and patch ECG devices. In addition, we provide information on methods that are not based on the original ECG, such as photoplethysmography and oscillometric blood pressure measurement, and describe the limitations of their use. We hope that the publication of this statement will lead to the appropriate use of ambulatory/wearable ECG devices in Japan.

Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta-analysis

Background

The prevalence of atrial fibrillation (AFib) continues to increase globally, posing a significant risk for serious cardiovascular complications, such as ischemic stroke and thromboembolism. Smartwatch single-lead electrocardiogram (ECG) can be a practical and accurate early detection tool for AFib.

Objective

The aim of this study was to fill the research gap in evaluating the accuracy and interpretability of smartwatch ECG for early AFib detection.

Methods

Data derived from indexed literature in the Scopus, Scilit, PubMed, Google Scholar, Web of Science, IEEE, and Cochrane Library databases (as of June 1, 2024) were systematically screened and extracted. The quantitative synthesis was performed using a two-level mixed-effects logistic regression model, as well as a proportional analysis with Freeman-Tukey double transformation on a restricted maximum-likelihood model.

Results

The sensitivity and specificity of smartwatch ECG in algorithmic readings were 86% and 94%, respectively. In manual readings, the sensitivity and specificity reached 96% and 95%, respectively. In a brand-specific subgroup analysis, the algorithmic reading reached a summary area under the curve (sAUC) of 96%, while another brand achieved the highest sAUC of 98% in manual reading. The level of manual interpretability was relatively high with Cohen's Kappa of 0.83, but 3% of ECG results were difficult to read manually.

Conclusion

This study shows that smartwatch ECG is able to detect AFib with high accuracy, especially through manual reading by trained medical personnel.

PROSPERO Registration

CRD42024548537 (May 29, 2024).

Home detection of atrial fibrillation using cardiac activity analysis: technologies available to the patient

INTRODUCTION

Atrial fibrillation (AF) is the most common cardiac arrhythmia, whose incidence and prevalence have increased over the last 20 years and will continue to increase over the next 30 years. It is characterized by irregular atrial activation, leading to complications as stroke and heart failure. Due to its intermittent and asymptomatic nature, diagnosing and monitoring AF is challenging but crucial for effective treatment and prevention of serious complications.

AREAS COVERED

This study reviews noninvasive medical devices available for home detection of AF by analyzing cardiac activity through ECG or photoplethysmography (PPG). The review covers the technologies underlying single-lead ECG acquisition and PPG sensors, and describes how these are used, also in combination, in home-use medical devices (including smartwatches and wristbands).

EXPERT OPINION

Single-lead ECG and PPG technologies in consumer electronics have revolutionized AF detection, making it more accessible and convenient for patients. Despite some limitations in signal quality and diagnostic scope, these devices offer significant benefits for early AF detection and management. The use of wearable devices, including smartwatches and wristbands, for heart activity monitoring represents a promising advancement in patient-lead healthcare, potentially leading to better outcomes through timely medical intervention and improved patient engagement in managing their condition.

2025 Japanese Heart Rhythm Society / Japanese Circulation Society Consensus Statement on the Appropriate Use of Ambulatory and Wearable Electrocardiographs

Recently, some clinicians have been diagnosing and treating arrhythmias on the basis of electrocardiogram (ECG) devices with low accuracy. In Europe and the US, several statements on the use of ECGs have already been published by related academic societies. In addition, with the relaxation of regulations on media advertising ambulatory/wearable ECG devices, the frequency of use of simple ECG devices by the general public will increase in the future. Therefore, this statement describes the functions and features of non-invasive ambulatory or wearable ECG devices that have been approved as medical devices in Japan (and that can record ECGs remotely), as well as points to note when using them; provides an overview of data storage and security for ambulatory/wearable ECG devices and implantable loop recorders (ILRs), as well as discussing differences between their use and the use of non-invasive ambulatory/wearable ECG devices; and provides classes of recommendation for the use of these devices and their evaluation for each arrhythmia type or condition. We describe lead-based ambulatory ECG devices (classical 24-h Holter ECG monitoring), handheld ECG devices, handheld-based ECG devices using a smartphone, wearable ECG devices (smartwatch and garment ECG devices), and patch ECG devices. In addition, we provide information on methods that are not based on the original ECG, such as photoplethysmography and oscillometric blood pressure measurement, and describe the limitations of their use. We hope that the publication of this statement will lead to the appropriate use of ambulatory/wearable ECG devices in Japan.

Diagnostic Accuracy of Apple Watch Electrocardiogram for Atrial Fibrillation: A Systematic Review and Meta-Analysis

Background

Electrocardiography (ECG) is the gold standard for the diagnosis of atrial fibrillation (AF). Recently, smartwatches like the Apple Watch have emerged as a promising, user-friendly device for rapid detection and diagnosis of AF, but the reliability and diagnostic accuracy still remain controversial.

Objectives

The purpose of this study was to perform a systematic review and diagnostic test accuracy meta-analysis evaluating the diagnostic performance of the Apple Watch ECG in detecting AF.

Methods

The literature search was conducted on PubMed, Embase, and Cochrane Library through April 2024 for studies comparing the diagnostic accuracy of Apple Watch to standard 12-lead ECG. Statistical analysis was performed using R Software version 4.4.0 and OpenMeta[Analyst]. Pooled analyses of sensitivity, specificity, and area under the receiver operating characteristic curve were determined along with their 95% CIs. The quality of studies was analyzed using the QUADAS-2 tool.

Results

The meta-analysis included 11 studies comprising 4,241 participants. Their mean age was 62.56 ± 3.92 years, and 28% of the patients were females. The pooled sensitivity and specificity of the Apple Watch for detecting AF were 94.8% (95% CI: 91.7% to 96.8%; I2 = 67%) and 95% (95% CI: 88.6% to 97.8%; I2 = 88%), respectively. The area under the receiver operating characteristic curve was 0.96 (95% CI: 0.92-0.97).

Conclusions

The Apple Watch ECG carries high accuracy in detecting atrial fibrillation, providing a convenient diagnostic option for patients.

Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study

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.

Methods

Patients exhibiting sinus rhythm or AF were enrolled through a cardiology outpatient clinic. The participants were instructed to perform heart rhythm measurements using a handheld 6-lead electrocardiogram (ECG) device (KardiaMobile 6L), a smartwatch-derived single-lead ECG (Apple Watch), and two PPG-based smartphone apps (FibriCheck and Preventicus) in a random sequence, with simultaneous 12-lead reference ECG as the gold standard.

Results

A total of 122 participants were included in the study: median age 69 (IQR 61-77) years, 63.9% (n=78) men, 25% (n=30) with AF, 9.8% (n=12) without prior smartphone experience, and 73% (n=89) without experience in using a smartwatch. The sensitivity to detect AF was 100% for all devices. The specificity to detect sinus rhythm was 96.4% (95% CI 89.5%-98.8%) for KardiaMobile 6L, 97.8% (95% CI 91.6%-99.5%) for Apple Watch, 98.9% (95% CI 92.5%-99.8%) for FibriCheck, and 97.8% (95% CI 91.5%-99.4%) for Preventicus (P=.50). Insufficient quality measurements were observed in 10.7% (95% CI 6.3%-17.5%) of cases for both KardiaMobile 6L and Apple Watch, 7.4% (95% CI 3.9%-13.6%) for FibriCheck, and 14.8% (95% CI 9.5%-22.2%) for Preventicus (P=.21). Participants preferred Apple Watch over the other devices to monitor their heart rhythm.

Conclusions

In this study population, the discrimination between sinus rhythm and AF using CWDs based on ECG or PPG was highly accurate, with no significant variations in performance across the examined devices.

Accuracy of Artificial Intelligence-Based Technologies for the Diagnosis of Atrial Fibrillation: A Systematic Review and Meta-Analysis

Atrial fibrillation (AF) is the most common arrhythmia with a high burden of morbidity including impaired quality of life and increased risk of thromboembolism. Early detection and management of AF could prevent thromboembolic events. Artificial intelligence (AI)--based methods in healthcare are developing quickly and can be proved as valuable for the detection of atrial fibrillation. In this metanalysis, we aim to review the diagnostic accuracy of AI-based methods for the diagnosis of atrial fibrillation. A predetermined search strategy was applied on four databases, the PubMed on 31 August 2022, the Google Scholar and Cochrane Library on 3 September 2022, and the Embase on 15 October 2022. The identified studies were screened by two independent investigators. Studies assessing the diagnostic accuracy of AI-based devices for the detection of AF in adults against a gold standard were selected. Qualitative and quantitative synthesis to calculate the pooled sensitivity and specificity was performed, and the QUADAS-2 tool was used for the risk of bias and applicability assessment. We screened 14,770 studies, from which 31 were eligible and included. All were diagnostic accuracy studies with case-control or cohort design. The main technologies used were: (a) photoplethysmography (PPG) with pooled sensitivity 95.1% and specificity 96.2%, and (b) single-lead ECG with pooled sensitivity 92.3% and specificity 96.2%. In the PPG group, 0% to 43.2% of the tracings could not be classified using the AI algorithm as AF or not, and in the single-lead ECG group, this figure fluctuated between 0% and 38%. Our analysis showed that AI-based methods for the diagnosis of atrial fibrillation have high sensitivity and specificity for the detection of AF. Further studies should examine whether utilization of these methods could improve clinical outcomes.

Electrocardiogram Devices for Home Use: Technological and Clinical Scoping Review

BACKGROUND

Electrocardiograms (ECGs) are used by physicians to record, monitor, and diagnose the electrical activity of the heart. Recent technological advances have allowed ECG devices to move out of the clinic and into the home environment. There is a great variety of mobile ECG devices with the capabilities to be used in home environments.

OBJECTIVE

This scoping review aimed to provide a comprehensive overview of the current landscape of mobile ECG devices, including the technology used, intended clinical use, and available clinical evidence.

METHODS

We conducted a scoping review to identify studies concerning mobile ECG devices in the electronic database PubMed. Secondarily, an internet search was performed to identify other ECG devices available in the market. We summarized the devices' technical information and usability characteristics based on manufacturer data such as datasheets and user manuals. For each device, we searched for clinical evidence on the capabilities to record heart disorders by performing individual searches in PubMed and ClinicalTrials.gov, as well as the Food and Drug Administration (FDA) 510(k) Premarket Notification and De Novo databases.

RESULTS

From the PubMed database and internet search, we identified 58 ECG devices with available manufacturer information. Technical characteristics such as shape, number of electrodes, and signal processing influence the capabilities of the devices to record cardiac disorders. Of the 58 devices, only 26 (45%) had clinical evidence available regarding their ability to detect heart disorders such as rhythm disorders, more specifically atrial fibrillation.

CONCLUSIONS

ECG devices available in the market are mainly intended to be used for the detection of arrhythmias. No devices are intended to be used for the detection of other cardiac disorders. Technical and design characteristics influence the intended use of the devices and use environments. For mobile ECG devices to be intended to detect other cardiac disorders, challenges regarding signal processing and sensor characteristics should be solved to increase their detection capabilities. Devices recently released include the use of other sensors on ECG devices to increase their detection capabilities.

Six-lead electrocardiography compared to single-lead electrocardiography and photoplethysmography of a wrist-worn device for atrial fibrillation detection controlled by premature atrial or ventricular contractions: six is smarter than one

Background

Smartwatches are commonly capable to record a lead-I-like electrocardiogram (ECG) and perform a photoplethysmography (PPG)-based atrial fibrillation (AF) detection. Wearable technologies repeatedly face the challenge of frequent premature beats, particularly in target populations for screening of AF.

Objective

To investigate the potential diagnostic benefit of six-lead ECG compared to single-lead ECG and PPG-based algorithm for AF detection of the wrist-worn device.

Methods and results

From the database of DoubleCheck-AF 249 adults were enrolled in AF group (n = 121) or control group of SR with frequent premature ventricular (PVCs) or atrial (PACs) contractions (n = 128). Cardiac rhythm was monitored using a wrist-worn device capable of recording continuous PPG and simultaneous intermittent six-lead standard-limb-like ECG. To display a single-lead ECG, the six-lead ECGs were trimmed to lead-I-like ECGs. Two diagnosis-blinded cardiologists evaluated reference, six-lead and single-lead ECGs as "AF", "SR", or "Cannot be concluded". AF detection based on six-lead ECG, single-lead ECG, and PPG yielded a sensitivity of 99.2%, 95.7%, and 94.2%, respectively. The higher number of premature beats per minute was associated with false positive outcomes of single-lead ECG (18.80 vs. 5.40 beats/min, P < 0.01), six-lead ECG (64.3 vs. 5.8 beats/min, P = 0.018), and PPG-based detector (13.20 vs. 5.60 beats/min, P = 0.05). Single-lead ECG required 3.4 times fewer extrasystoles than six-lead ECG to result in a false positive outcome. In a control subgroup of PACs, the specificity of six-lead ECG, single-lead ECG, and PPG dropped to 95%, 83.8%, and 90%, respectively. The diagnostic value of single-lead ECG (AUC 0.898) was inferior to six-lead ECG (AUC 0.971) and PPG-based detector (AUC 0.921). In a control subgroup of PVCs, the specificity of six-lead ECG, single-lead ECG, and PPG was 100%, 96.4%, and 96.6%, respectively. The diagnostic value of single-lead ECG (AUC 0.961) was inferior to six-lead ECG (AUC 0.996) and non-inferior to PPG-based detector (AUC 0.954).

Conclusions

A six-lead wearable-recorded ECG demonstrated the superior diagnostic value of AF detection compared to a single-lead ECG and PPG-based AF detection. The risk of type I error due to the widespread use of smartwatch-enabled single-lead ECGs in populations with frequent premature beats is significant.