Wearable Arrhythmia Detection: Moving from your Watch to your Shirt?

Q: What is the clinical evidence from this study?

Study design: Review. Population: Atrial fibrillation and other cardiac arrhythmias. Intervention: Wearable arrhythmia detection devices (smartwatches and smart garments) vs. Conventional ECG monitoring (12-lead ECG, Holter monitoring, or standard care).

Q: What does this research mean for the field?

Single-lead ECG wearables such as smartwatches provide robust evidence for atrial fibrillation screening, while emerging smart garments offer potential for continuous multi-channel monitoring despite current limitations from motion artifacts. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

Janna-Luisa Beermann; David Duncker

doi:10.1007/s11886-026-02445-6

November 3, 2026Current Cardiology ReportsOpen Access

Wearable Arrhythmia Detection: Moving from your Watch to your Shirt?

View Full Paper

Ask AI

Bookmark

Share

Why the study?

Digital devices play an increasingly important role in arrhythmia detection, and this review summarizes the current evidence on wearable devices for screening and diagnosing AF, which is associated with increased risks of stroke, heart failure, and mortality.

Do wearable digital devices (such as smartwatches and smart garments) improve the screening, detection, and management of atrial fibrillation and other cardiac arrhythmias compared to conventional monitoring?

Key Points

Summarize current evidence on wearable digital devices, including smartwatches and smart garments, for screening and diagnosing atrial fibrillation.
Narrative review synthesizing clinical evidence on wearable cardiac rhythm monitoring technologies, including photoplethysmography, single-lead electrocardiography, and textile-integrated sensor garments.
Evaluated clinical data on diagnostic accuracy, patient adherence, artificial intelligence integration, and wearable-guided arrhythmia detection workflows.
Single-lead ECG devices demonstrate the strongest diagnostic evidence for atrial fibrillation, with 6-month smartwatch monitoring in the randomized EQUAL trial increasing detection of undiagnosed atrial fibrillation compared with standard care (9.6% vs. 2.3%).
Smart garments enable continuous multi-channel electrocardiographic monitoring with diagnostic accuracy comparable to Holter monitors during rest, though motion artefacts degrade signal quality during intense physical activity.
Artificial intelligence algorithms improve automated signal analysis, motion artefact suppression, and differentiation of complex tachyarrhythmias, while definitive clinical diagnosis still requires physician confirmation.

Structured PICO

Do wearable digital devices (such as smartwatches and smart garments) improve the screening, detection, and management of atrial fibrillation and other cardiac arrhythmias compared to conventional monitoring?

P

Population

Patients being screened or monitored for cardiac arrhythmias, particularly atrial fibrillation (AF), including asymptomatic and paroxysmal AF, older individuals at elevated stroke risk, pediatric patients with heart conditions, and patients following catheter ablation or electrical cardioversion.

I

Intervention

Wearable digital devices for cardiac rhythm monitoring, including smartwatches, smart garments/shirts with integrated electrodes, ECG patches, smart rings, and smartphone-based applications utilizing photoplethysmography (PPG) and/or single- or multi-lead electrocardiography (ECG), often integrated with artificial intelligence (AI) and machine learning algorithms.

C

Comparator

Standard care, conventional 12-lead ECG, portable Holter ECG monitoring, or implantable loop recorders (ILRs).

O

Outcome

Detection, screening, and diagnosis of atrial fibrillation (AF) and quantification of AF burden.surrogate

This narrative review highlights that smartwatches and emerging smart garments utilizing PPG, single- or multi-lead ECG, and AI algorithms provide effective non-invasive screening and monitoring for atrial fibrillation, though physician ECG confirmation remains necessary and impacts on hard clinical outcomes require further study.

Limitations

Motion artefacts during physical activity reduce signal quality and cause false-positive or false-negative results.
Smartwatches predominantly provide semi-continuous monitoring and require active user interaction to record an ECG.
Limited ability of photoplethysmography (PPG) signals to reliably differentiate between complex supraventricular and ventricular tachyarrhythmias.
Definitive arrhythmia diagnosis still requires confirmation by a physician using an electrocardiogram.
Pre-existing ECG abnormalities can compromise the precision of automated single-lead ECG classification algorithms.
Smart garments are still undergoing technical and clinical validation, with signal quality decreasing at high exercise intensity.
Presence of motion artefacts during physical activity affecting signal quality and resulting in false-positive or false-negative results
Predominantly semi-continuous monitoring and requirement for active user interaction to record smartwatch ECGs
Lower automated AF detection rates with smartwatches compared with implantable loop recorders
Pre-existing ECG abnormalities compromise the precision of automated classification algorithms in single-lead ECGs
Difficulty reliably distinguishing between supraventricular and ventricular tachycardias based on PPG signals alone
Unclear impact of wearable monitoring on clinically relevant endpoints such as stroke, heart failure, hospitalisation, or earlier therapeutic intervention

Ask about this paper

Answers are grounded in this paper and cite their sources.

Implication

Supports AF screening with PPG-ECG wearables; leaves open effects on outcomes and optimal integration.

Abstract

Purpose of Review Digital devices play an increasingly important role in the detection and screening of cardiac arrhythmias. Atrial fibrillation (AF), the most common arrhythmia, is associated with an increased risk of stroke, heart failure, and mortality. This review summarises the current evidence on wearable devices for screening and diagnosing atrial fibrillation. Recent findings Numerous studies have demonstrated the value of wearables for AF detection and diagnosis. In addition, artificial intelligence enhances automated rhythm analysis and signal processing, supporting the increasing clinical implementation of digital technologies in outpatient care. Summary Single-lead ECG devices provide the strongest evidence for AF detection, with smartwatches representing one of the most extensively investigated wearable technology. Limitations include motion artefacts and predominantly semi-continuous monitoring. Future research should focus on integrating artificial intelligence to improve signal analysis and artefact reduction, and on evaluating the impact of wearable-based strategies on clinically relevant outcomes, including stroke and heart failure.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Beermann et al. (2026) conducted a review in Atrial fibrillation and other cardiac arrhythmias. Wearable arrhythmia detection devices (smartwatches and smart garments) vs. Conventional ECG monitoring (12-lead ECG, Holter monitoring, or standard care) was evaluated.

synapsesocial.com/papers/6aea772189a8acbed9c87ae9 https://doi.org/10.1007/s11886-026-02445-6

View Full Paper

Ask AI

Bookmark

Share

Wearable Arrhythmia Detection: Moving from your Watch to your Shirt?

Key Points

Structured PICO

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Wearable Arrhythmia Detection: Moving from your Watch to your Shirt?

Key Points

Structured PICO

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading