ArticleEuropace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology2024
Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation.
Article in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 25 citations in OpenAlex.
- Improving atrial fibrillation or flutter detection and management by smartphone-based photoplethysmography rhythm monitoring following cardiac surgery: a pragmatic randomized trial.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Trial
- Wearable smartwatches for atrial fibrillation detection and burden estimation after ablation: comparison with continuous monitoring.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026Article
- [Atrial fibrillation in primary care: Towards a proactive risk-based model focused on early prevention].Atencion primaria · 2026Article
- Diagnostic performance of two commercially available, PPG-based smartphone applications to detect atrial fibrillation.European heart journal. Digital health · 2026Article
- Atrial Fibrillation Detection from At-Rest PPG Signals Using an SDOF-TF Method.Sensors (Basel, Switzerland) · 2026Article
- Multi class photoplethysmography-based deep model for cardiovascular disease classification.PloS one · 2026Article
- Relations of Artificial Intelligence Vascular Age With Cardiometabolic Disease Progression: The Framingham Heart Study.Journal of the American Heart Association · 2025Article
- Fibricheck detection capabilities for atrial fibrillation (FDA-AF): a multicenter validation study.NPJ digital medicine · 2025Article
- Implementation of new concise care pathways into a software tool to detect and manage comorbidities in older patients with atrial fibrillation: the Horizon 2020 EHRA-PATHS project.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Article
- Feasibility and diagnostic yield of a photoplethysmography-based arrhythmia screening and integrated management pathway in a COPD outpatient clinic.ERJ open research · 2025Article
- Ultra-short-term heart rate variability using a photoplethysmography-based smartphone application: a TeleCheck-AF subanalysis.European heart journal. Digital health · 2025Article
- State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Article
- Article
- External validation of a machine learning-based classification algorithm for ambulatory heart rhythm diagnostics in pericardioversion atrial fibrillation patients using smartphone photoplethysmography: the SMARTBEATS-ALGO study.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Article
- Initial experience with a virtual atrial fibrillation clinic after pulmonary vein isolation using follow-up with photoplethysmography.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2025Article
- Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study.JMIR formative research · 2025Article
- Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study.JMIR formative research · 2025Article
- Evidence Gaps and Lessons in the Early Detection of Atrial Fibrillation: A Prospective Study in a Primary Care Setting (PREFATE Study).Biomedicines · 2025Article
- Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review.Frontiers in cardiovascular medicine · 2025Review
- Smartphone app-based approximation of time spent with atrial fibrillation and symptoms in patients after catheter ablation: data from the TeleCheck-AF project.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024Article
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
Abstract
aimsPhotoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. METHODS AND
resultsFifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7-99.9%], specificity (99.9%; CI: 99.8-100.0%), positive predictive value (99.6%; CI: 99.1-100.0%), and negative predictive value (99.6%; CI: 99.0-100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland-Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m.
conclusionSmartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.
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