ArticleScientific reports2022
Impact of recording length and other arrhythmias on atrial fibrillation detection from wrist photoplethysmogram using smartwatches.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Diagnostic accuracy of ECG smart chest patches versus PPG smartwatches for atrial fibrillation detection: a systematic review and meta-analysis.BMC cardiovascular disorders · 2025Pooled it
- 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
- A multitask Transformer-VAE framework for robust PPG denoising and atrial fibrillation screening.BMC medical imaging · 2026Article
- Advances in cardiovascular signal analysis with future directions: a review of machine learning and deep learning models for cardiovascular disease classification based on ECG, PCG, and PPG signals.Biomedical engineering letters · 2025Review
- AI-Driven Wearable Bioelectronics in Digital Healthcare.Biosensors · 2025Review
- Comparison of diagnostic accuracy of electrocardiogram-based versus photoplethysmography-based smartwatches for atrial fibrillation detection: A Systematic Review and Meta-Analysis.Annals of medicine and surgery (2012) · 2025Article
- The role of atrial fibrillation in vascular cognitive impairment and dementia: epidemiology, pathophysiology, and preventive strategies.GeroScience · 2025Review
- Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review.Frontiers in cardiovascular medicine · 2025Review
- An efficient approach for detecting atrial fibrillation in ischemic stroke patients using a wearable device: a prospective multicenter substudy of the STABLED trial.Frontiers in neurology · 2025Article
- Detection of Arrhythmias Using Smartwatches-A Systematic Literature Review.Healthcare (Basel, Switzerland) · 2024Review
- Photoplethysmography based atrial fibrillation detection: a continually growing field.Physiological measurement · 2024Review
- Smartwatches in healthcare medicine: assistance and monitoring; a scoping review.BMC medical informatics and decision making · 2023Article
- Wrist-worn device combining PPG and ECG can be reliably used for atrial fibrillation detection in an outpatient setting.Frontiers in cardiovascular medicine · 2023Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to evaluate whether quantitative analysis of wrist photoplethysmography (PPG) could detect atrial fibrillation (AF). Continuous electrocardiograms recorded using an electrophysiology recording system and PPG obtained using a wrist-worn smartwatch were simultaneously collected from patients undergoing catheter ablation or electrical cardioversion. PPG features were extracted from 10, 25, 40, and 80 heartbeats of the split segments. Machine learning with a support vector machine and random forest approach were used to detect AF. A total of 116 patients were evaluated. We annotated > 117 h of PPG. A total of 6475 and 3957 segments of 25-beat pulse-to-pulse intervals (PPIs) were annotated as AF and sinus rhythm, respectively. The accuracy of the 25 PPIs yielded a test area under the receiver operating characteristic curve (AUC) of 0.9676, which was significantly better than the AUC for the 10 PPIs (0.9453; P < .001). PPGs obtained from another 38 patients with frequent premature ventricular/atrial complexes (PVCs/PACs) were used to evaluate the impact of other arrhythmias on diagnostic accuracy. The new AF detection algorithm achieved an AUC of 0.9680. The appropriate data length of PPG for optimizing the PPG analytics program was 25 heartbeats. Algorithm modification using a machine learning approach shows robustness to PVCs/PACs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.