ReviewDiagnostics (Basel, Switzerland)2022
Current Advancement in Diagnosing Atrial Fibrillation by Utilizing Wearable Devices and Artificial Intelligence: A Review Study.
Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.
- Wearable Technology and Machine Learning for Prediction of Performance-Based and Patient-Reported Outcome Measures: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Wearable Devices and Machine Learning in Cardiovascular Monitoring: Current Evidence and Future Directions for Precision Medicine.Journal of personalized medicine · 2026Review
- RT-AFNet: A Hybrid ResNet-Transformer Architecture with Multi-Scale Fusion for Atrial Fibrillation Detection.Biosensors · 2026Article
- Diagnostic Accuracy of Wearable ECG Devices for Atrial Fibrillation and ST-Segment Changes: A Systematic Review.Diagnostics (Basel, Switzerland) · 2025Review
- AI-Driven Wearable Bioelectronics in Digital Healthcare.Biosensors · 2025Review
- The Importance of Timing in Performing a Holter ECG in Patients Diagnosed with an Embolic Stroke of Undetermined Source.Biomedicines · 2025Article
- Recent advances in the tools and techniques for AI-aided diagnosis of atrial fibrillation.Biophysics reviews · 2025Review
- Key Fundamentals and Examples of Sensors for Human Health: Wearable, Non-Continuous, and Non-Contact Monitoring Devices.Sensors (Basel, Switzerland) · 2025Article
- Wearables and Atrial Fibrillation: Advances in Detection, Clinical Impact, Ethical Concerns, and Future Perspectives.Cureus · 2025Review
- Biometrics of complete human pregnancy recorded by wearable devices.NPJ digital medicine · 2024Article
- Recent Advances in the Management of Non-rheumatic Atrial Fibrillation: A Comprehensive Review.Cureus · 2024Review
- Early warning of atrial fibrillation using deep learning.Patterns (New York, N.Y.) · 2024Article
- Wearables for early detection of atrial fibrillation and timely referral for Indigenous people ≥55 years: mixed-methods protocol.BMJ open · 2024Article
- Heart Rate Variability Analysis of Healthy Individuals and Patients with Ischemia and Arrhythmia.Diagnostics (Basel, Switzerland) · 2023Article
- Obesity-Related Atrial Fibrillation: Cardiac Manifestation of a Systemic Disease.Journal of cardiovascular development and disease · 2023Review
- A Bibliometric Analysis on Arrhythmia Detection and Classification from 2005 to 2022.Diagnostics (Basel, Switzerland) · 2023Review
- Evaluation of Mitochondrial Function in Blood Samples Shows Distinct Patterns in Subjects with Thyroid Carcinoma from Those with Hyperplasia.International journal of molecular sciences · 2023Article
- Personal recording devices for arrhythmia detection.The British journal of cardiology · 2023Article
- A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors.Sensors (Basel, Switzerland) · 2022Review
- Smart Consumer Wearables as Digital Diagnostic Tools: A Review.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Atrial fibrillation (AF) is a common arrhythmia affecting 8-10% of the population older than 80 years old. The importance of early diagnosis of atrial fibrillation has been broadly recognized since arrhythmias significantly increase the risk of stroke, heart failure and tachycardia-induced cardiomyopathy with reduced cardiac function. However, the prevalence of atrial fibrillation is often underestimated due to the high frequency of clinically silent atrial fibrillation as well as paroxysmal atrial fibrillation, both of which are hard to catch by routine physical examination or 12-lead electrocardiogram (ECG). The development of wearable devices has provided a reliable way for healthcare providers to uncover undiagnosed atrial fibrillation in the population, especially those most at risk. Furthermore, with the advancement of artificial intelligence and machine learning, the technology is now able to utilize the database in assisting detection of arrhythmias from the data collected by the devices. In this review study, we compare the different wearable devices available on the market and review the current advancement in artificial intelligence in diagnosing atrial fibrillation. We believe that with the aid of the progressive development of technologies, the diagnosis of atrial fibrillation shall be made more effectively and accurately in the near future.
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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.