ArticleSensors (Basel, Switzerland)2020
A Wearable Electrocardiogram Telemonitoring System for Atrial Fibrillation Detection.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
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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
24 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- 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
- Medical Technology: A Systematic Review on Medical Devices Utilized for Epilepsy Prediction and Management.Current neuropharmacology · 2022Pooled 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
- ScaHybNet: a scalogram-based hybrid ensemble network for ECG arrhythmia classification.Scientific reports · 2026Article
- Physiological Monitoring Applications of Wearable Multimodal Fusion Systems Based on ECG and PPG: A Comprehensive Review.Sensors (Basel, Switzerland) · 2026Review
- Digital therapeutics into geriatric cardiovascular emergency care.Frontiers in digital health · 2026Review
- 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
- Analysis of the Independent Risk Factors of second-Degree Atrioventricular Block in Patients with Atrial Fibrillation and the Diagnostic Efficacy of Dynamic Electrocardiogram.International journal of general medicine · 2025Article
- Predictive Data Analytics in Telecare and Telehealth: Systematic Scoping Review.Online journal of public health informatics · 2024Article
- A Narrowband IoT Personal Sensor for Long-Term Heart Rate Monitoring and Atrial Fibrillation Detection.Sensors (Basel, Switzerland) · 2024Article
- IoT-Based Heartbeat Rate-Monitoring Device Powered by Harvested Kinetic Energy.Sensors (Basel, Switzerland) · 2024Article
- Wearable EMG Measurement Device Using Polyurethane Foam for Motion Artifact Suppression.Sensors (Basel, Switzerland) · 2024Article
- Cloud-Integrated Smart Nanomembrane Wearables for Remote Wireless Continuous Health Monitoring of Postpartum Women.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review.Sensors (Basel, Switzerland) · 2023Review
- Article
- Applying Artificial Intelligence to Wearable Sensor Data to Diagnose and Predict Cardiovascular Disease: A Review.Sensors (Basel, Switzerland) · 2022Review
- Quantitative Analysis Using Consecutive Time Window for Unobtrusive Atrial Fibrillation Detection Based on Ballistocardiogram Signal.Sensors (Basel, Switzerland) · 2022Article
- Using Minimum Redundancy Maximum Relevance Algorithm to Select Minimal Sets of Heart Rate Variability Parameters for Atrial Fibrillation Detection.Journal of clinical medicine · 2022Article
- Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View.JMIR medical informatics · 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
5 authors.
Funding
Abstract
In this paper we proposed a wearable electrocardiogram (ECG) telemonitoring system for atrial fibrillation (AF) detection based on a smartphone and cloud computing. A wearable ECG patch was designed to collect ECG signals and send the signals to an Android smartphone via Bluetooth. An Android APP was developed to display the ECG waveforms in real time and transmit every 30 s ECG data to a remote cloud server. A machine learning (CatBoost)-based ECG classification method was proposed to detect AF in the cloud server. In case of detected AF, the cloud server pushed the ECG data and classification results to the web browser of a doctor. Finally, the Android APP displayed the doctor's diagnosis for the ECG signals. Experimental results showed the proposed CatBoost classifier trained with 17 selected features achieved an overall F
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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.