ReviewSensors (Basel, Switzerland)2021
Recent Research for Unobtrusive Atrial Fibrillation Detection Methods Based on Cardiac Dynamics Signals: A Survey.
Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Detection of Atrial Fibrillation Using Multi-Site Ballistocardiogram with Piezoelectric Rubber Sheet Sensors.Sensors (Basel, Switzerland) · 2025Article
- A ballistocardiogram dataset with reference ECG signals for bed-based heart rhythm assessment.Scientific data · 2025Article
- Enhanced DWT for Denoising Heartbeat Signal in Non-Invasive Detection.Sensors (Basel, Switzerland) · 2025Article
- Recent advances in the tools and techniques for AI-aided diagnosis of atrial fibrillation.Biophysics reviews · 2025Review
- Intelligent Detection Method of Atrial Fibrillation by CEPNCC-BiLSTM Based on Long-Term Photoplethysmography Data.Sensors (Basel, Switzerland) · 2024Article
- Unobstructive Heartbeat Monitoring of Sleeping Infants and Young Children Using Sheet-Type PVDF Sensors.Sensors (Basel, Switzerland) · 2023Article
- Non-invasive monitoring of cardiac function through Ballistocardiogram: an algorithm integrating short-time Fourier transform and ensemble empirical mode decomposition.Frontiers in physiology · 2023Article
- Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review.Sensors (Basel, Switzerland) · 2022Review
- Quantitative Analysis Using Consecutive Time Window for Unobtrusive Atrial Fibrillation Detection Based on Ballistocardiogram Signal.Sensors (Basel, Switzerland) · 2022Article
- A Flexible Baseline Measuring System Based on Optics for Airborne DPOS.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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5 authors.
Funding
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia. It tends to cause multiple cardiac conditions, such as cerebral artery blockage, stroke, and heart failure. The morbidity and mortality of AF have been progressively increasing over the past few decades, which has raised widespread concern about unobtrusive AF detection in routine life. The up-to-date non-invasive AF detection methods include electrocardiogram (ECG) signals and cardiac dynamics signals, such as the ballistocardiogram (BCG) signal, the seismocardiogram (SCG) signal and the photoplethysmogram (PPG) signal. Cardiac dynamics signals can be collected by cushions, mattresses, fabrics, or even cameras, which is more suitable for long-term monitoring. Therefore, methods for AF detection by cardiac dynamics signals bring about extensive attention for recent research. This paper reviews the current unobtrusive AF detection methods based on the three cardiac dynamics signals, summarized as data acquisition and preprocessing, feature extraction and selection, classification and diagnosis. In addition, the drawbacks and limitations of the existing methods are analyzed, and the challenges in future work are discussed.
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