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.
Highlights
Emiliano Schena and Atrial fibrillation (AF) is one of the most common arrhythmias that increases the risk of heart diseases, such as cardiogenic stroke and heart failure
The purpose of this paper is to provide a comprehensive summary of previous work on unobtrusive AF detection methods based on the three cardiac dynamics signals, which could aid in developing future research and guidance of ideas for home AF monitoring
This study sums up the major research on non-invasive AF detection methods based on cardiac dynamics signals, which are more suitable for long-term unobtrusive cardiovascular monitoring at home
Summary
Emiliano Schena and Atrial fibrillation (AF) is one of the most common arrhythmias that increases the risk of heart diseases, such as cardiogenic stroke and heart failure. Paroxysmal AF is usually asymptomatic, difficult to detect in daily life, and may deteriorate to persistent and permanent or even cause various malignant cardiovascular diseases [4]. Unobtrusive AF detecting methods include ECG signals from portable devices and cardiac dynamics signals. The cardiac dynamics signal has the same rhythm as the ECG signal, which helps diagnose arrhythmias, especially in the detection of AF. The purpose of this paper is to provide a comprehensive summary of previous work on unobtrusive AF detection methods based on the three cardiac dynamics signals, which could aid in developing future research and guidance of ideas for home AF monitoring.
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