AIMC Topic: Atrial Fibrillation

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Wearables in cardiology: Here to stay.

Heart rhythm
The adoption of wearables in medicine has rapidly expanded worldwide. New generations of wearables are emerging, driven by consumers' demand to monitor their own health. With the ongoing development of new features capable of assessing real-time biom...

A new smart wristband equipped with an artificial intelligence algorithm to detect atrial fibrillation.

Heart rhythm
BACKGROUND: Detection of atrial fibrillation (AF) occurrence over a long duration has been a challenge in the screening and follow-up of AF patients. Wearable devices may be an ideal solution.

Anticoagulant treatment in elderly patients with atrial fibrillation: a position paper.

Geriatrie et psychologie neuropsychiatrie du vieillissement
Atrial fibrillation (AF) is common in the elderly. The treatment of this condition is based on anticoagulation to prevent stroke and systemic arterial embolism. Vitamin K antagonists (VKAs) have long been the only anticoagulants available for the man...

Convolutional Neural Network Based Detection of Atrial Fibrillation Combing R-R intervals and F-wave Frequency Spectrum.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial Fibrillation (AF) is one of the arrhythmias that is common and serious in clinic. In this study, a novel method of AF classification with a convolutional neural network (CNN) was proposed, and particularly two cardiac rhythm features of R-R in...

Automatic Detection of Atrial Fibrillation from Ballistocardiogram (BCG) Using Wavelet Features and Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents an unobtrusive method for automatic detection of atrial fibrillation (AF) from single-channel ballistocardiogram (BCG) recordings during sleep. We developed a remote data acquisition system that measures BCG signals through an ele...

A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet Transform.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial fibrillation (AF) is one of the most common arrhythmias. The automatic AF detection is of great clinical significance but at the same time it remains a big problem to researchers. In this study, a novel deep learning method to detect AF was pr...

Deep Learning Approach for Highly Specific Atrial Fibrillation and Flutter Detection based on RR Intervals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial fibrillation (AF) and atrial flutter (AFL) represent atrial arrhythmias closely related to increasing risk for embolic stroke, and therefore being in the focus of cardiologists. While the reported methods for AF detection exhibit high performa...

Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network.

IEEE transactions on medical imaging
Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia. Current treatments for AF remain suboptimal due to a lack of understanding of the underlying atrial structures that directly sustain AF. Existing approaches for analyzing atri...