A review on sample entropy applications for the non-invasive analysis of atrial fibrillation electrocardiograms
The application of non-linear metrics to physiological signals is a valuable tool because
“hidden information” related to underlying mechanisms can be obtained. In this respect …
“hidden information” related to underlying mechanisms can be obtained. In this respect …
Prediction of atrial fibrillation using machine learning: a review
AS Tseng, PA Noseworthy - Frontiers in Physiology, 2021 - frontiersin.org
There has been recent immense interest in the use of machine learning techniques in the
prediction and screening of atrial fibrillation, a common rhythm disorder present with …
prediction and screening of atrial fibrillation, a common rhythm disorder present with …
Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems
Cardiovascular diseases are the number one cause of death worldwide. Currently, portable
battery-operated systems such as mobile phones with wireless ECG sensors have the …
battery-operated systems such as mobile phones with wireless ECG sensors have the …
Prediction of paroxysmal Atrial Fibrillation: A machine learning based approach using combined feature vector and mixture of expert classification on HRV signal
E Ebrahimzadeh, M Kalantari, M Joulani… - Computer methods and …, 2018 - Elsevier
Abstract Background and Objective Paroxysmal Atrial Fibrillation (PAF) is one of the most
common major cardiac arrhythmia. Unless treated timely, PAF might transform into …
common major cardiac arrhythmia. Unless treated timely, PAF might transform into …
Feature extraction of electrocardiogram signals by applying adaptive threshold and principal component analysis
R Rodríguez, A Mexicano, J Bila… - Journal of applied …, 2015 - scielo.org.mx
This paper presents a novel approach for QRS complex detection and extraction of
electrocardiogram signals for different types of arrhythmias. Firstly, the ECG signal is filtered …
electrocardiogram signals for different types of arrhythmias. Firstly, the ECG signal is filtered …
A robust QRS detection and accurate R-peak identification algorithm for wearable ECG sensors
This paper presents a robust QRS detection algorithm that is capable of detecting QRS
complexes as well as accurately identifying R-peaks. The proposed bilateral threshold …
complexes as well as accurately identifying R-peaks. The proposed bilateral threshold …
[HTML][HTML] Prediction of paroxysmal atrial fibrillation using new heart rate variability features
Paroxysmal atrial fibrillation (PAF) is a cardiac arrhythmia that can eventually lead to heart
failure or stroke if left untreated. Early detection of PAF is therefore crucial to prevent any …
failure or stroke if left untreated. Early detection of PAF is therefore crucial to prevent any …
Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal
M Mohebbi, H Ghassemian - Computer methods and programs in …, 2012 - Elsevier
In this paper, an effective paroxysmal atrial fibrillation (PAF) prediction algorithm is
presented, which is based on analysis of the heart rate variability (HRV) signal. The …
presented, which is based on analysis of the heart rate variability (HRV) signal. The …
Electrocardiographic predictors of atrial fibrillation
BACKGROUND: Atrial fibrillation (AF) is the most prevalent arrhythmia in the United States
and accounts for more than 750,000 strokes per year. Noninvasive predictors of AF may …
and accounts for more than 750,000 strokes per year. Noninvasive predictors of AF may …
Application of the relative wavelet energy to heart rate independent detection of atrial fibrillation
Abstract Background and Objectives Atrial fibrillation (AF) is the most common sustained
cardiac arrhythmia and a growing healthcare burden worldwide. It is often asymptomatic and …
cardiac arrhythmia and a growing healthcare burden worldwide. It is often asymptomatic and …