A survey on ECG analysis
The electrocardiogram (ECG) signal basically corresponds to the electrical activity of the
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
AN Uwaechia, DA Ramli - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …
and has recently received significant interest as a promising biometric trait. However, ECG …
Deep learning approach for active classification of electrocardiogram signals
In this paper, we propose a novel approach based on deep learning for active classification
of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation …
of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation …
AFCNNet: Automated detection of AF using chirplet transform and deep convolutional bidirectional long short term memory network with ECG signals
Atrial fibrillation (AF) is the most common type of cardiac arrhythmia and is characterized by
the heart's beating in an uncoordinated manner. In clinical studies, patients often do not …
the heart's beating in an uncoordinated manner. In clinical studies, patients often do not …
An overview on state-of-the-art electrocardiogram signal processing methods: Traditional to AI-based approaches
VA Ardeti, VR Kolluru, GT Varghese… - Expert Systems with …, 2023 - Elsevier
Over the last decade, cardiovascular diseases (CVD's) are the leading cause of death
globally. Early prediction of CVD's can help in reducing the complications of high-risk …
globally. Early prediction of CVD's can help in reducing the complications of high-risk …
A review on the state of the art in atrial fibrillation detection enabled by machine learning
Atrial Fibrillation (AF) the most commonly occurring type of cardiac arrhythmia is one of the
main causes of morbidity and mortality worldwide. The timely diagnosis of AF is an equally …
main causes of morbidity and mortality worldwide. The timely diagnosis of AF is an equally …
[HTML][HTML] A survey on physiological signal-based emotion recognition
Physiological signals are the most reliable form of signals for emotion recognition, as they
cannot be controlled deliberately by the subject. Existing review papers on emotion …
cannot be controlled deliberately by the subject. Existing review papers on emotion …
A novel deep wavelet convolutional neural network for actual ecg signal denoising
Recently, more than 80% of sudden cardiac death is caused by arrhythmia, whose
incidence has increased rapidly. In the actual wearable device acquisition process, ECG …
incidence has increased rapidly. In the actual wearable device acquisition process, ECG …
ECG classification using three-level fusion of different feature descriptors
Z Golrizkhatami, A Acan - Expert Systems with Applications, 2018 - Elsevier
Fusion of feature descriptors extracted from a signal through different methods is an
important issue for the exploitation of representational power of each descriptor. In this …
important issue for the exploitation of representational power of each descriptor. In this …
Time-varying coherence function for atrial fibrillation detection
We introduce a novel method for the automatic detection of atrial fibrillation (AF) using time-
varying coherence functions (TVCF). The TVCF is estimated by the multiplication of two time …
varying coherence functions (TVCF). The TVCF is estimated by the multiplication of two time …