[HTML][HTML] ECG signal classification using various machine learning techniques
S Celin, K Vasanth - Journal of medical systems, 2018 - Springer
Electrocardiogram (ECG) signal is a process that records the heart rate by using electrodes
and detects small electrical changes for each heat rate. It is used to investigate some types …
and detects small electrical changes for each heat rate. It is used to investigate some types …
A new automated CNN deep learning approach for identification of ECG congestive heart failure and arrhythmia using constant-Q non-stationary Gabor transform
AS Eltrass, MB Tayel, AI Ammar - Biomedical signal processing and control, 2021 - Elsevier
Electrocardiogram (ECG) is an important noninvasive diagnostic method for interpretation
and identification of various kinds of heart diseases. In this work, a new Deep Learning (DL) …
and identification of various kinds of heart diseases. In this work, a new Deep Learning (DL) …
Automated ECG multi-class classification system based on combining deep learning features with HRV and ECG measures
AS Eltrass, MB Tayel, AI Ammar - Neural Computing and Applications, 2022 - Springer
Electrocardiogram (ECG) serves as the gold standard for noninvasive diagnosis of several
types of heart disorders. In this study, a novel hybrid approach of deep neural network …
types of heart disorders. In this study, a novel hybrid approach of deep neural network …
A secure fuzzy extractor based biometric key authentication scheme for body sensor network in Internet of Medical Things
RK Mahendran, P Velusamy - Computer Communications, 2020 - Elsevier
Body sensor network (BSN) is largely utilized in IoMT to attain easier access of patient's data
remotely without much cost by connecting the various bio-sensors. However, there is a …
remotely without much cost by connecting the various bio-sensors. However, there is a …
Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review
Heart rate variability (HRV) is an important metric with a variety of applications in clinical
situations such as cardiovascular diseases, diabetes mellitus, and mental health. HRV data …
situations such as cardiovascular diseases, diabetes mellitus, and mental health. HRV data …
A new approach for congestive heart failure and arrhythmia classification using angle transformation with LSTM
Electrocardiogram (ECG) is widely used as a diagnostic method to identify various heart
diseases such as heart failure, cardiac and sinus rhythms. The ECG signal analyzes the …
diseases such as heart failure, cardiac and sinus rhythms. The ECG signal analyzes the …
A new approach for congestive heart failure and arrhythmia classification using downsampling local binary patterns with LSTM
S Akdağ, F Kuncan, Y Kaya - Turkish Journal of Electrical …, 2022 - journals.tubitak.gov.tr
Electrocardiogram (ECG) is a vital diagnosis approach for the rapid explication and
detection of various heart diseases, especially cardiac arrest, sinus rhythms, and heart …
detection of various heart diseases, especially cardiac arrest, sinus rhythms, and heart …
Optimized adaptive noise canceller for denoising cardiovascular signal using SOS algorithm
Cardiovascular or electrocardiogram signals (ECG) are contaminated by various artefacts
while recording which in turn degrades the quality of the vital information present in the …
while recording which in turn degrades the quality of the vital information present in the …
Novel cascade filter design of improved sparse low-rank matrix estimation and kernel adaptive filtering for ECG denoising and artifacts cancellation
AS Eltrass - Biomedical Signal Processing and Control, 2022 - Elsevier
ElectroCardioGram (ECG) signals are highly vulnerable to disturbances caused by noise
and artifact sources which can degrade the ECG signal quality and increase the difficulty in …
and artifact sources which can degrade the ECG signal quality and increase the difficulty in …
A novel wavelet-based filtering strategy to remove powerline interference from electrocardiograms with atrial fibrillation
Objective: The electrocardiogram (ECG) is currently the most widely used recording to
diagnose cardiac disorders, including the most common supraventricular arrhythmia, such …
diagnose cardiac disorders, including the most common supraventricular arrhythmia, such …