Post-processing refined ECG delineation based on 1D-UNet

Z Chen, M Wang, M Zhang, W Huang, H Gu… - … Signal Processing and …, 2023 - Elsevier
The Electrocardiography (ECG) serves as a standard method for diagnosing cardiovascular
disease due to its minimal risk, affordable price and simple application. Clinical information …

Segmentation of the ECG signal by means of a linear regression algorithm

J Aspuru, A Ochoa-Brust, RA Félix, W Mata-López… - Sensors, 2019 - mdpi.com
The monitoring and processing of electrocardiogram (ECG) beats have been actively
studied in recent years: new lines of research have even been developed to analyze ECG …

ECG signal denoising and features extraction using unbiased FIR smoothing

C Lastre-Domínguez, YS Shmaliy… - BioMed research …, 2019 - Wiley Online Library
Methods of the electrocardiography (ECG) signal features extraction are required to detect
heart abnormalities and different kinds of diseases. However, different artefacts and …

SEResUTer: a deep learning approach for accurate ECG signal delineation and atrial fibrillation detection

X Li, W Cai, B Xu, Y Jiang, M Qi… - Physiological …, 2023 - iopscience.iop.org
Objective. Accurate detection of electrocardiogram (ECG) waveforms is crucial for computer-
aided diagnosis of cardiac abnormalities. This study introduces SEResUTer, an enhanced …

Shannon's energy based algorithm in ECG signal processing

H Beyramienanlou, N Lotfivand - … and mathematical methods in …, 2017 - Wiley Online Library
Physikalisch‐Technische Bundesanstalt (PTB) database is electrocardiograms (ECGs) set
from healthy volunteers and patients with different heart diseases. PTB is provided for …

A knowledge-based deep learning method for ECG signal delineation

J Wang, R Li, R Li, B Fu - Future Generation Computer Systems, 2020 - Elsevier
The delineation of electrocardiograms (ECG) is a crucial step designed to extract signal
characteristics and assist cardiologists in diagnosing certain diseases. It refers to the …

A machine-learning approach for detection and quantification of QRS fragmentation

G Goovaerts, S Padhy, B Vandenberk… - IEEE journal of …, 2018 - ieeexplore.ieee.org
Objective: Fragmented QRS (fQRS) is an accessible biomarker and indication of myocardial
scarring that can be detected from the electrocardiogram (ECG). Nowadays, fQRS scoring is …

Beat-to-beat electrocardiogram waveform classification based on a stacked convolutional and bidirectional long short-term memory

S Nurmaini, A Darmawahyuni, MN Rachmatullah… - IEEE …, 2021 - ieeexplore.ieee.org
Delineating the electrocardiogram (ECG) waveform is an important step with high
significance in cardiology diagnosis. It refers to extract the ECG morphology in start, peak …

[HTML][HTML] ECG PQRST complex detector and heart rate variability analysis using temporal characteristics of fiducial points

TW Bae, KK Kwon - Biomedical Signal Processing and Control, 2021 - Elsevier
The detection accuracy of fiducial points related to the main waves of electrocardiogram
(ECG)—the PQRST complex—considerably affects the heart rate variability (HRV) accuracy …

A greedy graph search algorithm based on changepoint analysis for automatic QRS complex detection

A Fotoohinasab, T Hocking, F Afghah - Computers in biology and medicine, 2021 - Elsevier
The electrocardiogram (ECG) signal is the most widely used non-invasive tool for the
investigation of cardiovascular diseases. Automatic delineation of ECG fiducial points, in …