Automatic digitization of paper electrocardiograms–A systematic review
The digitization of electrocardiogram paper records is an essential step to preserve and
analyze cardiac data. This digitization process is not flawless as it involves several …
analyze cardiac data. This digitization process is not flawless as it involves several …
Development of a convolutional neural network model to predict coronary artery disease based on single-lead and twelve-lead ECG signals
ST Vasudeva, SS Rao, NK Panambur, AK Shettigar… - Applied Sciences, 2022 - mdpi.com
Coronary artery disease (CAD) is one of the most common causes of heart ailments; many
patients with CAD do not exhibit initial symptoms. An electrocardiogram (ECG) is a …
patients with CAD do not exhibit initial symptoms. An electrocardiogram (ECG) is a …
Efficient approach for digitization of the cardiotocography signals
Cardiotocography (CTG) is generally provided on printed traces, and digitization of CTG
signal is important for forthcoming assessments. In this paper, a new algorithm relies on the …
signal is important for forthcoming assessments. In this paper, a new algorithm relies on the …
[PDF][PDF] Features extraction technique for ECG recording paper
HK Khleaf, KH Ghazali, AN Abdalla - Proceeding of the …, 2013 - researchgate.net
Generally the ECG is recorded on a thermal paper which cannot be stored for a long time,
because thermal trace over time becomes erased gradually. However some hospitals are …
because thermal trace over time becomes erased gradually. However some hospitals are …
Electrocardiogram Two-Dimensional Motifs: A Study Directed at Cardio Vascular Disease Classification
A process is described, using the concept of 2D motifs and 2D discords, to build
classification models to classify Cardiovascular Disease using Electrocardiogram (ECG) …
classification models to classify Cardiovascular Disease using Electrocardiogram (ECG) …
Covering rough set-based classification for cardiac arrhythmia
SS Kumar, HH Inbarani - International Journal of Intelligent …, 2017 - inderscienceonline.com
The objective of this work is to use data processing methods to unravel the biomedical
difficulties of detecting a selection of arrhythmia conditions from patient's electrocardiograph …
difficulties of detecting a selection of arrhythmia conditions from patient's electrocardiograph …
Scanned ECG Arrhythmia Classification Using a Pre-trained Convolutional Neural Network as a Feature Extractor
The classification of cardiovascular diseases using ECG data is considered. It is argued that
to obtain a satisfactory classification features should be extracted from ECG images in their …
to obtain a satisfactory classification features should be extracted from ECG images in their …
Ecg paper record digitization and diagnosis using deep learning
N Mehendale, S Mishra, V Shah… - Available at SSRN …, 2020 - papers.ssrn.com
Electrocardiogram (ECG) is one of the most essential tools for detecting heart problems. Till
today most of the ECG records are available in paper form. It can be challenging and time …
today most of the ECG records are available in paper form. It can be challenging and time …
[HTML][HTML] Computationally Efficient LOB Algorithm for Digitization of Degraded Paper ECG Reports
R Patil, R Karandikar - Biomedical and Pharmacology …, 2023 - biomedpharmajournal.org
Purpose: A less computationally intensive methodology is required to digitise paper
Electrocardiogram (ECG) records from scanned photographs so that it can be implemented …
Electrocardiogram (ECG) records from scanned photographs so that it can be implemented …