Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review

HV Denysyuk, RJ Pinto, PM Silva, RP Duarte… - Heliyon, 2023 - cell.com
The prevalence of cardiovascular diseases is increasing around the world. However, the
technology is evolving and can be monitored with low-cost sensors anywhere at any time …

A Systematic Review on the Use of Consumer-Based ECG Wearables on Cardiac Health Monitoring

R Wang, SCM Veera, O Asan… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
This systematic review aims to summarize the consumer wearable devices used for
collecting ECG signals, explore the models or algorithms employed in diagnosing and …

An automatic premature ventricular contraction recognition system based on imbalanced dataset and pre-trained residual network using transfer learning on ECG …

H Ullah, MBB Heyat, F Akhtar, AY Muaad… - Diagnostics, 2022 - mdpi.com
The development of automatic monitoring and diagnosis systems for cardiac patients over
the internet has been facilitated by recent advancements in wearable sensor devices from …

Automatic premature ventricular contraction detection using deep metric learning and KNN

J Yu, X Wang, X Chen, J Guo - Biosensors, 2021 - mdpi.com
Premature ventricular contractions (PVCs), common in the general and patient population,
are irregular heartbeats that indicate potential heart diseases. Clinically, long-term …

Automated diagnosis of coronary artery disease using scalogram-based tensor decomposition with heart rate signals

N Nesaragi, A Sharma, S Patidar… - Medical Engineering & …, 2022 - Elsevier
Early identification of coronary artery disease (CAD) can facilitate timely clinical intervention
and save lives. This study aims to develop a machine learning framework that uses tensor …

A Review on Multisensor Data Fusion for Wearable Health Monitoring

A John, B Cardiff, D John - arXiv preprint arXiv:2412.05895, 2024 - arxiv.org
The growing demand for accurate, continuous, and non-invasive health monitoring has
propelled multi-sensor data fusion to the forefront of healthcare technology. This review aims …

Searching for premature ventricular contraction from electrocardiogram by using one-dimensional convolutional neural network

J Yu, X Wang, X Chen, J Guo - Electronics, 2020 - mdpi.com
Premature ventricular contraction (PVC) is a common cardiac arrhythmia that can occur in
ordinary healthy people and various heart disease patients. Clinically, cardiologists usually …

Application of tensor decomposition in removing motion artifacts from the measurements of a wireless electrocardiogram

J Lilienthal, W Dargie - 2020 IEEE 23rd International …, 2020 - ieeexplore.ieee.org
Wireless electrocardiograms (WECG) facilitate the long-term monitoring of patients in their
residential environment. However, the freedom of movement provokes motion artifacts in the …

[PDF][PDF] Premature Ventricular Contraction Detection Based on Chebyshev Polynomials and K Nearest Neighbours Classifier.

F Guendouzi, M Attari - Traitement du Signal, 2023 - researchgate.net
Accepted: 9 March 2023 Premature ventricular contraction (PVC) is among the most
prevalent forms of arrhythmia diagnosed in clinical settings. Arrhythmias can be recognised …

A Review on Heart Diseases Prediction Using Artificial Intelligence

R Hasnat, A Al Mamun, A Musha… - … Conference on Machine …, 2022 - Springer
Heart disease is one of the major concerns of this modern world. The insufficiency of the
experts has made this issue a bigger concern. Diagnosing heart diseases at an early stage …