LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "arrhythmia classification" as a keyword



ECG arrhythmia classification using artificial intelligence and nonlinear and nonstationary decomposition

Sign Up to like & get
recommendations! Published in 2019 at "Signal, Image and Video Processing"

DOI: 10.1007/s11760-019-01479-4

Abstract: AbstractECG signals reflect all the electrical activities of the heart. Consequently, it plays a key role in the diagnosis of the cardiac disorder and arrhythmia detection. Based on tiny alterations in the amplitude, duration and… read more here.

Keywords: arrhythmia classification; arrhythmia; decomposition; nonstationary decomposition ... See more keywords

An improved cardiac arrhythmia classification using an RR interval-based approach

Sign Up to like & get
recommendations! Published in 2021 at "Biocybernetics and Biomedical Engineering"

DOI: 10.1016/j.bbe.2021.04.004

Abstract: Abstract Accurate and early detection of cardiac arrhythmia present in an electrocardiogram (ECG) can prevent many premature deaths. Cardiac arrhythmia arises due to the improper conduction of electrical impulses throughout the heart. In this paper,… read more here.

Keywords: interval based; arrhythmia; arrhythmia classification; cardiac arrhythmia ... See more keywords
Photo from wikipedia

Optimal Multi-Stage Arrhythmia Classification Approach

Sign Up to like & get
recommendations! Published in 2020 at "Scientific Reports"

DOI: 10.1038/s41598-020-59821-7

Abstract: Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme… read more here.

Keywords: multi stage; classification; arrhythmia classification; approach ... See more keywords

A novel arrhythmia classification of electrocardiogram signal based on modified HRNet and ECA

Sign Up to like & get
recommendations! Published in 2022 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/ac51a3

Abstract: Electrocardiogram (ECG) signals have been widely used to detect cardiac arrhythmia. Visual inspection is not only time consuming, but also may lead to misdiagnosis and affect the prevention or treatment of the disease. Therefore, automatic… read more here.

Keywords: modified hrnet; arrhythmia classification; hrnet; based modified ... See more keywords
Photo from wikipedia

Three-Heartbeat Multilead ECG Recognition Method for Arrhythmia Classification

Sign Up to like & get
recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3169893

Abstract: Electrocardiogram (ECG) is the primary basis for the diagnosis of cardiovascular diseases. However, the amount of ECG data of patients makes manual interpretation time-consuming and onerous. Therefore, the intelligent ECG recognition technology is an important… read more here.

Keywords: classification; ecg data; ecg; method ... See more keywords

Morphological Arrhythmia Classification Based on Inter-Patient and Two Leads ECG Using Machine Learning

Sign Up to like & get
recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3469640

Abstract: Arrhythmia is a heart disorder in which the heart beats irregularly. Electrocardiogram (ECG) has been widely used as a tool for detecting arrhythmias. However, the interpretation of ECG recordings is still tedious, time-consuming, and a… read more here.

Keywords: classification; arrhythmia classification; inter patient; machine learning ... See more keywords

Multi-Scale Convolutional Neural Network Ensemble for Multi-Class Arrhythmia Classification.

Sign Up to like & get
recommendations! Published in 2021 at "IEEE journal of biomedical and health informatics"

DOI: 10.1109/jbhi.2021.3138986

Abstract: The automated analysis of electrocardiogram (ECG) signals plays a crucial role in the early diagnosis and management of cardiac arrhythmias. The diverse etiology of arrhythmia and the subtle variations in the pathological ECG characteristics pose… read more here.

Keywords: convolutional neural; network; arrhythmia classification; ecg ... See more keywords

Arrhythmia Classification Algorithm Based on a Two-Dimensional Image and Modified EfficientNet

Sign Up to like & get
recommendations! Published in 2022 at "Computational Intelligence and Neuroscience"

DOI: 10.1155/2022/8683855

Abstract: The classification and identification of arrhythmias using electrocardiogram (ECG) signals are of great practical significance in the early prevention and diagnosis of cardiovascular diseases. In this study, we propose an arrhythmia classification algorithm based on… read more here.

Keywords: network; algorithm based; classification; classification algorithm ... See more keywords

Automated arrhythmia classification based on a pyramid dense connectivity layer and BiLSTM

Sign Up to like & get
recommendations! Published in 2024 at "Technology and Health Care"

DOI: 10.1177/09287329241290941

Abstract: Background Deep neural networks (DNNs) have recently been significantly applied to automatic arrhythmia classification. However, their classification accuracy still has room for improvement. Objectives The aim of this study is to address the existing limitations… read more here.

Keywords: classification; connectivity layer; arrhythmia classification; dense connectivity ... See more keywords

WavelNet: A novel convolutional neural network architecture for arrhythmia classification from electrocardiograms

Sign Up to like & get
recommendations! Published in 2023 at "Computer methods and programs in biomedicine"

DOI: 10.2139/ssrn.4260024

Abstract: BACKGROUND AND OBJECTIVE Automated detection of arrhythmias from electrocardiograms (ECGs) can be of considerable assistance to medical professionals in providing efficient treatment for patients with cardiovascular diseases. In recent times, convolutional neural network (CNN)-based arrhythmia… read more here.

Keywords: model; arrhythmia classification; wavelnet; performance ... See more keywords

Infinite Feature Selection Based Arrhythmia Classification Using Semantic Features and Random Forest

Sign Up to like & get
recommendations! Published in 2019 at "International Journal of Intelligent Engineering and Systems"

DOI: 10.22266/ijies2019.0630.21

Abstract: In this research study, arrhythmia classification was assessed by using Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. After signal acquisition, semantic feature extraction (combination of statistical, entropy, linear and non-linear features) was used… read more here.

Keywords: arrhythmia classification; methodology; feature selection; feature ... See more keywords