ECG arrhythmia classification using artificial intelligence and nonlinear and nonstationary decomposition
Sign Up to like & getrecommendations! 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 & getrecommendations! 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
Optimal Multi-Stage Arrhythmia Classification Approach
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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 & getrecommendations! 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
Three-Heartbeat Multilead ECG Recognition Method for Arrhythmia Classification
Sign Up to like & getrecommendations! 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
Multi-Scale Convolutional Neural Network Ensemble for Multi-Class Arrhythmia Classification.
Sign Up to like & getrecommendations! 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 & getrecommendations! 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
WavelNet: A novel convolutional neural network architecture for arrhythmia classification from electrocardiograms
Sign Up to like & getrecommendations! 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 & getrecommendations! 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
An Arrhythmia Classification Model Based on Vision Transformer with Deformable Attention
Sign Up to like & getrecommendations! Published in 2023 at "Micromachines"
DOI: 10.3390/mi14061155
Abstract: The electrocardiogram (ECG) is a highly effective non-invasive tool for monitoring heart activity and diagnosing cardiovascular diseases (CVDs). Automatic detection of arrhythmia based on ECG plays a critical role in the early prevention and diagnosis… read more here.
Keywords: arrhythmia; ecg; model; arrhythmia classification ... See more keywords