Automated ECG multi-class classification system based on combining deep learning features with HRV and ECG measures
AS Eltrass, MB Tayel, AI Ammar - Neural Computing and Applications, 2022 - Springer
Electrocardiogram (ECG) serves as the gold standard for noninvasive diagnosis of several
types of heart disorders. In this study, a novel hybrid approach of deep neural network …
types of heart disorders. In this study, a novel hybrid approach of deep neural network …
A novel proposed CNN–SVM architecture for ECG scalograms classification
Nowadays, the number of sudden deaths due to heart disease is increasing with the
coronavirus pandemic. Therefore, automatic classification of electrocardiogram (ECG) …
coronavirus pandemic. Therefore, automatic classification of electrocardiogram (ECG) …
[HTML][HTML] An IOT framework for detecting cardiac arrhythmias in real-time using deep learning resnet model
A cardiac arrhythmia poses a serious health risk to patients and can have serious
consequences for their health. A clinical assessment of arrhythmia disorders could save a …
consequences for their health. A clinical assessment of arrhythmia disorders could save a …
A Hybrid Compressive Sensing and Classification Approach for Dynamic Storage Management of Vital Biomedical Signals
The efficient compression and classification of medical signals, particularly
electroencephalography (EEG) and electrocardiography (ECG) signals in wireless body …
electroencephalography (EEG) and electrocardiography (ECG) signals in wireless body …
[HTML][HTML] RHYTHMI: A deep learning-based mobile ECG device for heart disease prediction
A Eleyan, E AlBoghbaish, A AlShatti, A AlSultan… - Applied System …, 2024 - mdpi.com
Heart disease, a global killer with many variations like arrhythmia and heart failure, remains
a major health concern. Traditional risk factors include age, cholesterol, diabetes, and blood …
a major health concern. Traditional risk factors include age, cholesterol, diabetes, and blood …
Electrocardiogram Signals Classification Using Deep-Learning-Based Incorporated Convolutional Neural Network and Long Short-Term Memory Framework
A Eleyan, E Alboghbaish - Computers, 2024 - mdpi.com
Cardiovascular diseases (CVDs) like arrhythmia and heart failure remain the world's leading
cause of death. These conditions can be triggered by high blood pressure, diabetes, and …
cause of death. These conditions can be triggered by high blood pressure, diabetes, and …
Detection of heart arrhythmia based on UCMFB and deep learning technique
Severe cardiovascular diseases (CVD) are the leading cause of death worldwide. In the
emergency scenario, reliable electrocardiography (ECG) is critical for the rapid diagnosis …
emergency scenario, reliable electrocardiography (ECG) is critical for the rapid diagnosis …
Categorizing the heart syndrome condition by predictive analysis using machine learning approach
R Krishnamoorthy, BS Liya, S Arun… - … on Advances in …, 2021 - ieeexplore.ieee.org
As the age of the elderly patients are getting increased, the health factors are also getting
affected. By the drastic increase of the human being population, the health factor has to be …
affected. By the drastic increase of the human being population, the health factor has to be …
[PDF][PDF] Gait cycle prediction model based on gait kinematic using machine learning technique for assistive rehabilitation device
The gait cycle prediction model is critical for controlling assistive rehabilitation equipment
like orthosis. The human gait model has recently used statistical models, but the dynamic …
like orthosis. The human gait model has recently used statistical models, but the dynamic …
Abnormalities analysis of electrocardiogram signals by using artificial intelligence
ECG recordings has been commonly used biological experiment for analysing the lot of
heart issues. Moreover, timely identification of arrhythmia will help to recognise the …
heart issues. Moreover, timely identification of arrhythmia will help to recognise the …