ECG arrhythmia classification by using a recurrence plot and convolutional neural network
BM Mathunjwa, YT Lin, CH Lin, MF Abbod… - … Signal Processing and …, 2021 - Elsevier
Cardiovascular diseases affect approximately 50 million people worldwide; thus, heart
disease prevention is one of the most important tasks of any health care system. Despite the …
disease prevention is one of the most important tasks of any health care system. Despite the …
A study on arrhythmia via ECG signal classification using the convolutional neural network
M Wu, Y Lu, W Yang, SY Wong - Frontiers in computational …, 2021 - frontiersin.org
Cardiovascular diseases (CVDs) are the leading cause of death today. The current
identification method of the diseases is analyzing the Electrocardiogram (ECG), which is a …
identification method of the diseases is analyzing the Electrocardiogram (ECG), which is a …
[HTML][HTML] A review on deep learning methods for ECG arrhythmia classification
Z Ebrahimi, M Loni, M Daneshtalab… - Expert Systems with …, 2020 - Elsevier
Deep Learning (DL) has recently become a topic of study in different applications including
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
Automated arrhythmia classification based on a combination network of CNN and LSTM
C Chen, Z Hua, R Zhang, G Liu, W Wen - Biomedical Signal Processing …, 2020 - Elsevier
Arrhythmia is an abnormal heartbeat rhythm, and its prevalence increases with age. An
electrocardiogram (ECG) is a standard tool for detecting cardiac activity. However, because …
electrocardiogram (ECG) is a standard tool for detecting cardiac activity. However, because …
Arrhythmia classification techniques using deep neural network
Electrocardiogram (ECG) is the most common and low‐cost diagnostic tool used in
healthcare institutes for screening heart electrical signals. The abnormal heart signals are …
healthcare institutes for screening heart electrical signals. The abnormal heart signals are …
Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals
YD Daydulo, BL Thamineni, AA Dawud - BMC Medical Informatics and …, 2023 - Springer
Background Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances
in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically …
in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically …
Arrhythmia classification with ECG signals based on the optimization-enabled deep convolutional neural network
Arrhythmia classification is the need of the hour as the world is reporting a higher death troll
as a cause of cardiac diseases. Most of the existing methods developed for arrhythmia …
as a cause of cardiac diseases. Most of the existing methods developed for arrhythmia …
Machine learning approach to detect cardiac arrhythmias in ECG signals: A survey
Cardiac arrhythmia is a condition when the heart rate is irregular either the beat is too slow
or too fast. It occurs due to improper electrical impulses that coordinates the heart beats …
or too fast. It occurs due to improper electrical impulses that coordinates the heart beats …
ECG recurrence plot-based arrhythmia classification using two-dimensional deep residual CNN features
In this paper, an effective electrocardiogram (ECG) recurrence plot (RP)-based arrhythmia
classification algorithm that can be implemented in portable devices is presented. Public …
classification algorithm that can be implemented in portable devices is presented. Public …
[HTML][HTML] Electrocardiogram based arrhythmia classification using wavelet transform with deep learning model
High-risk patients of cardiovascular disease can be provided with computerized
electrocardiogram (ECG) devices to detect Arrhythmia. These require long segments of …
electrocardiogram (ECG) devices to detect Arrhythmia. These require long segments of …