Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …
Computational diagnostic techniques for electrocardiogram signal analysis
Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina,
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …
Automatic ECG classification using continuous wavelet transform and convolutional neural network
Early detection of arrhythmia and effective treatment can prevent deaths caused by
cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the …
cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the …
LSTM-based ECG classification for continuous monitoring on personal wearable devices
S Saadatnejad, M Oveisi… - IEEE journal of biomedical …, 2019 - ieeexplore.ieee.org
Objective: A novel electrocardiogram (ECG) classification algorithm is proposed for
continuous cardiac monitoring on wearable devices with limited processing capacity …
continuous cardiac monitoring on wearable devices with limited processing capacity …
A deep learning approach for ECG-based heartbeat classification for arrhythmia detection
Classification is one of the most popular topics in healthcare and bioinformatics, especially
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
Real-time patient-specific ECG classification by 1-D convolutional neural networks
Goal: This paper presents a fast and accurate patient-specific electrocardiogram (ECG)
classification and monitoring system. Methods: An adaptive implementation of 1-D …
classification and monitoring system. Methods: An adaptive implementation of 1-D …
[HTML][HTML] ECG-based heartbeat classification for arrhythmia detection: A survey
An electrocardiogram (ECG) measures the electric activity of the heart and has been widely
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
Deep learning approach for active classification of electrocardiogram signals
In this paper, we propose a novel approach based on deep learning for active classification
of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation …
of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation …
Detecting atrial fibrillation by deep convolutional neural networks
Background Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of
AF increases with age, causing high risks of stroke and increased morbidity and mortality …
AF increases with age, causing high risks of stroke and increased morbidity and mortality …
A novel application of deep learning for single-lead ECG classification
Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with
cardiac abnormalities. In this paper, a novel approach based on deep learning methodology …
cardiac abnormalities. In this paper, a novel approach based on deep learning methodology …