AIMC Topic: Arrhythmias, Cardiac

Clear Filters Showing 181 to 190 of 287 articles

Inter-Patient ECG Classification With Symbolic Representations and Multi-Perspective Convolutional Neural Networks.

IEEE journal of biomedical and health informatics Sep 23, 2019
This paper presents a novel deep learning framework for the inter-patient electrocardiogram (ECG) heartbeat classification. A symbolization approach especially designed for ECG is introduced, which can jointly represent the morphology and rhythm of t...
Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer Deep Learning
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Cardiac arrhythmia detection using deep learning: A review.

Journal of electrocardiology Aug 8, 2019
Due to its simplicity and low cost, analyzing an electrocardiogram (ECG) is the most common technique for detecting cardiac arrhythmia. The massive amount of ECG data collected every day, in home and hospital, may preclude data review by human operat...
Electrocardiography Arrhythmias, Cardiac Cardiac Conduction System Disease Machine Learning Deep Learning Humans
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Energy-Efficient Intelligent ECG Monitoring for Wearable Devices.

IEEE transactions on biomedical circuits and systems Jul 22, 2019
Wearable intelligent ECG monitoring devices can perform automatic ECG diagnosis in real time and send out alert signal together with abnormal ECG signal for doctor's further analysis. This provides a means for the patient to identify their heart prob...
Humans Neural Networks, Computer Signal Processing, Computer-Assisted Female Aged, 80 and over Arrhythmias, Cardiac Middle Aged Aged Adult Wearable Electronic Devices Male Electrocardiography
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A Novel Approach for Multi-Lead ECG Classification Using DL-CCANet and TL-CCANet.

Sensors (Basel, Switzerland) Jul 21, 2019
Cardiovascular disease (CVD) has become one of the most serious diseases that threaten human health. Over the past decades, over 150 million humans have died of CVDs. Hence, timely prediction of CVDs is especially important. Currently, deep learning ...
Cardiovascular Diseases Deep Learning Electrocardiography Algorithms Databases, Factual Heart Rate Support Vector Machine Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans
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Electrocardiogram Classification Based on Faster Regions with Convolutional Neural Network.

Sensors (Basel, Switzerland) Jun 5, 2019
The classification of electrocardiograms (ECG) plays an important role in the clinical diagnosis of heart disease. This paper proposes an effective system development and implementation for ECG classification based on faster regions with a convolutio...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Electrocardiography Support Vector Machine Humans Neural Networks, Computer Software Algorithms Databases, Factual
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Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings.

Physiological measurement Jun 4, 2019
OBJECTIVE: We aim to combine deep neural networks and engineered features (hand-crafted features based on medical domain knowledge) for cardiac arrhythmia detection from short single-lead ECG recordings.
Neural Networks, Computer Algorithms Deep Learning Electrocardiography Arrhythmias, Cardiac Humans
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I-Vector-Based Patient Adaptation of Deep Neural Networks for Automatic Heartbeat Classification.

IEEE journal of biomedical and health informatics May 29, 2019
Automatic classification of electrocardiogram (ECG) signals is important for diagnosing heart arrhythmias. A big challenge in automatic ECG classification is the variation in the waveforms and characteristics of ECG signals among different patients. ...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Neural Networks, Computer Heart Rate Algorithms Humans Electrocardiography
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A new approach for arrhythmia classification using deep coded features and LSTM networks.

Computer methods and programs in biomedicine May 10, 2019
BACKGROUND AND OBJECTIVE: For diagnosis of arrhythmic heart problems, electrocardiogram (ECG) signals should be recorded and monitored. The long-term signal records obtained are analyzed by expert cardiologists. Devices such as the Holter monitor hav...
Data Compression Databases, Factual Electrocardiography, Ambulatory Humans Electrocardiography Software Reproducibility of Results Arrhythmias, Cardiac Neural Networks, Computer Principal Component Analysis Pattern Recognition, Automated Data Management Algorithms Signal Processing, Computer-Assisted
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An Efficient Cardiac Arrhythmia Onset Detection Technique Using a Novel Feature Rank Score Algorithm.

Journal of medical systems May 6, 2019
The interpretation of various cardiovascular blood flow abnormalities can be identified using Electrocardiogram (ECG). The predominant anomaly due to the blood flow dynamics leads to the occurrence of cardiac arrhythmias in the cardiac system. In thi...
Humans Algorithms Electrocardiography Blood Flow Velocity Arrhythmias, Cardiac Support Vector Machine Heart Rate Signal Processing, Computer-Assisted Cardiac Output
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Assessment of Electrocardiogram Rhythms by GoogLeNet Deep Neural Network Architecture.

Journal of healthcare engineering Apr 28, 2019
The aim of this study is to design GoogLeNet deep neural network architecture by expanding the kernel size of the inception layer and combining the convolution layers to classify the electrocardiogram (ECG) beats into a normal sinus rhythm, premature...
Signal Processing, Computer-Assisted Sensitivity and Specificity Arrhythmias, Cardiac Humans Internet Deep Learning Databases, Factual Electrocardiography
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