Arrhythmias

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was pr...

Model-Based Feature Augmentation for Cardiac Ablation Target Learning From Images.

GOAL: We present a model-based feature augmentation scheme to improve the performance of a learning algorithm for the detection of cardiac radio-frequency ablation (RFA) targets with respect to learning from images alone.

Multiclass Classification of Cardiac Arrhythmia Using Improved Feature Selection and SVM Invariants.

Arrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias ...

Randomized controlled trial of Amigo® robotically controlled versus manually controlled ablation of the cavo-tricuspid isthmus using a contact force ablation catheter.

BACKGROUND: Radiofrequency catheter ablation (RFCA) of the cavo-tricuspid isthmus (CTI) is a common treatment for atrial flutter (AFL). However, achie...

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

BACKGROUND: Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extract...

Automatic QRS complex detection using two-level convolutional neural network.

BACKGROUND: The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal ...

Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rat...

Real-time estimation of lesion depth and control of radiofrequency ablation within ex vivo animal tissues using a neural network.

BACKGROUND: Radiofrequency ablation (RFA), a method of inducing thermal ablation (cell death), is often used to destroy tumours or potentially cancero...

Quantitative Assessment of the Physiological Parameters Influencing QT Interval Response to Medication: Application of Computational Intelligence Tools.

Human heart electrophysiology is complex biological phenomenon, which is indirectly assessed by the measured ECG signal. ECG trace is further analyzed...

Application of stacked convolutional and long short-term memory network for accurate identification of CAD ECG signals.

Coronary artery disease (CAD) is the most common cause of heart disease globally. This is because there is no symptom exhibited in its initial phase u...

Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks.

BACKGROUND: Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac rep...

Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection.

Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac d...

Catheter Ablation of Focal Atrial Tachycardia Using Remote Magnetic Navigation.

OBJECTIVES: The outcomes of catheter ablation in focal atrial tachycardia (AT) using remote magnetic navigation (RMN) are still controversial. The obj...

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 i...

Lyme disease presenting with facial palsy and myocarditis mimicking myocardial infarction.

A 45-year-old woman presented with a sudden episode of typical chest pain, radiating to her neck. The patient denied premature coronary artery disease...

Real-Time Multilead Convolutional Neural Network for Myocardial Infarction Detection.

In this paper, a novel algorithm based on a convolutional neural network (CNN) is proposed for myocardial infarction detection via multilead electroca...

ECG data compression using a neural network model based on multi-objective optimization.

Electrocardiogram (ECG) data analysis is of great significance to the diagnosis of cardiovascular disease. ECG compression should be processed in real...

Localization of Origins of Premature Ventricular Contraction by Means of Convolutional Neural Network From 12-Lead ECG.

OBJECTIVE: This paper proposes a novel method to localize origins of premature ventricular contractions (PVCs) from 12-lead electrocardiography (ECG) ...

A deep convolutional neural network model to classify heartbeats.

The electrocardiogram (ECG) is a standard test used to monitor the activity of the heart. Many cardiac abnormalities will be manifested in the ECG inc...

A Wireless ExG Interface for Patch-Type ECG Holter and EMG-Controlled Robot Hand.

This paper presents a wearable electrophysiological interface with enhanced immunity to motion artifacts. Anti-artifact schemes, including a patch-typ...