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

2018/03/28 by Özal Yildirim, Özal Yıldırım · 830 citations
Engineering · Mathematics · Medicine · Neuroscience · #Artificial intelligence #Artificial neural network #Beat (acoustics) #Block (permutation group theory) #Computer science #Deep learning #ECG Monitoring and Analysis #EEG and Brain-Computer Interfaces #Electrocardiography #Left bundle branch block #Mathematics #Non-Invasive Vital Sign Monitoring #Pattern recognition (psychology) #Recurrent neural network #Right bundle branch block #Speech recognition #Wavelet

paper · doi:10.1016/j.compbiomed.2018.03.016

published in Computers in Biology and Medicine 96, 189-202 (Elsevier BV)

openalex publication_date 2018/03/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25

Citations

• Gradient-based learning applied to document recognition
• ImageNet classification with deep convolutional neural networks

Cited by

• Automated arrhythmia detection with homeomorphically irreducible tree technique using more than 10,000 individual subject ECG records
• Knowledge-Guided Cross-Modal Fusion for Adult-to-Pediatric ECG Transfer via Label-Conditioned Contrastive Alignment
• Consciousness-ECG Transformer for Conscious State Estimation System with Real-Time Monitoring
• SE-ECGNet: A Multi-scale Deep Residual Network with Squeeze-and-Excitation Module for ECG Signal Classification
• Deep learning in ECG diagnosis: A review
• Heart-Darts: Classification of Heartbeats Using Differentiable Architecture Search
• A Novel Feature Representation for Single-Channel Heartbeat Classification based on Adaptive Fourier Decomposition
• Real-time structural damage assessment using LSTM networks: regression and classification approaches
• System for Neural Network Determination of Atrial Fibrillation on ECG Signals with Wavelet-Based Preprocessing
• FOUND-AF: Benchmarking ECG Foundation Models for Atrial Fibrillation Detection
• A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals. [europepmc]
• Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia. [europepmc]
• A primer in artificial intelligence in cardiovascular medicine. [europepmc]
• Electrocardiogram Classification Based on Faster Regions with Convolutional Neural Network. [europepmc]
• Sequential Factorized Autoencoder for Localizing the Origin of Ventricular Activation From 12-Lead Electrocardiograms. [europepmc]
• An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset. [europepmc]
• Deep Learning in Physiological Signal Data: A Survey. [europepmc]
• A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation Study. [europepmc]
• Automated detection of cardiovascular disease by electrocardiogram signal analysis: a deep learning system. [europepmc]
• ECG Identification For Personal Authentication Using LSTM-Based Deep Recurrent Neural Networks. [europepmc]
• Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records. [europepmc]
• Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram Signals. [europepmc]
• Computational Diagnostic Techniques for Electrocardiogram Signal Analysis. [europepmc]
• Forecasting COVID-19 cases: A comparative analysis between recurrent and convolutional neural networks. [europepmc]
• Diagnosis of Alzheimer's Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal. [europepmc]
• A deep learning algorithm to translate and classify cardiac electrophysiology. [europepmc]
• Deep Learning Techniques in the Classification of ECG Signals Using R-Peak Detection Based on the PTB-XL Dataset. [europepmc]
• A Review of Recurrent Neural Network-Based Methods in Computational Physiology. [europepmc]
• ECG Recurrence Plot-Based Arrhythmia Classification Using Two-Dimensional Deep Residual CNN Features. [europepmc]
• An Effective and Lightweight Deep Electrocardiography Arrhythmia Recognition Model Using Novel Special and Native Structural Regularization Techniques on Cardiac Signal. [europepmc]
• Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning. [europepmc]
• A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram. [europepmc]
• An End-to-End Cardiac Arrhythmia Recognition Method with an Effective DenseNet Model on Imbalanced Datasets Using ECG Signal. [europepmc]
• An Automatic Premature Ventricular Contraction Recognition System Based on Imbalanced Dataset and Pre-Trained Residual Network Using Transfer Learning on ECG Signal. [europepmc]
• Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017-2023. [europepmc]