ATRIAL FIBRILLATION FROM AN ENGINEERING PERSPECTIVE

Transcription

1 Leif Sörnmo (editor) ATRIAL FIBRILLATION FROM AN ENGINEERING PERSPECTIVE February 26, 2018 Springer

2 Contents 1 A Clinical Perspective on Atrial Fibrillation Pyotr G. Platonov and Valentina D. A. Corino 1.1 Introduction Atrial Fibrillation: Definition Classification of Atrial Fibrillation Epidemiology of Atrial Fibrillation Mechanisms of Atrial Fibrillation Atrial Myocardium Characteristics in Atrial Fibrillation Atrial Fibrillation and Stroke Principles of Atrial Fibrillation Management Ischemic stroke prevention Rate-control strategy Rhythm-control strategy Electrocardiography in Atrial Fibrillation Diagnosis Standardization of Atrial Fibrillation ECG Characteristics Assessment Electrocardiographic characteristics as biomarkers Roadmap for standardization of AF parameters References Lead Systems and Recording Devices Andrius Petrėnas, Vaidotas Marozas, and Leif Sörnmo 2.1 Introduction Lead Systems Body surface potential mapping Modifications of the standard 12-lead ECG Reduced lead systems Recording Devices Standard resting ECG Standard ambulatory monitors Cardiac event recorders v

3 vi Contents Biopatches Handheld recorders Smartphone-based devices Implantable devices Non-ECG devices Monitoring strategies References Databases and Simulation Leif Sörnmo, Andrius Petrėnas, and Vaidotas Marozas 3.1 Public ECG Databases Non-Public ECG Databases Simulation of Atrial Fibrillation Simulation of Paroxysmal AF Using Synthetic Components Atrial fibrillation Sinus rhythm Atrial premature beats Respiration Additive noise Transformation from VCG to 12-lead ECG Switching between atrial fibrillation and sinus rhythm Simulation of Paroxysmal AF Using Real Components Relevance of Simulated Signals References Detection of Atrial Fibrillation Leif Sörnmo, Andrius Petrėnas, and Vaidotas Marozas 4.1 Introduction Rhythm-based AF Detection Irregularity parameters Poincaré-based parameters Time-varying coherence function Parameter time series exemplified Ectopic beat handling Classification Rhythm and Morphology based AF Detection P wave detection information f wave detection information Noise level estimation Ectopic beat handling Classification Implementation Aspects Performance measures Detection Performance ECG databases

4 Contents vii Training and evaluation Simulated ECG signals Brief AF episodes Additional Detector Information References Extraction of f waves Leif Sörnmo, Andrius Petrėnas, Pablo Laguna, and Vaidotas Marozas 5.1 Introduction Average Beat Subtraction and Variants Noise-dependent weights Signal- and noise-dependent weighted averaging Spatiotemporal QRST cancellation Separate cancellation of the QRS and JQ intervals Residual-constrained QRS template Interpolation and Large-Amplitude QRS Residuals Sine/cosine-based interpolation Autoregressive interpolation Extended Kalman Filtering Adaptive Filtering Least mean square linear filtering Nonlinear filtering based on a simple recurrent network Nonlinear filtering based on an echo state network Principal Component Analysis Single-lead PCA Multi-lead PCA Multi-lead PCA of single beats Singular Spectral Analysis Autoregressive Modeling and Prediction Error Analysis Independent Component Analysis f waves and modeling assumptions f wave identification Performance Measures Real signals Simulated signals Extraction Performance References Characterization of f waves Leif Sörnmo, Raúl Alcaraz, Pablo Laguna, and José Joaquín Rieta 6.1 Introduction f wave Amplitude Atrial Fibrillatory Rate and Beyond Dominant atrial frequency Spectral parameters

5 viii Contents Time frequency analysis Frequency tracking f wave Morphology and Regularity Phase analysis PCA-based characterization of regularity Similarity-based characterization of regularity Entropy-based characterization of regularity Signal Quality Control Time domain analysis Frequency domain analysis Spatial Characterization Vectorcardiogram loop analysis Body surface potential mapping f wave Characterization in Clinical Applications Monitoring of drug response Prediction of catheter ablation outcome Prediction of cardioversion outcome Prediction of spontaneous AF termination Detection and characterization of circadian variation References Modeling and Analysis of Ventricular Response in Atrial Fibrillation 281 Valentina D. A. Corino, Frida Sandberg, Luca T. Mainardi, and Leif Sörnmo 7.1 Introduction RR Interval Analysis Heuristic Assessment of the Atrioventricular Node Synchrogram Analysis Mathematical Modeling of the Atrioventricular Node Modeling of conduction delay in non-af rhythms Modeling of conduction delay in AF Modeling of refractory period in AF Modeling of refractory period and conduction delay in AF Modeling of spatial dynamics Statistical Modeling of the Atrioventricular Node and Parameter Estimation A first statistical model of the AV node Statistical modeling of dual AV nodal pathways Statistical modeling of pathway switching Comparison of AV Models References Acronyms Index