Supervised Learning Methods for ECG Classification/ Neural Networks and SVM Approaches - Chapter 12

Stanislaw Osowski, Linh Tran Hoai, and Tomasz Markiewicz

This page provides supplementary information and relevant links for Chapter 12 in Advanced Methods for ECG Analysis, which is co-edited by Francisco Azuaje and Patrick McSharry, and is published by Artech House. The main URL for this book can be found here, together with ordering information. Much of the software associated with this book can be found here.

 

Links:

• ECGtools - A selection of ECG analysis tools in Matlab including a self-explaining QRS detector, filtering tools and HRV analysis algorithms. Includes FIR, SVD, ICA and Wiener filtering code. 
• Netlab -- A free set of pattern recognition & neural network tools in Matlab by Ian Nabney. the associated book is simply wonderful. 

 

Contents:

12.1 Introduction

 

12.2 Generation of Features

12.2.1 Hermite Basis Function Expansion

12.2.2 HOS Features of the ECG

12.3 Supervised Neural Classifiers

12.3.1 Multilayer Perceptron

12.3.2 Hybrid Fuzzy Network

12.3.3 TSK Neuro-Fuzzy Network

12.3.4 Support Vector Machine Classifiers

12.4 Integration of Multiple Classifiers

 

12.5 Results of Numerical Experiments

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12.6 Conclusions