ECG Signal Processing, Classification and Interpretation A Comprehensive Framework of Computational Intelligence /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Gacek, Adam (Editor), Pedrycz, Witold (Editor)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2012.
• Subjects: Engineering.; Cardiology.; Computational intelligence.; Biomedical engineering.; Biomedical Engineering.; Signal, Image and Speech Processing.; Computational Intelligence.

Electrocardiogram (ECG) signals are among the most important sources of diagnostic information in healthcare so improvements in their analysis may also have telling consequences. Both the underlying signal technology and a burgeoning variety of algorithms and systems developments have proved success...

Table of Contents:

• Part I: Introduction
• Introduction to ECG Signal Processing
• Fuzzy Sets: A Primer
• Neural Networks and Neurocomputing
• Evolutionary and Population-based Optimization
• Part II: Techniques and Models of Computational Intelligence for ECG Signal Analysis and Classification
• Neurocomputing in ECG Signal Classification
• Knowledge-based Representation and Processing of ECG Signals: A Fuzzy Set Approach
• Evolutionary Optimization of ECG Signal Analysis and Classification
• Granular Models of ECG Signal Analysis and Their Refinements and Abstractions
• Hybrid Architectures of ECG Analyzers and Classifiers. Part III: Computational-intelligence-based ECG System Diagnostic, Interpretation and Knowledge Acquisition Architectures
• Diagnostic ECG Systems and Computational Intelligence: Development Issues
• Interpretation of ECG Signals: A Systems Approach
• Knowledge Representation and ECG Diagnostic and Interpretation Systems.