ECG signal processing, classification and interpretation a comprehensive framework of computational intelligence /
<p>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 prove...
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| Format: | eBook |
| Language: | English |
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London
Springer
2012.
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| Online Access: | Click here to view the full text content |
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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.