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ECG Signal Processing, Classification and Interpretation

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Cover of 'ECG Signal Processing, Classification and Interpretation'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 An Introduction to ECG Interpretation
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    Chapter 2 An Introduction to ECG Signal Processing and Analysis
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    Chapter 3 ECG Signal Analysis, Classification, and Interpretation: A Framework of Computational Intelligence
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    Chapter 4 A Generic and Patient-Specific Electrocardiogram Signal Classification System
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    Chapter 5 Model-Based Atrial Fibrillation Detection
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    Chapter 6 An Introduction to the Use of Evolutionary Computation Techniques for Dealing with ECG Signals
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    Chapter 7 Electrocardiogram Application Based on Heart Rate Variability Ontology and Fuzzy Markup Language
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    Chapter 8 Learning in Artificial Neural Networks
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    Chapter 9 A Review of Kernel Methods in ECG Signal Classification
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    Chapter 10 Hyperellipsoidal Classifier for Beat Classification in ECG Signals
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    Chapter 11 Evolutionary Optimization of ECG Feature Extraction Methods: Applications to the Monitoring of Adult Myocardial Ischemia and Neonatal Apnea Bradycardia Events
Attention for Chapter 6: An Introduction to the Use of Evolutionary Computation Techniques for Dealing with ECG Signals
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Citations

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Chapter title
An Introduction to the Use of Evolutionary Computation Techniques for Dealing with ECG Signals
Chapter number 6
Book title
ECG Signal Processing, Classification and Interpretation
Published by
Springer, London, January 2012
DOI 10.1007/978-0-85729-868-3_6
Book ISBNs
978-0-85729-867-6, 978-0-85729-868-3
Authors

Guillermo Leguizamón, Carlos A. Coello

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Researcher 2 29%
Student > Bachelor 1 14%
Professor 1 14%
Unknown 1 14%
Readers by discipline Count As %
Computer Science 3 43%
Engineering 2 29%
Unknown 2 29%

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