ECG Signal Processing, Classification and Interpretation

ECG Signal Processing, Classification and Interpretation

Author: Adam Gacek

Publisher: Springer Science & Business Media

Published: 2011-09-18

Total Pages: 283

ISBN-13: 0857298682

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The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.


Book Synopsis ECG Signal Processing, Classification and Interpretation by : Adam Gacek

Download or read book ECG Signal Processing, Classification and Interpretation written by Adam Gacek and published by Springer Science & Business Media. This book was released on 2011-09-18 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.

ECG Signal Processing, Classification and Interpretation

ECG Signal Processing, Classification and Interpretation

Author: Adam Gacek

Publisher: Springer

Published: 2013-01-02

Total Pages: 278

ISBN-13: 9780857298690

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The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.


Book Synopsis ECG Signal Processing, Classification and Interpretation by : Adam Gacek

Download or read book ECG Signal Processing, Classification and Interpretation written by Adam Gacek and published by Springer. This book was released on 2013-01-02 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.

Advanced Methods and Tools for ECG Data Analysis

Advanced Methods and Tools for ECG Data Analysis

Author: Gari D. Clifford

Publisher: Artech House Publishers

Published: 2006

Total Pages: 412

ISBN-13:

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This practical book is the first one-stop resource to offer a thorough, up-to-date treatment of the techniques and methods used in electrocardiogram (ECG) data analysis, from fundamental principles to the latest tools in the field. The book places emphasis on the selection, modeling, classification, and interpretation of data based on advanced signal processing and artificial intelligence techniques.


Book Synopsis Advanced Methods and Tools for ECG Data Analysis by : Gari D. Clifford

Download or read book Advanced Methods and Tools for ECG Data Analysis written by Gari D. Clifford and published by Artech House Publishers. This book was released on 2006 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical book is the first one-stop resource to offer a thorough, up-to-date treatment of the techniques and methods used in electrocardiogram (ECG) data analysis, from fundamental principles to the latest tools in the field. The book places emphasis on the selection, modeling, classification, and interpretation of data based on advanced signal processing and artificial intelligence techniques.

Feature Engineering and Computational Intelligence in ECG Monitoring

Feature Engineering and Computational Intelligence in ECG Monitoring

Author: Chengyu Liu

Publisher: Springer Nature

Published: 2020-06-24

Total Pages: 264

ISBN-13: 9811538247

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This book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these methods can be efficiently used to address the emerging challenges of dynamic, continuous & long-term individual ECG monitoring and real-time feedback. By doing so, it provides a “snapshot” of the current research at the interface between physiological signal analysis and machine learning. It also helps clarify a number of dilemmas and encourages further investigations in this field, to explore rational applications of feature engineering and computational intelligence in ECG monitoring. The book is intended for researchers and graduate students in the field of biomedical engineering, ECG signal processing, and intelligent healthcare.


Book Synopsis Feature Engineering and Computational Intelligence in ECG Monitoring by : Chengyu Liu

Download or read book Feature Engineering and Computational Intelligence in ECG Monitoring written by Chengyu Liu and published by Springer Nature. This book was released on 2020-06-24 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these methods can be efficiently used to address the emerging challenges of dynamic, continuous & long-term individual ECG monitoring and real-time feedback. By doing so, it provides a “snapshot” of the current research at the interface between physiological signal analysis and machine learning. It also helps clarify a number of dilemmas and encourages further investigations in this field, to explore rational applications of feature engineering and computational intelligence in ECG monitoring. The book is intended for researchers and graduate students in the field of biomedical engineering, ECG signal processing, and intelligent healthcare.

Developments and Applications for ECG Signal Processing

Developments and Applications for ECG Signal Processing

Author: Joao Paulo do Vale Madeiro

Publisher: Academic Press

Published: 2018-11-29

Total Pages: 210

ISBN-13: 0128140364

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Developments and Applications for ECG Signal Processing: Modeling, Segmentation, and Pattern Recognition covers reliable techniques for ECG signal processing and their potential to significantly increase the applicability of ECG use in diagnosis. This book details a wide range of challenges in the processes of acquisition, preprocessing, segmentation, mathematical modelling and pattern recognition in ECG signals, presenting practical and robust solutions based on digital signal processing techniques. Users will find this to be a comprehensive resource that contributes to research on the automatic analysis of ECG signals and extends resources relating to rapid and accurate diagnoses, particularly for long-term signals. Chapters cover classical and modern features surrounding f ECG signals, ECG signal acquisition systems, techniques for noise suppression for ECG signal processing, a delineation of the QRS complex, mathematical modelling of T- and P-waves, and the automatic classification of heartbeats. Gives comprehensive coverage of ECG signal processing Presents development and parametrization techniques for ECG signal acquisition systems Analyzes and compares distortions caused by different digital filtering techniques for noise suppression applied over the ECG signal Describes how to identify if a digitized ECG signal presents irreversible distortion through analysis of its frequency components prior to, and after, filtering Considers how to enhance QRS complexes and differentiate these from artefacts, noise, and other characteristic waves under different scenarios


Book Synopsis Developments and Applications for ECG Signal Processing by : Joao Paulo do Vale Madeiro

Download or read book Developments and Applications for ECG Signal Processing written by Joao Paulo do Vale Madeiro and published by Academic Press. This book was released on 2018-11-29 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developments and Applications for ECG Signal Processing: Modeling, Segmentation, and Pattern Recognition covers reliable techniques for ECG signal processing and their potential to significantly increase the applicability of ECG use in diagnosis. This book details a wide range of challenges in the processes of acquisition, preprocessing, segmentation, mathematical modelling and pattern recognition in ECG signals, presenting practical and robust solutions based on digital signal processing techniques. Users will find this to be a comprehensive resource that contributes to research on the automatic analysis of ECG signals and extends resources relating to rapid and accurate diagnoses, particularly for long-term signals. Chapters cover classical and modern features surrounding f ECG signals, ECG signal acquisition systems, techniques for noise suppression for ECG signal processing, a delineation of the QRS complex, mathematical modelling of T- and P-waves, and the automatic classification of heartbeats. Gives comprehensive coverage of ECG signal processing Presents development and parametrization techniques for ECG signal acquisition systems Analyzes and compares distortions caused by different digital filtering techniques for noise suppression applied over the ECG signal Describes how to identify if a digitized ECG signal presents irreversible distortion through analysis of its frequency components prior to, and after, filtering Considers how to enhance QRS complexes and differentiate these from artefacts, noise, and other characteristic waves under different scenarios

Classification of ECG Signals

Classification of ECG Signals

Author: Sahana Ramesh

Publisher:

Published: 2016

Total Pages: 98

ISBN-13:

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Electrocardiogram (ECG) plays an enormous role in the medical field. An electrocardiograph is a device used in cardiology, which records heart's electrical signals over time. ECG can be used to determine various heart diseases or damages to the heart along with the pace at which the heart beats as well as the effects of drugs or devices used to control the heart. The interpretation of the ECG signals is an application of pattern recognition. The technique used in this project integrates the study of the ECG signals and their classification. Analysis of ECG signals is done using neural network pattern recognition and classification methods. The study includes simulation of ECG signals, comparison between ECG signals, and detection of any abnormalities in the signal by using effective learning algorithms & pattern recognition techniques. The processed signals used in this project are obtained from an arrhythmia database, which was developed for research in cardiac electrophysiology by Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH). The neural clustering application available in the pattern recognition tool software is used to classify ECG signals based on self-organizing maps. Self-organizing maps are used to cluster the data, based on the similarity and topology, which reduces the dimensionality of the data. Thus, after training the network using the classification tool, a given ECG signal can be classified as normal or arrhythmic signal based on its features.


Book Synopsis Classification of ECG Signals by : Sahana Ramesh

Download or read book Classification of ECG Signals written by Sahana Ramesh and published by . This book was released on 2016 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electrocardiogram (ECG) plays an enormous role in the medical field. An electrocardiograph is a device used in cardiology, which records heart's electrical signals over time. ECG can be used to determine various heart diseases or damages to the heart along with the pace at which the heart beats as well as the effects of drugs or devices used to control the heart. The interpretation of the ECG signals is an application of pattern recognition. The technique used in this project integrates the study of the ECG signals and their classification. Analysis of ECG signals is done using neural network pattern recognition and classification methods. The study includes simulation of ECG signals, comparison between ECG signals, and detection of any abnormalities in the signal by using effective learning algorithms & pattern recognition techniques. The processed signals used in this project are obtained from an arrhythmia database, which was developed for research in cardiac electrophysiology by Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH). The neural clustering application available in the pattern recognition tool software is used to classify ECG signals based on self-organizing maps. Self-organizing maps are used to cluster the data, based on the similarity and topology, which reduces the dimensionality of the data. Thus, after training the network using the classification tool, a given ECG signal can be classified as normal or arrhythmic signal based on its features.

Leveraging Data Science for Global Health

Leveraging Data Science for Global Health

Author: Leo Anthony Celi

Publisher: Springer Nature

Published: 2020-07-31

Total Pages: 471

ISBN-13: 3030479943

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This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.


Book Synopsis Leveraging Data Science for Global Health by : Leo Anthony Celi

Download or read book Leveraging Data Science for Global Health written by Leo Anthony Celi and published by Springer Nature. This book was released on 2020-07-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.

Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias

Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias

Author: Hani Saleh

Publisher: Springer

Published: 2017-10-20

Total Pages: 74

ISBN-13: 3319639730

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This book presents techniques necessary to predict cardiac arrhythmias, long before they occur, based on minimal ECG data. The authors describe the key information needed for automated ECG signal processing, including ECG signal pre-processing, feature extraction and classification. The adaptive and novel ECG processing techniques introduced in this book are highly effective and suitable for real-time implementation on ASICs.


Book Synopsis Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias by : Hani Saleh

Download or read book Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias written by Hani Saleh and published by Springer. This book was released on 2017-10-20 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents techniques necessary to predict cardiac arrhythmias, long before they occur, based on minimal ECG data. The authors describe the key information needed for automated ECG signal processing, including ECG signal pre-processing, feature extraction and classification. The adaptive and novel ECG processing techniques introduced in this book are highly effective and suitable for real-time implementation on ASICs.

Aspects of ECG Signal Processing with Application to Classification

Aspects of ECG Signal Processing with Application to Classification

Author: Ian Burns

Publisher:

Published: 1997

Total Pages: 262

ISBN-13:

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Book Synopsis Aspects of ECG Signal Processing with Application to Classification by : Ian Burns

Download or read book Aspects of ECG Signal Processing with Application to Classification written by Ian Burns and published by . This book was released on 1997 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities

Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities

Author: Moein, Sara

Publisher: IGI Global

Published: 2018-05-25

Total Pages: 196

ISBN-13: 1522555811

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Technological tools and computational techniques have enhanced the healthcare industry. These advancements have led to significant progress in the diagnosis of heart disorders. Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities is a critical scholarly resource that examines the importance of automatic normalization and classification of electrocardiogram (ECG) signals of heart disorders. Featuring a wide range of topics such as common heart disorders, particle swarm optimization, and benchmarks functions, this publication is geared toward medical professionals, researchers, professionals, and students seeking current and relevant research on the categorization of ECG signals.


Book Synopsis Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities by : Moein, Sara

Download or read book Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities written by Moein, Sara and published by IGI Global. This book was released on 2018-05-25 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological tools and computational techniques have enhanced the healthcare industry. These advancements have led to significant progress in the diagnosis of heart disorders. Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities is a critical scholarly resource that examines the importance of automatic normalization and classification of electrocardiogram (ECG) signals of heart disorders. Featuring a wide range of topics such as common heart disorders, particle swarm optimization, and benchmarks functions, this publication is geared toward medical professionals, researchers, professionals, and students seeking current and relevant research on the categorization of ECG signals.