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.
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.
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.
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.
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 212 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
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.
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.
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 85 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.
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:
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 210 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.
Download or read book Using Neural Networks for the Recognition of Cardiac ECG Signals written by Ali Isin and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: An electrocardiogram (ECG) is a bioelectrical signal which records the heart's electrical activity versus time. It is an important diagnostic tool for assessing heart functions. In this book, pattern recognition techniques are used for the interpretation of an ECG signal. The techniques used in this pattern recognition application are, signal pre-processing, QRS detection, feature extraction and artificial neural network for signal and cardiac condition (healthy or a certain disease) classification. In this book, the signal processing and neural network toolbox are used in Matlab environment. The processed signal source came from the Massachusetts Institute of Technology Beth Israel Hospital (MIT-BIH) arrhythmia database which was developed for research in cardiac electrophysiology. Three conditions of ECG waveform were selected from MIT-BIH database in this book. The ECG samples were pre-processed, then features representing the each sample were extracted to produce a set of features that can be used in a neural network to make the classification of samples and the recognition rates were recorded. The book is focused on finding an easy but reliable feature extraction method.
Download or read book Introduction to ECG Interpretation written by Dawn Y. Bean and published by . This book was released on 1987 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and published by Academic Press. This book was released on 2019-03-16 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. - Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction - Explains how to apply machine learning techniques to EEG, ECG and EMG signals - Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series
Download or read book Advances in Cardiac Signal Processing written by U. Rajendra Acharya and published by Springer Science & Business Media. This book was released on 2007-04-25 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive review of progress in the acquisition and extraction of electrocardiogram signals. The coverage is extensive, from a review of filtering techniques to measurement of heart rate variability, to aortic pressure measurement, to strategies for assessing contractile effort of the left ventricle and more. The book concludes by assessing the future of cardiac signal processing, leading to next generation research which directly impact cardiac health care.
Download or read book Trends in Intelligent Robotics Automation and Manufacturing written by S.G. Poonambalam and published by Springer. This book was released on 2012-11-28 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the First International Conference on Intelligent Robotics and Manufacturing, IRAM 2012, held in Kuala Lumpur, Malaysia, in November 2012. The 64 revised full papers included in this volume were carefully reviewed and selected from 102 initial submissions. The papers are organized in topical sections named: mobile robots, intelligent autonomous systems, robot vision and robust, autonomous agents, micro, meso and nano-scale automation and assembly, flexible manufacturing systems, CIM and micro-machining, and fabrication techniques.
Download or read book Photoplethysmography written by Panicos A. Kyriacou and published by Academic Press. This book was released on 2021-11-03 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Photoplethysmography: Technology, Signal Analysis, and Applications is the first comprehensive volume on the theory, principles, and technology (sensors and electronics) of photoplethysmography (PPG). It provides a detailed description of the current state-of-the-art technologies/optical components enabling the extreme miniaturization of such sensors, as well as comprehensive coverage of PPG signal analysis techniques including machine learning and artificial intelligence. The book also outlines the huge range of PPG applications in healthcare, with a strong focus on the contribution of PPG in wearable sensors and PPG for cardiovascular assessment. - Presents the underlying principles and technology surrounding PPG - Includes applications for healthcare and wellbeing - Focuses on PPG in wearable sensors and devices - Presents advanced signal analysis techniques - Includes cutting-edge research, applications and future directions
Download or read book Advanced Machine Learning Technologies and Applications written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-05-25 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the 5th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2020), held at Manipal University Jaipur, India, on February 13 – 15, 2020, and organized in collaboration with the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic and security, as well as intelligence swarms and optimization.
