Atrial fibrillation

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Atrial fibrillation (AF or A-fib) is the most common cardiac arrhythmia (abnormal heart rhythm), and involves the two upper chambers of the heart. (Wikipedia.org)






Conferences related to Atrial fibrillation

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2013 Computing in Cardiology Conference (CinC)

Provide a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology.

  • 2012 Computing in Cardiology Conference (CinC)

    Provide a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology.

  • 2011 Computing in Cardiology Conference (CinC)

    Provides a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology.

  • 2010 Computing in Cardiology (CinC)

    Computing in Cardiology (formerly Computers in Cardiology) is one of the premier events focusing on computer applications in clinical cardiology and cardiovascular research. The conference fosters interdisciplinary discussions and collaboration among physicians, engineers, physicists, biologists, computer scientists and others in research and development in Cardiology.

  • 2009 36th Annual Computers in Cardiology Conference (CinC)

    The Computers in Cardiology conference provides an international forum for scientific presentations focusing on computer applications in clinical cardiology and cardiovascular research. The conference fosters interdisciplinary discussions and collaboration between physicians, engineers, physicists, biologists, computer scientists and others engaged in research in this area.

  • 2008 35th Annual Computers in Cardiology Conference (CinC)

    The Computers in Cardiology conference provides an international forum for scientific presentations focusing on computer applications in clinical cardiology and cardiovascular research. The conference fosters interdisciplinary discussions between scientists and professionals from different fields including medicine, physics, engineering, biology, information technology, computer science and others engaged in research in this area.

  • 2007 34th Annual Computers in Cardiology Conference (CinC)

    The Computers in Cardiology conference provides an international forum for scientific presentations focusing on computer applications in clinical cardiology and cardiovascular research. The conference fosters interdisciplinary discussions and collaboration between physicians, engineers, physicists, biologists, computer scientists, and others engaged in research in this area.

  • 2006 Computers in Cardiology Conference

  • 2005 Computers in Cardiology Conference


2011 IEEE 7th International Symposium on Intelligent Signal Processing - (WISP 2011)

2011 WISP will highlight how the use of intelligent signal processing, contribute towards the solution of current challenges for systems measurements and promote emerging technologies. It aims to strengthen relations between industry, research laboratories, and universities.

  • 2009 IEEE International Symposium on Intelligent Signal Processing - (WISP 2009)

    to highlight how the use of intelligent signal processing, contribute towards the solution of current challenges for systems measurements and promote emerging technologies. It aims to strengthen relations between industry, research laboratories, and universities.

  • 2007 IEEE International Symposium on Intelligent Signal Processing - (WISP 2007)

    Topics will include, but are not limited to: analogue, digital and mixed signal processing, modelling, diagnostics, control, uncertainty-handling, artificial intelligence, soft computing techniques, anytime algorithms, emerging technologies, adaptive and non-linear processing, intelligent signal processing, sensors, embedded systems, real-time systems, distributed measurement, diagnostics and control systems, system id and control, VLSI/ASIC for intelligent signal processing.



Periodicals related to Atrial fibrillation

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Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.



Most published Xplore authors for Atrial fibrillation

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Xplore Articles related to Atrial fibrillation

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Contributions for the optimal lead placement for the study of atrial fibrillation applying Independent Component Analysis to 64 body surface potential mapping recordings

J. Millet-Roig; M. S. Guillem; J. Igual; R. Llinares; R. Ruiz 2006 Computers in Cardiology, 2006

The interest in the study and analysis of atrial fibrillation has increased significantly in the last decades. A correct estimation of the atrial activity is a crucial previous step for AF analysis. Different methods based on independent component analysis of 12-lead ECG have been proposed. However, they don't work for a reduced number of leads. The purpose of this study ...


Electrophysiological models for the heterogeneous canine atria: Computational platform for studying rapid atrial arrhythmias

Oleg V. Aslanidi; Timothy D. Butters; Christopher X. Ren; Gareth Ryecroft; Henggui Zhang 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Heterogeneity in the electrical action potential (AP) properties can provide a substrate for atrial arrhythmias, especially at rapid pacing rates. In order to quantify such substrates, we develop a family of detailed AP models for canine atrial cells. An existing model for the canine right atrial (RA) myocyte was modified based on electrophysiological data from dog to create new models ...


A new method for analysis of atrial activation during chronic atrial fibrillation in man

M. Holm; R. Johansson; B. Olsson; J. Brandt; C. Luhrs IEEE Transactions on Biomedical Engineering, 1996

To further clarify the mechanisms maintaining chronic atrial fibrillation (CAF), a method identifying preferable activation patterns of the atria during fibrillation, by time averaging of multiple discrete excitation vectors, was developed. Repeated recordings, each of 56 atrial bipolar electrograms simultaneously acquired during 8 s, were made at multiple sites in the right atrial free wall and the left atrial appendage ...


Prediction of Spontaneous Termination of Atrial Fibrillation with Supervised Neural Networks

Germán E. Melo A.; Ricardo A. Osorio M.; Alvaro D. Orjuela C. 2012 VI Andean Region International Conference, 2012

This paper presents a proposal of ECG analysis, which determines a spontaneous termination of atrial fibrilation prediction. Supervised neural networks are trained to develop this task, where a comparison is carried out between multilayer perceptron (MLP) and supervised self organized maps (SOM). Principal component analysis (PCA) is implemented to reduce the input dimensionality. Results show maximum classification rates of 100% ...


Detection of Long Term Variations of Heart Rate Variability in Normal Sinus Rhythm and Atrial Fibrillation ECG Data

Desok Kim; Yunhwan Seo; Woo Ram Jung; Chan-Hyun Youn 2008 International Conference on BioMedical Engineering and Informatics, 2008

Circadian variations of heart rate variability (HRV) have been well known in cardiac diseases. However, long term HRV features were not thoroughly investigated for the prediction of atrial fibrillation (AF). Thus, we analyzed the 15 hour long changes of HRV of normal sinus rhythm (NSR) and AF data. Long term patterns of HR V in NSR were established first and ...


More Xplore Articles

Educational Resources on Atrial fibrillation

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eLearning

Contributions for the optimal lead placement for the study of atrial fibrillation applying Independent Component Analysis to 64 body surface potential mapping recordings

J. Millet-Roig; M. S. Guillem; J. Igual; R. Llinares; R. Ruiz 2006 Computers in Cardiology, 2006

The interest in the study and analysis of atrial fibrillation has increased significantly in the last decades. A correct estimation of the atrial activity is a crucial previous step for AF analysis. Different methods based on independent component analysis of 12-lead ECG have been proposed. However, they don't work for a reduced number of leads. The purpose of this study ...


Electrophysiological models for the heterogeneous canine atria: Computational platform for studying rapid atrial arrhythmias

Oleg V. Aslanidi; Timothy D. Butters; Christopher X. Ren; Gareth Ryecroft; Henggui Zhang 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Heterogeneity in the electrical action potential (AP) properties can provide a substrate for atrial arrhythmias, especially at rapid pacing rates. In order to quantify such substrates, we develop a family of detailed AP models for canine atrial cells. An existing model for the canine right atrial (RA) myocyte was modified based on electrophysiological data from dog to create new models ...


A new method for analysis of atrial activation during chronic atrial fibrillation in man

M. Holm; R. Johansson; B. Olsson; J. Brandt; C. Luhrs IEEE Transactions on Biomedical Engineering, 1996

To further clarify the mechanisms maintaining chronic atrial fibrillation (CAF), a method identifying preferable activation patterns of the atria during fibrillation, by time averaging of multiple discrete excitation vectors, was developed. Repeated recordings, each of 56 atrial bipolar electrograms simultaneously acquired during 8 s, were made at multiple sites in the right atrial free wall and the left atrial appendage ...


Prediction of Spontaneous Termination of Atrial Fibrillation with Supervised Neural Networks

Germán E. Melo A.; Ricardo A. Osorio M.; Alvaro D. Orjuela C. 2012 VI Andean Region International Conference, 2012

This paper presents a proposal of ECG analysis, which determines a spontaneous termination of atrial fibrilation prediction. Supervised neural networks are trained to develop this task, where a comparison is carried out between multilayer perceptron (MLP) and supervised self organized maps (SOM). Principal component analysis (PCA) is implemented to reduce the input dimensionality. Results show maximum classification rates of 100% ...


Detection of Long Term Variations of Heart Rate Variability in Normal Sinus Rhythm and Atrial Fibrillation ECG Data

Desok Kim; Yunhwan Seo; Woo Ram Jung; Chan-Hyun Youn 2008 International Conference on BioMedical Engineering and Informatics, 2008

Circadian variations of heart rate variability (HRV) have been well known in cardiac diseases. However, long term HRV features were not thoroughly investigated for the prediction of atrial fibrillation (AF). Thus, we analyzed the 15 hour long changes of HRV of normal sinus rhythm (NSR) and AF data. Long term patterns of HR V in NSR were established first and ...


More eLearning Resources

IEEE.tv Videos

No IEEE.tv Videos are currently tagged "Atrial fibrillation"

IEEE-USA E-Books

  • No title

    The book presents recent advances in signal processing techniques for modeling, analysis, and understanding of the heart's electrical activity during atrial fibrillation. This arrhythmia is the most commonly encountered in clinical practice and its complex and metamorphic nature represents a challenging problem for clinicians, engineers, and scientists. Research on atrial fibrillation has stimulated the development of a wide range of signal processing tools to better understand the mechanisms ruling its initiation, maintenance, and termination. This book provides undergraduate and graduate students, as well as researchers and practicing engineers, with an overview of techniques, including time domain techniques for atrial wave extraction, time- frequency analysis for exploring wave dynamics, and nonlinear techniques to characterize the ventricular response and the organization of atrial activity. The book includes an introductory chapter about atrial fibrillation and its mechanisms, t eatment, and management. The successive chapters are dedicated to the analysis of atrial signals recorded on the body surface and to the quantification of ventricular response. The rest of the book explores techniques to characterize endo- and epicardial recordings and to model atrial conduction. Under the appearance of being a monothematic book on atrial fibrillation, the reader will not only recognize common problems of biomedical signal processing but also discover that analysis of atrial fibrillation is a unique challenge for developing and testing novel signal processing tools.

  • No title

    The book presents recent advances in signal processing techniques for modeling, analysis, and understanding of the heart's electrical activity during atrial fibrillation. This arrhythmia is the most commonly encountered in clinical practice and its complex and metamorphic nature represents a challenging problem for clinicians, engineers, and scientists. Research on atrial fibrillation has stimulated the development of a wide range of signal processing tools to better understand the mechanisms ruling its initiation, maintenance, and termination. This book provides undergraduate and graduate students, as well as researchers and practicing engineers, with an overview of techniques, including time domain techniques for atrial wave extraction, time- frequency analysis for exploring wave dynamics, and nonlinear techniques to characterize the ventricular response and the organization of atrial activity. The book includes an introductory chapter about atrial fibrillation and its mechanisms, t eatment, and management. The successive chapters are dedicated to the analysis of atrial signals recorded on the body surface and to the quantification of ventricular response. The rest of the book explores techniques to characterize endo- and epicardial recordings and to model atrial conduction. Under the appearance of being a monothematic book on atrial fibrillation, the reader will not only recognize common problems of biomedical signal processing but also discover that analysis of atrial fibrillation is a unique challenge for developing and testing novel signal processing tools. Table of Contents: Analysis of Ventricular Response During Atrial Fibrillation / Organization Measures of Atrial Activity During Fibrillation / Modeling Atrial Fibrillation: From Myocardial Cells to ECG / Algorithms for Atrial Tachyarrythmia Detection for Long-Term Monitoring with Implantable Devices



Standards related to Atrial fibrillation

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No standards are currently tagged "Atrial fibrillation"


Jobs related to Atrial fibrillation

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