Catalogue


Biosignal processing : principles and practices /
edited by Hualou Liang, Joseph D. Bronzino, Donald R. Peterson.
imprint
Boca Raton : CRC Press, c2013.
description
1 v. (various pagings) : ill. (some col.) ; 26 cm.
ISBN
1439871434 (hardcover : alk. paper), 9781439871430 (hardcover : alk. paper)
format(s)
Book
Holdings
More Details
imprint
Boca Raton : CRC Press, c2013.
isbn
1439871434 (hardcover : alk. paper)
9781439871430 (hardcover : alk. paper)
contents note
Digital biomedical signal acquisition and processing / Luca Mainardi, Sergio Cerutti -- Time-frequency signal representations for biomedical signals / G. Faye Boudreaux-Bartels and Robin Murray -- Multivariate spectral analysis of EEG : power, coherence, and second-order blind identification / Ramesh Srinivasan and Siyi Deng -- General linear modeling of magnetoencephalography data / Dimitrios Pantazis, Juan Luis Poletti Soto, Richard M. Leahy -- Emergence of groupwise registration in MR brain study / Guorong Wu ... [et al.] -- Functional optical brain imaging / Meltem Izzetoglu -- Causality analysis of multivariate neural data / Maciej Kaminski, Hualou Liang.
abstract
"This book provides state-of-the-art coverage of contemporary methods in biosignal processing, with emphasis on brain signal analysis. The topics covered in this book reflect an ongoing evolution in biosignal processing. As biomedical data sets grow larger and more complicated, emerging signal processing methods to analyze and interpret these data have gained in importance. This book discusses the process for biosignal analysis and stimulates new ideas and opportunities for developing cutting-edge computational methods for biosignal processing, which will in turn accelerate laboratory discoveries into treatments for patients. Provides a general overview of basic concepts in biomedical signal acquisition and processing. Discusses nonstationary and transient nature of signals by introducing time-frequency analysis and its applications to signal analysis and detection problems in bioengineering. Covers emerging methods for brain signal processing, each focusing on specific non-invasive imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), magnetic resonance imaging (MRI) and functional near-infrared spectroscopy (fNIR). Explores a multivariate spectral analysis of EEG data using power, coherence and second-order blind identification. Introduces a general linear modeling approach for the analysis of induced and evoked response in MEG. Presents the progress in groupwise registration algorithms for effective MRI medical image analysis. Examines the basis of optical imaging, fNIR instrumentation and signal analysis in various cognitive studies. Reviews recent advances of causal influence measures such as Granger causality for analyzing multivariate neural data"--Provided by publisher.
catalogue key
8833468
 
Includes bibliographical references and index.
A Look Inside
Reviews
This item was reviewed in:
Reference & Research Book News, December 2012
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Summaries
Bowker Data Service Summary
With the rise of advanced computerized data collection systems, monitoring devices, and instrumentation technologies, large and complex datasets accrue as an inevitable part of biomedical enterprise. The availability of these massive amounts of data offers unprecedented opportunities to advance our understanding of underlying biological and physiological functions, structures, and dynamics. This book provides state-of-the-art coverage of contemporary methods in biosignal processing with an emphasis on brain signal analysis.
Main Description
With the rise of advanced computerized data collection systems, monitoring devices, and instrumentation technologies, large and complex datasets accrue as an inevitable part of biomedical enterprise. The availability of these massive amounts of data offers unprecedented opportunities to advance our understanding of underlying biological and physiological functions, structures, and dynamics. Biosignal Processing: Principles and Practicesprovides state-of-the-art coverage of contemporary methods in biosignal processing with an emphasis on brain signal analysis. After introducing the fundamentals, it presents emerging methods for brain signal processing, focusing on specific non-invasive imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), magnetic resonance imaging (MRI), and functional near-infrared spectroscopy (fNIR). In addition, the book presents recent advances, reflecting the evolution of biosignal processing. As biomedical datasets grow larger and more complicated, the development and use of signal processing methods to analyze and interpret these data has become a matter of course. This book is one step in the development of biosignal analysis and is designed to stimulate new ideas and opportunities in the development of cutting-edge computational methods for biosignal processing.
Main Description
This book provides state-of-the-art coverage of contemporary methods in biosignal processing, with emphasis on brain signal analysis. The topics covered in this book reflect an ongoing evolution in biosignal processing. As biomedical data sets grow larger and more complicated, emerging signal processing methods to analyze and interpret these data have gained in importance. This book discusses the process for biosignal analysis and stimulates new ideas and opportunities for developing cutting-edge computational methods for biosignal processing, which will in turn accelerate laboratory discoveries into treatments for patients.
Main Description
With the rise of advanced computerized data collection systems, monitoring devices, and instrumentation technologies, large and complex datasets accrue as an inevitable part of biomedical enterprise. The availability of these massive amounts of data offers unprecedented opportunities to advance our understanding of underlying biological and physiological functions, structures, and dynamics. Biosignal Processing: Principles and Practices provides state-of-the-art coverage of contemporary methods in biosignal processing with an emphasis on brain signal analysis. After introducing the fundamentals, it presents emerging methods for brain signal processing, focusing on specific non-invasive imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), magnetic resonance imaging (MRI), and functional near-infrared spectroscopy (fNIR). In addition, the book presents recent advances, reflecting the evolution of biosignal processing. As biomedical datasets grow larger and more complicated, the development and use of signal processing methods to analyze and interpret these data has become a matter of course. This book is one step in the development of biosignal analysis and is designed to stimulate new ideas and opportunities in the development of cutting-edge computational methods for biosignal processing.
Library of Congress Summary
"This book provides state-of-the-art coverage of contemporary methods in biosignal processing, with emphasis on brain signal analysis. The topics covered in this book reflect an ongoing evolution in biosignal processing. As biomedical data sets grow larger and more complicated, emerging signal processing methods to analyze and interpret these data have gained in importance. This book discusses the process for biosignal analysis and stimulates new ideas and opportunities for developing cutting-edge computational methods for biosignal processing, which will in turn accelerate laboratory discoveries into treatments for patients. Provides a general overview of basic concepts in biomedical signal acquisition and processing. Discusses nonstationary and transient nature of signals by introducing time-frequency analysis and its applications to signal analysis and detection problems in bioengineering. Covers emerging methods for brain signal processing, each focusing on specific non-invasive imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), magnetic resonance imaging (MRI) and functional near-infrared spectroscopy (fNIR). Explores a multivariate spectral analysis of EEG data using power, coherence and second-order blind identification. Introduces a general linear modeling approach for the analysis of induced and evoked response in MEG. Presents the progress in groupwise registration algorithms for effective MRI medical image analysis. Examines the basis of optical imaging, fNIR instrumentation and signal analysis in various cognitive studies. Reviews recent advances of causal influence measures such as Granger causality for analyzing multivariate neural data"--Provided by publisher.
Table of Contents
Prefacep. vii
Editorsp. ix
Contributorsp. xi
Digital Biomedical Signal Acquisition and Processingp. 1-1
Time-Frequency Signal Representations for Biomedical Signalsp. 2-1
Multivariate Spectral Analysis of Electroencephalogram: Power, Coherence, and Second-Order Blind Identificationp. 3-1
General Linear Modeling of Magnetoencephalography Datap. 4-1
Emergence of Groupwise Registration in MR Brain Studyp. 5-1
Functional Optical Brain Imagingp. 6-1
Causality Analysis of Multivariate Neural Datap. 7-1
Indexp. Index-1
Table of Contents provided by Ingram. All Rights Reserved.

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